model: Capacity cannot decrease over time

Capacity was being incorrectly multiplied by T twice. This
happened because there were two references to the same struct
in the plant sizes array. This fix replaces the second reference
by an actual copy of the struct.

.dockerignore

@@ -0,0 +1,4 @@
+build
+jobs
+relog-web/node_modules
+relog-web/build

.github/workflows/lint.yml

@@ -14,10 +14,10 @@ jobs:
         shell: julia --color=yes {0}
         run: |
           using Pkg
-          Pkg.add(PackageSpec(name="JuliaFormatter", version="0.14.4"))
+          Pkg.add(PackageSpec(name="JuliaFormatter", version="1"))
           using JuliaFormatter
           format("src", verbose=true)
-          format("test", verbose=true)
+          format("test/src", verbose=true)
           out = String(read(Cmd(`git diff`)))
           if isempty(out)
               exit(0)

.github/workflows/test.yml

@@ -10,7 +10,7 @@ jobs:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        version: ['1.3', '1.4', '1.5', 'nightly']
+        version: ['1.6', '1.7', '1.8']
         os:
           - ubuntu-latest
         arch:
@@ -21,5 +21,15 @@ jobs:
         with:
           version: ${{ matrix.version }}
           arch: ${{ matrix.arch }}
-      - uses: julia-actions/julia-buildpkg@v1
+      - name: Run tests
-      - uses: julia-actions/julia-runtest@v1
+        shell: julia --color=yes --project=test {0}
+        run: |
+          using Pkg
+          Pkg.develop(path=".")
+          Pkg.update()
+          using RELOGT
+          try
+            runtests()
+          catch
+            exit(1)
+          end

.gitignore

@@ -12,3 +12,8 @@ Manifest.toml
 data
 build
 benchmark
+run.jl
+relog-web-legacy
+.vscode
+jobs
+tmp

.zenodo.json

@@ -0,0 +1,28 @@
+{
+  "creators": [
+    {
+      "orcid": "0000-0002-5022-9802",
+      "affiliation": "Argonne National Laboratory",
+      "name": "Santos Xavier, Alinson"
+    },
+    {
+      "orcid": "0000-0002-3426-9425",
+      "affiliation": "Argonne National Laboratory",
+      "name": "Iloeje, Chukwunwike"
+    },
+    {
+      "affiliation": "Argonne National Laboratory",
+      "name": "Atkins, John"
+    },
+    {
+      "affiliation": "Argonne National Laboratory",
+      "name": "Sun, Kyle"
+    },
+    {
+      "affiliation": "Argonne National Laboratory",
+      "name": "Gallier, Audrey"
+    }
+  ],
+  "title": "RELOG: Reverse Logistics Optimization",
+  "description": "<b>RELOG</b> is a supply chain optimization package focusing on reverse logistics and reverse manufacturing. For example, the package can be used to determine where to build recycling plants, what sizes should they have and which customers should be served by which plants. The package supports customized reverse logistics pipelines, with multiple types of plants, multiple types of product and multiple time periods."
+}

CHANGELOG.md

@@ -1,28 +0,0 @@
-# Version 0.5.0 (Jan 6, 2021)
-
-- Allow plants to store input material for processing in later years
-
-# Version 0.4.0 (Sep 18, 2020)
-
-- Generate simplified solution reports (CSV)
-
-# Version 0.3.3 (Aug 13, 2020)
-
-- Add option to write solution to JSON file in RELOG.solve
-- Improve error message when instance is infeasible
-- Make output file more readable
-
-# Version 0.3.2 (Aug 7, 2020)
-
-- Add "building period" parameter
-
-# Version 0.3.1 (July 17, 2020)
-
-- Fix expansion cost breakdown
-
-# Version 0.3.0 (June 25, 2020)
-
-- Track emissions and energy (transportation and plants)
-- Minor changes to input file format:
-    - Make all dictionary keys lowercase
-    - Rename "outputs (tonne)" to "outputs (tonne/tonne)"

COPYING.md

@@ -1,25 +0,0 @@
-Copyright © 2020, UChicago Argonne, LLC
-
-All Rights Reserved
-
-Software Name: RELOG
-
-By: Argonne National Laboratory
-
-OPEN SOURCE LICENSE
--------------------
-
-Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
-
-1. Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
-2. Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
-3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.
-
-********************************************************************************
-
-DISCLAIMER
-----------
-
-THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
-
-********************************************************************************

Makefile

@@ -1,28 +0,0 @@
-JULIA := julia --color=yes --project=@.
-SRC_FILES := $(wildcard src/*.jl test/*.jl)
-VERSION := 0.5
-
-all: docs test
-
-build/sysimage.so: src/sysimage.jl Project.toml Manifest.toml
-	mkdir -p build
-	$(JULIA) src/sysimage.jl
-
-build/test.log: $(SRC_FILES) build/sysimage.so
-	cd test; $(JULIA) --sysimage ../build/sysimage.so runtests.jl
-
-clean:
-	rm -rf build/*
-
-docs:
-	mkdocs build -d ../docs/$(VERSION)/
-
-format:
-	julia -e 'using JuliaFormatter; format(["src", "test"], verbose=true);'
-
-test: build/test.log
-
-test-watch:
-	bash -c "while true; do make test --quiet; sleep 1; done"
-
-.PHONY: docs test

Project.toml

@@ -1,47 +1,18 @@
 name = "RELOG"
-uuid = "a2afcdf7-cf04-4913-85f9-c0d81ddf2008"
+uuid = "7cafaa7a-b311-45f0-b313-80bf15b5e5e5"
-authors = ["Alinson S Xavier <axavier@anl.gov>"]
+authors = ["Alinson S. Xavier <git@axavier.org>"]
-version = "0.5.0"
+version = "0.8.0"
 
 [deps]
 CRC = "44b605c4-b955-5f2b-9b6d-d2bd01d3d205"
 CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
-Cbc = "9961bab8-2fa3-5c5a-9d89-47fab24efd76"
-Clp = "e2554f3b-3117-50c0-817c-e040a3ddf72d"
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
-DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
-Downloads = "f43a241f-c20a-4ad4-852c-f6b1247861c6"
-GZip = "92fee26a-97fe-5a0c-ad85-20a5f3185b63"
 Geodesy = "0ef565a4-170c-5f04-8de2-149903a85f3d"
 JSON = "682c06a0-de6a-54ab-a142-c8b1cf79cde6"
-JSONSchema = "7d188eb4-7ad8-530c-ae41-71a32a6d4692"
 JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
-LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
+NearestNeighbors = "b8a86587-4115-5ab1-83bc-aa920d37bbce"
-MathOptInterface = "b8f27783-ece8-5eb3-8dc8-9495eed66fee"
 OrderedCollections = "bac558e1-5e72-5ebc-8fee-abe8a469f55d"
-PackageCompiler = "9b87118b-4619-50d2-8e1e-99f35a4d4d9d"
 Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
-ProgressBars = "49802e3a-d2f1-5c88-81d8-b72133a6f568"
-Shapefile = "8e980c4a-a4fe-5da2-b3a7-4b4b0353a2f4"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
-Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+TimerOutputs = "a759f4b9-e2f1-59dc-863e-4aeb61b1ea8f"
 ZipFile = "a5390f91-8eb1-5f08-bee0-b1d1ffed6cea"
-
-[compat]
-CRC = "4"
-CSV = "0.7"
-Cbc = "0.6"
-Clp = "0.8"
-DataFrames = "0.21"
-DataStructures = "0.17"
-GZip = "0.5"
-Geodesy = "0.5"
-JSON = "0.21"
-JSONSchema = "0.3"
-JuMP = "0.21"
-MathOptInterface = "0.9"
-PackageCompiler = "1"
-ProgressBars = "0.6"
-Shapefile = "0.7"
-ZipFile = "0.9"
-julia = "1"

README.md

@@ -1,8 +1,5 @@
-<h1 align="center">RELOG: Reverse Logistics Optimization</h1>
+<h1 align="center">RELOG: Supply Chain Analysis and Optimization</h1>
 <p align="center">
-  <a href="https://github.com/ANL-CEEESA/RELOG/actions">
-    <img src="https://github.com/ANL-CEEESA/RELOG/workflows/CI/badge.svg">
-  </a>
   <a href="https://doi.org/10.5281/zenodo.4302341">
     <img src="https://zenodo.org/badge/DOI/10.5281/zenodo.4302341.svg">
   </a>
@@ -11,29 +8,44 @@
   </a>
 </p>
 
-**RELOG** is a supply chain optimization package focusing on reverse logistics and reverse manufacturing. For example, the package can be used to determine where to build recycling plants, what sizes should they have and which customers should be served by which plants. The package supports customized reverse logistics pipelines, with multiple types of plants, multiple types of product and multiple time periods.
+**RELOG** is an open-source package designed to optimize supply chains for
+forward, reverse and circular manufacturing. Using mixed-integer linear
+optimization, RELOG helps users determine strategic decisions such as:
 
+- Where and when to build manufacturing and recycling plants
+- The size of these plants, when to expand them, and by how much
+- The sources for each plant's input materials and the destinations for their
+  processed outputs
+- Whether to process input materials immediately or store them for later use
 
+RELOG has been successfully applied in research at various laboratories and
+universities, focusing on areas like critical material recovery from spent NiMH
+and Li-Ion batteries, biomass processing for hydrogen production, and the
+recycling of electronics, plastics and solar PV materials, among others. See
+references for more details.
 
-<img src="https://anl-ceeesa.github.io/RELOG/0.5/images/ex_transportation.png" width="1000px"/>
+## Screenshots
 
-### Documentation
+<img src="https://raw.githubusercontent.com/ANL-CEEESA/RELOG/refs/heads/circular/docs/src/assets/relog.png" width="1000px"/>
 
-  * [Usage](https://anl-ceeesa.github.io/RELOG/0.5/usage)
+## Documentation
-  * [Input and Output Data Formats](https://anl-ceeesa.github.io/RELOG/0.5/format)
-  * [Simplified Solution Reports](https://anl-ceeesa.github.io/RELOG/0.5/reports)
-  * [Optimization Model](https://anl-ceeesa.github.io/RELOG/0.5/model)
 
-### Authors
+See official documentation at: https://anl-ceeesa.github.io/RELOG/
 
-* **Alinson S. Xavier,** Argonne National Laboratory <<axavier@anl.gov>>
+## Authors
-* **Nwike Iloeje,** Argonne National Laboratory <<ciloeje@anl.gov>>
 
-### License
+- **Alinson S. Xavier,** Argonne National Laboratory <axavier@anl.gov>
+- **Nwike Iloeje,** Argonne National Laboratory <ciloeje@anl.gov>
+- **Kavitha G. Menon,** Argonne National Laboratory
+- **John Atkins,** Argonne National Laboratory
+- **Kyle Sun,** Argonne National Laboratory
+- **Audrey Gallier,** Argonne National Laboratory
+
+## License
 
 ```text
 RELOG: Reverse Logistics Optimization
-Copyright © 2020, UChicago Argonne, LLC. All Rights Reserved.
+Copyright © 2020-2025, UChicago Argonne, LLC. All Rights Reserved.
 
 Redistribution and use in source and binary forms, with or without modification, are permitted
 provided that the following conditions are met:

docs/Project.toml

@@ -0,0 +1,5 @@
+[deps]
+BetterFileWatching = "c9fd44ac-77b5-486c-9482-9798bd063cc6"
+Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
+RELOG = "a2afcdf7-cf04-4913-85f9-c0d81ddf2008"
+Revise = "295af30f-e4ad-537b-8983-00126c2a3abe"

docs/make.jl

@@ -0,0 +1,26 @@
+using Documenter
+using RELOG
+using BetterFileWatching
+
+function make()
+    makedocs(
+        sitename="RELOG",
+        pages=[
+            "Home" => "index.md",
+            "User guide" => [
+                "problem.md",
+                "format.md",
+            ]
+        ],
+        format = Documenter.HTML(
+            assets=["assets/custom.css"],
+        )
+    )
+end
+
+function watch()
+    make()
+    watch_folder("src") do event
+        make()
+    end
+end

docs/src/assets/custom.css

@@ -0,0 +1,36 @@
+@media screen and (min-width: 1056px) {
+    #documenter .docs-main {
+      max-width: 65rem !important;
+    }
+}
+  
+
+tbody, thead, pre {
+    border: 1px solid rgba(0, 0, 0, 0.25);
+}
+
+table td, th {
+    padding: 8px;
+}
+
+table p {
+    margin-bottom: 0;
+}
+
+table td code {
+    white-space: nowrap;
+}
+
+table tr,
+table th {
+    border-bottom: 1px solid rgba(0, 0, 0, 0.1);
+}
+
+table tr:last-child {
+    border-bottom: 0;
+}
+
+code {
+    background-color: transparent;
+    color: rgb(232, 62, 140);
+}

docs/src/format.md

@@ -0,0 +1,249 @@
+# Input data format
+
+RELOG accepts as input a JSON file with five sections: `parameters`, `products`,
+`centers`, `plants` and `emissions`. Below, we describe each section in more
+detail.
+
+## Parameters
+
+| Key                       | Description                                                                                                                                                                                                                                                  |
+| :------------------------ | :----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `time horizon (years)`    | Number of years in the simulation.                                                                                                                                                                                                                           |
+| `building period (years)` | List of years in which we are allowed to open new plants. For example, if this parameter is set to `[1,2,3]`, we can only open plants during the first three years. By default, this equals `[1]`; that is, plants can only be opened during the first year. |
+| `distance metric`         | Metric used to compute distances between pairs of locations. Valid options are: `"Euclidean"`, for the straight-line distance between points; or `"driving"` for an approximated driving distance. If not specified, defaults to `"Euclidean"`.              |
+
+#### Example
+
+```json
+{
+  "parameters": {
+    "time horizon (years)": 4,
+    "building period (years)": [1],
+    "distance metric": "driving"
+  }
+}
+```
+
+## Products
+
+| Key                                         | Description                                                                                                                                                                                                                 |
+| :------------------------------------------ | :-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `transportation cost ($/km/tonne)`          | The cost to transport this product. Must be a time series.                                                                                                                                                                  |
+| `transportation energy (J/km/tonne)`        | The energy required to transport this product. Must be a time series. Optional.                                                                                                                                             |
+| `transportation emissions (tonne/km/tonne)` | A dictionary mapping the name of each greenhouse gas, produced to transport one tonne of this product along one kilometer, to the amount of gas produced (in tonnes). Must be a time series. Optional.                      |
+| `disposal limit (tonne)`                    | Global disposal limit for this product, per year, across all plants and centers. Entry may be `null` if unlimited. Note that individual plants and centers may also have their individual disposal limits for this product. |
+
+#### Example
+
+```json
+{
+  "products": {
+    "P1": {
+      "transportation cost ($/km/tonne)": 0.015,
+      "transportation energy (J/km/tonne)": 0.12,
+      "transportation emissions (tonne/km/tonne)": {
+        "CO2": 0.052,
+        "CH4": 0.003
+      },
+      "disposal limit (tonne)": 100.0
+    }
+  }
+}
+```
+
+## Centers
+
+| Key                             | Description                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
+| :------------------------------ | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- |
+| `latitude (deg)`                | The latitude of the center.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
+| `longitude (deg)`               | The longitude of the center.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                           |
+| `input`                         | The name of the product this center takes as input from the plants. May be `null` if the center accept no input product.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               |
+| `outputs`                       | List of output products collected by the center. May be `[]` if none.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  |
+| `fixed output (tonne)`          | Dictionary mapping the name of each output product to the amount generated by this center each year, regardless of how much input the center receives. For example, if this field equals to `{"P1": [1.0, 2.0, 3.0, 4.0]}`, then this center generates 1.0, 2.0, 3.0 and 4.0 tonnes of P2 in years 1, 2, 3 and 4, respectively.                                                                                                                                                                                                                                                                                        |
+| `variable output (tonne/tonne)` | Dictionary mapping the name of each output product to the amount of output generated, for each tonne of input material, and for each year after the input is received. For example, in a 4-year simulation, if this field equals to `{"P1": [0.1, 0.3, 0.6, 0.0]}` and the center receives 1.0, 2.0, 3.0 and 4.0 tonnes of input material in years 1, 2, 3 and 4, then the center will produce $1.0 * 0.1 = 0.1$ of P1 in the first year, $1.0 * 0.3 + 2.0 * 0.1 = 0.5$ the second year, $1.0 * 0.6 + 2.0 * 0.3 + 3.0 * 0.1 = 1.5$ in the third year, and $2.0 * 0.6 + 3.0 * 0.3 + 4.0 * 0.1 = 2.5$ in the final year. |
+| `revenue ($/tonne)`             | Revenue generated by each tonne of input material sent to the center. If the center accepts no input, this should be `null`                                                                                                                                                                                                                                                                                                                                                                                                                                                                                            |
+| `collection cost ($/tonne)`     | Dictionary mapping the name of each output product to the cost of collecting one tonne of the product.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 |
+| `operating cost ($)`            | Fixed cost to operate the center for one year, regardless of amount of product received or generated.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  |
+| `disposal limit (tonne)`        | Dictionary mapping the name of each output product to the maximum disposal amount allowed per year of the product at the center. Entry may be `null` if unlimited.                                                                                                                                                                                                                                                                                                                                                                                                                                                     |
+| `disposal cost ($/tonne)`       | Dictionary mapping the name of each output product to the cost to dispose one tonne of the product at the center.                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                      |
+
+```json
+{
+  "centers": {
+    "C1": {
+      "latitude (deg)": 41.881,
+      "longitude (deg)": -87.623,
+      "input": "P1",
+      "outputs": ["P2", "P3"],
+      "fixed output (tonne)": {
+        "P2": [100, 50, 0, 0],
+        "P3": [20, 10, 0, 0]
+      },
+      "variable output (tonne/tonne)": {
+        "P2": [0.12, 0.25, 0.12, 0.0],
+        "P3": [0.25, 0.25, 0.25, 0.0]
+      },
+      "revenue ($/tonne)": [12.0, 12.0, 12.0, 12.0],
+      "collection cost ($/tonne)": {
+        "P2": [0.25, 0.25, 0.25, 0.25],
+        "P3": [0.37, 0.37, 0.37, 0.37]
+      },
+      "operating cost ($)": [150.0, 150.0, 150.0, 150.0],
+      "disposal limit (tonne)": {
+        "P2": [0, 0, 0, 0],
+        "P3": [null, null, null, null]
+      },
+      "disposal cost ($/tonne)": {
+        "P2": [0.23, 0.23, 0.23, 0.23],
+        "P3": [1.0, 1.0, 1.0, 1.0]
+      }
+    },
+    "C2": {
+      "latitude (deg)": 41.881,
+      "longitude (deg)": -87.623,
+      "input": null,
+      "outputs": ["P4"],
+      "variable output (tonne/tonne)": {
+        "P4": [0, 0, 0, 0]
+      },
+      "fixed output (tonne)": {
+        "P4": [50, 60, 70, 80]
+      },
+      "revenue ($/tonne)": null,
+      "collection cost ($/tonne)": {
+        "P4": [0.25, 0.25, 0.25, 0.25]
+      },
+      "operating cost ($)": [150.0, 150.0, 150.0, 150.0],
+      "disposal limit (tonne)": {
+        "P4": [null, null, null, null]
+      },
+      "disposal cost ($/tonne)": {
+        "P4": [0, 0, 0, 0]
+      }
+    },
+    "C3": {
+      "latitude (deg)": 41.881,
+      "longitude (deg)": -87.623,
+      "input": "P1",
+      "outputs": [],
+      "variable output (tonne/tonne)": {},
+      "constant output (tonne)": {},
+      "revenue ($/tonne)": [12.0, 12.0, 12.0, 12.0],
+      "collection cost ($/tonne)": {},
+      "operating cost ($)": [150.0, 150.0, 150.0, 150.0],
+      "disposal limit (tonne)": {},
+      "disposal cost ($/tonne)": {}
+    }
+  }
+}
+```
+
+## Plants
+
+| Key                            | Description                                                                                                                                  |
+| :----------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------- |
+| `latitude (deg)`               | The latitude of the plant, in degrees.                                                                                                       |
+| `longitude (deg)`              | The longitude of the plant, in degrees.                                                                                                      |
+| `input mix (%)`                | Dictionary mapping the name of each input product to the amount required (as a percentage). Must sum to 100%.                                |
+| `output (tonne)`               | Dictionary mapping the name of each output product to the amount produced (in tonne) for one tonne of input mix.                             |
+| `processing emissions (tonne)` | A dictionary mapping the name of each greenhouse gas, produced to process each tonne of input, to the amount of gas produced (in tonne).     |
+| `storage cost ($/tonne)`       | Dictionary mapping the name of each input product to the cost of storing the product for one year at the plant for later processing.         |
+| `storage limit (tonne)`        | Dictionary mapping the name of each input product to the maximum amount allowed in storage at any time. May be `null` if unlimited.          |
+| `disposal cost ($/tonne)`      | Dictionary mapping the name of each output product to the cost of disposing it at the plant.                                                 |
+| `disposal limit (tonne)`       | Dictionary mapping the name of each output product to the maximum amount allowed to be disposed of at the plant. May be `null` if unlimited. |
+| `capacities`                   | List describing what plant sizes are allowed, and their characteristics.                                                                     |
+| `initial capacity (tonne)`     | Capacity already available. If the plant has not been built yet, this should be `0`.                                                         |
+
+The entries in the `capacities` list should be dictionaries with the following
+keys:
+
+| Key                                 | Description                                                                                         |
+| :---------------------------------- | :-------------------------------------------------------------------------------------------------- |
+| `size (tonne)`                      | The size of the plant.                                                                              |
+| `opening cost ($)`                  | The cost to open a plant of this size.                                                              |
+| `fixed operating cost ($)`          | The cost to keep the plant open, even if the plant doesn't process anything.                        |
+| `variable operating cost ($/tonne)` | The cost that the plant incurs to process each tonne of input. Must be the same for all capacities. |
+
+```json
+{
+  "plants": {
+    "L1": {
+      "latitude (deg)": 41.881,
+      "longitude (deg)": -87.623,
+      "input mix (%)": {
+        "P1": 95.3,
+        "P2": 4.7
+      },
+      "output (tonne)": {
+        "P3": 0.25,
+        "P4": 0.12,
+        "P5": 0.1
+      },
+      "processing emissions (tonne)": {
+        "CO2": 0.1
+      },
+      "storage cost ($/tonne)": {
+        "P1": 0.1,
+        "P2": 0.1
+      },
+      "storage limit (tonne)": {
+        "P1": 100,
+        "P2": null
+      },
+      "disposal cost ($/tonne)": {
+        "P3": 0,
+        "P4": 0.86,
+        "P5": 0.25,
+      },
+      "disposal limit (tonne)": {
+        "P3": null,
+        "P4": 1000.0,
+        "P5": 1000.0
+      },
+      "capacities": [
+        {
+          "size": 100,
+          "opening cost ($)": 500,
+          "fixed operating cost ($)": 300,
+          "variable operating cost ($/tonne)": 5.0
+        },
+        {
+          "size": 500,
+          "opening cost ($)": 1000.0,
+          "fixed operating cost ($)": 400.0,
+          "variable operating cost ($/tonne)": 5.0.
+        }
+      ],
+      "initial capacity (tonne)": 0,
+    }
+  }
+}
+```
+
+## Emissions
+
+| Key                 | Description                                                                                                                            |
+| :------------------ | :------------------------------------------------------------------------------------------------------------------------------------- |
+| `limit (tonne)`     | Maximum amount of this greenhouse gas allowed to be emitted per year across the entire supply chain. Entry may be `null` if unlimited. |
+| `penalty ($/tonne)` | Penalty cost per tonne of this greenhouse gas emitted.                                                                                 |
+
+#### Example
+
+```json
+{
+  "emissions": {
+    "CO2": {
+      "limit (tonne)": 1000.0,
+      "penalty ($/tonne)": 50.0
+    },
+    "CH4": {
+      "limit (tonne)": null,
+      "penalty ($/tonne)": 1200.0
+    },
+    "N2O": {
+      "limit (tonne)": 10.0,
+      "penalty ($/tonne)": 15000.0
+    }
+  }
+}
+```

docs/src/index.md

@@ -1,31 +1,42 @@
-# RELOG: Reverse Logistics Optimization
+# RELOG -- Supply Chain Analysis and Optimization
 
+**RELOG** is an open-source package designed to optimize supply chains for
+forward, reverse and circular manufacturing. Using mixed-integer linear
+optimization, RELOG helps users determine strategic decisions such as:
 
-**RELOG** is an open-source supply chain optimization package focusing on reverse logistics and reverse manufacturing. The package uses Mixed-Integer Linear Programming to determine where to build recycling plants, what size should these plants have and which customers should be served by which plants. The package supports custom reverse logistics pipelines, with multiple types of plants, multiple types of product and multiple time periods.
+- Where and when to build manufacturing and recycling plants
+- The size of these plants, when to expand them, and by how much
+- The sources for each plant's input materials and the destinations for their
+  processed outputs
+- Whether to process input materials immediately or store them for later use
 
-<img src="images/ex_transportation.png" width="1000px"/>
+RELOG has been successfully applied in research at various laboratories and
+universities, focusing on areas like critical material recovery from spent NiMH
+and Li-Ion batteries, biomass processing for hydrogen production, and the
+recycling of electronics, plastics and solar PV materials, among others. See
+references for more details.
 
+## Screenshots
+```@raw html
+<center>
+   <img src="assets/relog.png" width="1000px"/>
+</center>
+```
 
-### Table of Contents
+## Authors
 
-  * [Usage](usage.md)
+- **Alinson S. Xavier,** Argonne National Laboratory <axavier@anl.gov>
-  * [Input and Output Data Formats](format.md)
+- **Nwike Iloeje,** Argonne National Laboratory <ciloeje@anl.gov>
-  * [Simplified Solution Reports](reports.md)
+- **Kavitha G. Menon,** Argonne National Laboratory
-  * [Optimization Model](model.md)
+- **John Atkins,** Argonne National Laboratory
+- **Kyle Sun,** Argonne National Laboratory
+- **Audrey Gallier,** Argonne National Laboratory
 
-### Source Code
+## License
-
-  * [https://github.com/ANL-CEEESA/RELOG](https://github.com/ANL-CEEESA/RELOG)
-
-### Authors
-* **Alinson S. Xavier,** Argonne National Laboratory <<axavier@anl.gov>>
-* **Nwike Iloeje,** Argonne National Laboratory <<ciloeje@anl.gov>>
-
-### License
 
 ```text
 RELOG: Reverse Logistics Optimization
-Copyright © 2020, UChicago Argonne, LLC. All Rights Reserved.
+Copyright © 2020-2025, UChicago Argonne, LLC. All Rights Reserved.
 
 Redistribution and use in source and binary forms, with or without modification, are permitted
 provided that the following conditions are met:

docs/src/problem.md

@@ -0,0 +1,415 @@
+# Mathematical problem definition
+
+## Overview and assumptions
+
+The mathematical model employed by RELOG is based on three main components:
+
+1. **Products and Materials:** Inputs and outputs for both manufacturing and
+   recycling plants. This includes raw materials, whether virgin or recovered,
+   and final products, whether new or at their end-of-life. Each product has
+   associated transportation parameters, such as costs, energy and emissions.
+
+2. **Manufacturing and Recycling Plants:** Facilities that take in specific
+   materials and produce certain products. The outputs can be sent to another
+   plant for further processing, to a collection & distribution center for
+   customer sale, or simply disposed of at landfill. Plants have associated
+   costs (capital, fixed and operating), as well as various limits (processing
+   capacity, storage and disposal limits).
+
+3. **Collection and Distribution Centers:** Facilities that receive final
+   products from the plants, sell them to customers, and then collect them back
+   once they reach their end-of-life. Collected products can either be sent to a
+   plant for recycling or disposed of at a local landfill. Centers have
+   associated revenue and various costs, such as operating cost, collection cost
+   and disposal cost. The amount of material collected by a center can either be
+   a fixed rate per year, or depend on the amount of product sold at the center
+   in previous years.
+
+!!! note
+
+    - We assume that transportation costs, energy and emissions scale linearly with transportation distance and amount being transported. Distances between locations are calculated using either approximated driving distances (continental U.S. only) or straight-line distances.
+    - Once a plant is opened, we assume that it remains open until the end of the planning horizon. Similarly, once a plant is expanded, its size cannot be reduced at a later time.
+    - In addition to serving as a source of end-of-life products, centers can also serve as a source for virgin materials. In this case, the center does not receive any inputs from manufacturing or recycling plants, and it generates the desired material at a fixed rate. Collection cost, in this case, refers to the cost to produce the virgin material.
+    - We assume that centers accept either no input product, or a single input product.
+
+## Sets
+
+| Symbol   | Description                                                                                                                                         |
+| :------- | :-------------------------------------------------------------------------------------------------------------------------------------------------- |
+| $C$      | Set of collection and distribution centers                                                                                                          |
+| $P$      | Set of manufacturing and recycling plants                                                                                                           |
+| $M$      | Set of products and materials                                                                                                                       |
+| $G$      | Set of greenhouse gases                                                                                                                             |
+| $M^+_u$  | Set of output products of plant/center $u$.                                                                                                         |
+| $M^-_u$  | Set of input products of plant/center $u$.                                                                                                          |
+| $T$      | Set of time periods in the planning horizon. We assume $T=\{1,\ldots,t^{max}\}.$                                                                    |
+| $E$      | Set of transportation edges. Specifically, $(u,v,m) \in E$ if $m$ is an output of $u$ and an input of $v$, where $m \in M$ and $u, v \in P \cup C$. |
+| $E^-(v)$ | Set of incoming edges for plant/center v. Specifically, edges $(u,m)$ such that $(u,v,m) \in E$.                                                    |
+| $E^+(u)$ | Set of outgoing edges for plant/center u. Specifically, edges $(v,m)$ such that $(u,v,m) \in E$.                                                    |
+
+## Constants
+
+| Symbol                        | Description                                                                                                                                                                                                      | Unit           |
+| :---------------------------- | :--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | :------------- |
+| $K^{\text{dist}}_{uv}$        | Distance between plants/centers $u$ and $v$                                                                                                                                                                      | km             |
+| $K^\text{cap-init}_p$         | Initial capacity of plant $p$                                                                                                                                                                                    | tonne          |
+| $K^\text{cap-max}_p$          | Maximum capacity of plant $p$                                                                                                                                                                                    | tonne          |
+| $K^\text{cap-min}_p$          | Minimum capacity of plant $p$                                                                                                                                                                                    | tonne          |
+| $K^\text{disp-limit}_{mt}$    | Maximum amount of material $m$ that can be disposed of (globally) at time $t$                                                                                                                                    | tonne          |
+| $K^\text{disp-limit}_{mut}$   | Maximum amount of material $m$ that can be disposed of at plant/center $u$ at time $t$                                                                                                                           | tonne          |
+| $K^\text{em-limit}_{gt}$      | Maximum amount of greenhouse gas $g$ allowed to be emitted (globally) at time $t$                                                                                                                                | tonne          |
+| $K^\text{em-plant}_{gpt}$     | Amount of greenhouse gas $g$ released by plant $p$ at time $t$ for each tonne of input material processed                                                                                                        | tonne/tonne    |
+| $K^\text{em-tr}_{gmt}$        | Amount of greenhouse gas $g$ released by transporting 1 tonne of material $m$ over one km at time $t$                                                                                                            | tonne/km-tonne |
+| $K^\text{mix}_{pmt}$          | If plant $p$ receives one tonne of input material at time $t$, then $K^\text{mix}_{pmt}$ is the amount of product $m$ in this mix. Must be between zero and one, and the sum of these amounts must equal to one. | tonne          |
+| $K^\text{out-fix}_{cmt}$      | Fixed amount of material $m$ collected at center $c$ at time $t$                                                                                                                                                 | tonne          |
+| $K^\text{out-var-len}_{cm}$   | Length of the $K^\text{out-var}_{c,m,*}$ vector.                                                                                                                                                                 | --             |
+| $K^\text{out-var}_{cmi}$      | Factor used to calculate variable amount of material $m$ collected at center $c$. See `eq_z_collected` for more details.                                                                                         | --             |
+| $K^\text{output}_{pmt}$       | Amount of material $m$ produced by plant $p$ at time $t$ for each tonne of input material processed                                                                                                              | tonne          |
+| $K^\text{storage-limit}_{pm}$ | Maximum amount of material $m$ that can be stored at plant $p$ at any time                                                                                                                                       | tonne          |
+| $R^\text{collect}_{cmt}$      | Cost of collecting material $m$ at center $c$ at time $t$                                                                                                                                                        | \$/tonne       |
+| $R^\text{disp}_{umt}$         | Cost to dispose of material at plant/center $u$ at time $t$                                                                                                                                                      | \$/tonne       |
+| $R^\text{em}_{gt}$            | Penalty cost per tonne of greenhouse gas $g$ emitted at time $t$                                                                                                                                                 | \$/tonne       |
+| $R^\text{expand}_{pt}$        | Cost to increase capacity of plant $p$ at time $t$                                                                                                                                                               | \$/tonne       |
+| $R^\text{fix-exp}_{pt}$       | Increase in fixed operational cost for plant $p$ at time $t$ for every additional tonne of capacity                                                                                                              | \$/tonne       |
+| $R^\text{fix-min}_{pt}$       | Fixed operating cost for plant $p$ at time $t$ at minimum capacity                                                                                                                                               | \$             |
+| $R^\text{fix}_{ct}$           | Fixed operating cost for center $c$ at time $t$                                                                                                                                                                  | \$             |
+| $R^\text{open}_{pt}$          | Cost to open plant $p$ at time $t$, at minimum capacity                                                                                                                                                          | \$             |
+| $R^\text{rev}_{ct}$           | Revenue for selling the input product of center $c$ at this center at time $t$                                                                                                                                   | \$/tonne       |
+| $R^\text{storage}_{pmt}$      | Cost to store one tonne of material $m$ at plant $p$ at time $t$ for one year                                                                                                                                    | \$/tonne       |
+| $R^\text{tr}_{mt}$            | Cost to send material $m$ at time $t$                                                                                                                                                                            | \$/km-tonne    |
+| $R^\text{var}_{pt}$           | Cost to process one tonne of input material at plant $p$ at time $t$                                                                                                                                             | \$/tonne       |
+
+## Decision variables
+
+| Symbol                       | JuMP name                                    | Description                                                                                             | Unit   |
+| :--------------------------- | :------------------------------------------- | :------------------------------------------------------------------------------------------------------ | :----- |
+| $x_{pt}$                     | `x[p.name, t]`                               | One if plant $p$ is operational at time $t$                                                             | binary |
+| $y_{uvmt}$                   | `y[u.name, v.name, m.name, t]`               | Amount of product $m$ sent from plant/center $u$ to plant/center $v$ at time $t$                        | tonne  |
+| $z^{\text{exp}}_{pt}$        | `z_exp[p.name, t]`                           | Extra capacity installed at plant $p$ at time $t$ above the minimum capacity                            | tonne  |
+| $z^{\text{collected}}_{cmt}$ | `z_collected[c.name, m.name, t]`             | Amount of material $m$ collected by center $c$ at time $t$                                              | tonne  |
+| $z^{\text{disp}}_{umt}$      | `z_disp[u.name, m.name, t]`                  | Amount of product $m$ disposed of at plant/center $u$ at time $t$                                       | tonne  |
+| $z^{\text{em-plant}}_{gpt}$  | `z_em_plant[g.name, p.name, t]`              | Amount of greenhouse gas $g$ released by plant $p$ at time $t$                                          | tonne  |
+| $z^{\text{em-tr}}_{guvmt}$   | `z_em_tr[g.name, u.name, v.name, m.name, t]` | Amount of greenhouse gas $g$ released at time $t$ due to transportation of material $m$ from $u$ to $v$ | tonne  |
+| $z^{\text{input}}_{ut}$      | `z_input[u.name, t]`                         | Total amount received by plant/center $u$ at time $t$                                                   | tonne  |
+| $z^{\text{prod}}_{umt}$      | `z_prod[u.name, m.name, t]`                  | Amount of product $m$ produced by plant/center $u$ at time $t$                                          | tonne  |
+| $z^{\text{storage}}_{pmt}$   | `z_storage[p.name, m.name, t]`               | Amount of input material $m$ stored at plant $p$ at the end of time $t$                                 | tonne  |
+| $z^{\text{process}}_{pt}$    | `z_process[p.name, t]`                       | Total amount of input material processed by plant $p$ at time $t$                                       | tonne  |
+
+## Objective function
+
+The goal is to minimize a linear objective function with the following terms:
+
+- Transportation costs, which depend on transportation distance
+  $K^{\text{dist}}_{uv}$ and product-specific factor $R^\text{tr}_{mt}$:
+
+```math
+\sum_{(u, v, m) \in E} \sum_{t \in T} K^{\text{dist}}_{uv} R^\text{tr}_{mt} y_{uvmt}
+```
+
+- Center revenue, obtained by selling products received from manufacturing and
+  recycling plants:
+
+```math
+- \sum_{c \in C} \sum_{(p,m) \in E^-(c)} \sum_{t \in T} R^\text{rev}_{ct} y_{pcmt}
+```
+
+- Center collection cost, incurred for each tonne of output material sent to a
+  plant:
+
+```math
+\sum_{c \in C} \sum_{(p,m) \in E^+(c)} \sum_{t \in T} R^\text{collect}_{cmt} y_{cpmt}
+```
+
+- Center disposal cost, incurred when disposing of output material, instead of
+  sending it to a plant:
+
+```math
+\sum_{c \in C} \sum_{m \in M^+_c} \sum_{t \in T} R^\text{disp}_{cmt} z^\text{disp}_{cmt}
+```
+
+- Center fixed operating cost, incurred for every time period, regardless of
+  input or output amounts:
+
+```math
+\sum_{c \in C} \sum_{t \in T} R^\text{fix}_{ct}
+```
+
+- Plant disposal cost, incurred for each tonne of product discarded at the
+  plant:
+
+```math
+\sum_{p \in P} \sum_{m \in M^+_p} \sum_{t \in T} R^\text{disp}_{pmt} z^\text{disp}_{pmt}
+```
+
+- Plant opening cost, incurred when the plant goes from non-operational at time
+  $t-1$ to operational at time $t$. Never incurred if the plant is initially
+  open:
+
+```math
+\sum_{p \in P} \sum_{t \in T} R^\text{open}_{pt} \left(
+  x_{pt} - x_{p,t-1}
+\right)
+```
+
+- Plant fixed operating cost, incurred for every time period, regardless of
+  input or output amounts, as long as the plant is operational. Depends on the
+  size of the plant:
+
+```math
+\sum_{p \in P} \sum_{t \in T} \left(
+    R^\text{fix-min}_{pt} x_{pt} +
+    R^\text{fix-exp}_{pt} z^\text{exp}_{pt}
+\right)
+```
+
+- Plant expansion cost, incurred whenever plant capacity increases:
+
+```math
+\sum_{p \in P} \sum_{t \in T} R^\text{expand}_{pt} \left(z^\text{exp}_{pt} - z^\text{exp}_{p,t-1} \right)
+```
+
+- Plant variable operating cost, incurred for each tonne of input material
+  received by the plant:
+
+```math
+\sum_{p \in P} \sum_{(u,m) \in E^-(p)} \sum_{t \in T} R^\text{var}_{pt} y_{upmt}
+```
+
+- Plant storage cost, incurred for each tonne of material stored at the plant:
+
+```math
+\sum_{p \in P} \sum_{m \in M^-_p} \sum_{t \in T} R^\text{storage}_{pmt} z^{\text{storage}}_{pmt}
+```
+
+- Emissions penalty cost, incurred for each tonne of greenhouse gas emitted:
+
+```math
+\sum_{g \in G} \sum_{t \in T} R^\text{em}_{gt} \left(
+  \sum_{p \in P} z^{\text{em-plant}}_{gpt} + \sum_{(u,v,m) \in E} z^{\text{em-tr}}_{guvmt}
+\right)
+```
+
+## Constraints
+
+- Definition of plant input (`eq_z_input[p.name, t]`):
+
+```math
+\begin{align*}
+& z^{\text{input}}_{pt} = \sum_{(u,m) \in E^-(p)} y_{upmt}
+& \forall p \in P, t \in T
+\end{align*}
+```
+
+- Definition of plant processing (`eq_z_process[p.name, t]`):
+
+```math
+\begin{align*}
+& z^{\text{process}}_{pt} = z^{\text{input}}_{pt} + \sum_{m \in M^-_p} \left(z^{\text{storage}}_{p,m,t-1} - z^{\text{storage}}_{pmt}\right)
+& \forall p \in P, t \in T
+\end{align*}
+```
+
+- Plant processing mix must have correct proportion
+  (`eq_process_mix[p.name, m.name, t]`):
+
+```math
+\begin{align*}
+& \sum_{u : (u,m) \in E^-(p)} y_{upmt} + z^{\text{storage}}_{p,m,t-1} - z^{\text{storage}}_{pmt}
+= K^\text{mix}_{pmt} z^{\text{process}}_{pt}
+& \forall p \in P, m \in M^-_p, t \in T
+\end{align*}
+```
+
+- Definition of amount produced by a plant (`eq_z_prod[p.name, m.name, t]`):
+
+```math
+\begin{align*}
+& z^\text{prod}_{pmt} = K^\text{output}_{pmt} z^{\text{process}}_{pt}
+& \forall p \in P, m \in M^+_p, t \in T
+\end{align*}
+```
+
+- Material produced by a plant must be sent somewhere or disposed of
+  (`eq_balance[p.name, m.name, t]`):
+
+```math
+\begin{align*}
+& z^\text{prod}_{pmt} = \sum_{v : (v,m) \in E^+(p)} y_{pvmt} + z^\text{disp}_{pmt}
+& \forall p \in P, m \in M^+_p, t \in T
+\end{align*}
+```
+
+- Plant can only be expanded if the plant is open, and up to a certain amount
+  (`eq_exp_ub[p.name, t]`):
+
+```math
+\begin{align*}
+& z^\text{exp}_{pt} \leq \left(K^\text{cap-max}_p - K^\text{cap-min}_p) x_{pt}
+& \forall p \in P, t \in T
+\end{align*}
+```
+
+- Plant capacity cannot decrease over time (`eq_capacity_nondecreasing[p.name, t]`):
+
+```math
+\begin{align*}
+& z^\text{exp}_{pt} \geq z^\text{exp}_{p,t-1}
+& \forall p \in P, t \in T
+\end{align*}
+```
+
+- Plant is initially open if initial capacity is positive:
+
+```math
+\begin{align*}
+& x_{p,0} = \begin{cases}
+    0 & \text{ if } K^\text{cap-init}_p = 0 \\
+    1 & \text{otherwise}
+\end{cases}
+& \forall p \in P
+\end{align*}
+```
+
+- Calculation of initial plant expansion:
+
+```math
+\begin{align*}
+& z^\text{exp}_{p,0} = K^\text{cap-init}_p - K^\text{cap-min}_p
+& \forall p \in P
+\end{align*}
+```
+
+- Plants cannot process more than their current capacity
+  (`eq_process_limit[p.name,t]`)
+
+```math
+\begin{align*}
+& z^\text{process}_{pt} \leq K^\text{cap-min}_p x_{pt} + z^\text{exp}_{pt}
+& \forall p \in P, t \in T
+\end{align*}
+```
+
+- Storage limit at the plants (`eq_storage_limit[p.name, m.name, t]`):
+
+```math
+\begin{align*}
+& z^{\text{storage}}_{pmt} \leq K^\text{storage-limit}_{pm}
+& \forall p \in P, m \in M^-_p, t \in T
+\end{align*}
+```
+
+- Disposal limit at the plants (`eq_disposal_limit[p.name, m.name, t]`):
+
+```math
+\begin{align*}
+& z^\text{disp}_{pmt} \leq K^\text{disp-limit}_{pmt}
+& \forall p \in P, m \in M^+_p, t \in T
+\end{align*}
+```
+
+- Once a plant is built, it must remain open until the end of the planning
+  horizon (`eq_keep_open[p.name, t]`):
+
+```math
+\begin{align*}
+& x_{pt} \geq x_{p,t-1}
+& \forall p \in P, t \in T
+\end{align*}
+```
+
+- Definition of center input (`eq_z_input[c.name, t]`):
+
+```math
+\begin{align*}
+& z^\text{input}_{ct} = \sum_{u : (u,m) \in E^-(c)} y_{ucmt}
+& \forall c \in C, t \in T
+\end{align*}
+```
+
+- Calculation of amount collected by the center
+  (`eq_z_collected[c.name, m.name, t]`). In the equation below,
+  $K^\text{out-var-len}$ is the length of the $K^\text{out-var}_{c,m,*}$ vector.
+
+```math
+\begin{align*}
+& z^\text{collected}_{cmt}
+  = \sum_{i=0}^{\min\{K^\text{out-var-len}_{cm}-1,t-1\}} K^\text{out-var}_{c,m,i+1} z^\text{input}_{c,t-i}
+  + K^\text{out-fix}_{cmt}
+& \forall c \in C, m \in M^+_c, t \in T
+\end{align*}
+```
+
+- Products collected at centers must be sent somewhere or disposed of
+  (`eq_balance[c.name, m.name, t]`):
+
+```math
+\begin{align*}
+& z^\text{collected}_{cmt} = \sum_{v : (v,m) \in E^+(c)} y_{cvmt} + z^\text{disp}_{cmt}
+& \forall c \in C, m \in M^+_c, t \in T
+\end{align*}
+```
+
+- Disposal limit at the centers (`eq_disposal_limit[c.name, m.name, t]`):
+
+```math
+\begin{align*}
+& z^\text{disp}_{cmt} \leq K^\text{disp-limit}_{cmt}
+& \forall c \in C, m \in M^+_c, t \in T
+\end{align*}
+```
+
+- Global disposal limit (`eq_disposal_limit[m.name, t]`)
+
+```math
+\begin{align*}
+& \sum_{p \in P} z^\text{disp}_{pmt} + \sum_{c \in C} z^\text{disp}_{cmt} \leq K^\text{disp-limit}_{mt}
+& \forall m \in M, t \in T
+\end{align*}
+```
+
+- Computation of transportation emissions
+  (`eq_emission_tr[g.name, u.name, v.name, m.name, t]`):
+
+```math
+\begin{align*}
+& z^{\text{em-tr}}_{guvmt} = K^{\text{dist}}_{uv} K^\text{em-tr}_{gmt} y_{uvmt}
+& \forall g \in G, (u, v, m) \in E, t \in T
+\end{align*}
+```
+
+- Computation of plant emissions (`eq_emission_plant[g.name, p.name, t]`):
+
+```math
+\begin{align*}
+& z^{\text{em-plant}}_{gpt} = K^\text{em-plant}_{gpt} z^{\text{process}}_{pt}
+& \forall g \in G, p \in P, t \in T
+\end{align*}
+```
+
+- Global emissions limit (`eq_emission_limit[g.name, t]`):
+
+```math
+\begin{align*}
+& \sum_{p \in P} z^{\text{em-plant}}_{gpt} + \sum_{(u,v,m) \in E} z^{\text{em-tr}}_{guvmt} \leq K^\text{em-limit}_{gt}
+& \forall g \in G, t \in T
+\end{align*}
+```
+
+- All stored materials must be processed by the end of the time horizon
+  (`eq_storage_final[p.name, m.name]`):
+
+```math
+\begin{align*}
+& z^{\text{storage}}_{p,m,t^{max}} = 0
+& \forall p \in P, m \in M^-_p
+\end{align*}
+```
+
+- Initial storage is zero (`eq_storage_initial[p.name, m.name]`):
+
+```math
+\begin{align*}
+& z^{\text{storage}}_{p,m,0} = 0
+& \forall p \in P, m \in M^-_p
+\end{align*}
+```

docs/src/reports.md

@@ -1,4 +1,4 @@
-# Simplified Solution Reports
+# Solution reports
 
 In addition to the full output format described in [data formats](format.md), RELOG can also generate a number of simplified reports in tabular data format (CSV), which can be more easily processed by spreadsheet software (such as Microsoft Excel), by data analysis libraries (such as Pandas) or by relational databases (such as SQLite).
 
@@ -6,15 +6,13 @@ In this page, we also illustrate what types of charts and visualizations can be
 
 ## Plants report
 
-Report showing plant costs, capacities, energy expenditure and utilization factors.
+Report showing plant costs, capacities, energy expenditure and utilization factors. Generated by `RELOG.write_plants_report(solution, filename)`.
-
-Generated by `RELOG.write_plants_report(solution, filename)`. For a concrete example, see [nimh_plants.csv](https://github.com/ANL-CEEESA/RELOG/blob/master/test/fixtures/nimh_plants.csv).
 
 | Column                                | Description
-|:--------------------------------------|---------------|
+|:--------------------------------------|:---------------|
 | `plant type` | Plant type.
 | `location name` | Location name.
-| `year` | What year this row corresponds to. This reports includes one row for each year in the simulation.
+| `year` | What year this row corresponds to. This reports includes one row for each year.
 | `latitude (deg)` | Latitude of the plant.
 | `longitude (deg)` | Longitude of the plant.
 | `capacity (tonne)`  | Capacity of the plant at this point in time.
@@ -47,7 +45,9 @@ sns.barplot(x="year",
                      .reset_index());
 ```
 
-<img src="../images/ex_plant_cost_per_year.png" width="500px"/>
+```@raw html
+<img src="../assets/ex_plant_cost_per_year.png" width="500px"/>
+```
 
 * Map showing plant locations (in Python):
 ```python
@@ -67,21 +67,20 @@ points = gp.points_from_xy(data["longitude (deg)"],
 gp.GeoDataFrame(data, geometry=points).plot(ax=ax);
 ```
 
-<img src="../images/ex_plant_locations.png" width="1000px"/>
+```@raw html
-
+<img src="../assets/ex_plant_locations.png" width="1000px"/>
+```
 
 ## Plant outputs report
 
-Report showing amount of products produced, sent and disposed of by each plant, as well as disposal costs.
+Report showing amount of products produced, sent and disposed of by each plant, as well as disposal costs. Generated by `RELOG.write_plant_outputs_report(solution, filename)`.
-
-Generated by `RELOG.write_plant_outputs_report(solution, filename)`. For a concrete example, see [nimh_plant_outputs.csv](https://github.com/ANL-CEEESA/RELOG/blob/master/test/fixtures/nimh_plant_outputs.csv).
 
 
 | Column                                | Description
-|:--------------------------------------|---------------|
+|:--------------------------------------|:---------------|
 | `plant type`  | Plant type.
 | `location name`  | Location name.
-| `year`  | What year this row corresponds to. This reports includes one row for each year in the simulation.
+| `year`  | What year this row corresponds to. This reports includes one row for each year.
 | `product name`  | Product being produced.
 | `amount produced (tonne)` | Amount of product produced this year.
 | `amount sent (tonne)` | Amount of product produced by this plant and sent to another plant for further processing this year.
@@ -105,17 +104,17 @@ sns.barplot(x="amount produced (tonne)",
                      .reset_index());
 ```
 
-<img src="../images/ex_amount_produced.png" width="500px"/>
+```@raw html
+<img src="../assets/ex_amount_produced.png" width="500px"/>
+```
 
 
 ## Plant emissions report
 
-Report showing amount of emissions produced by each plant.
+Report showing amount of emissions produced by each plant. Generated by `RELOG.write_plant_emissions_report(solution, filename)`.
-
-Generated by `RELOG.write_plant_emissions_report(solution, filename)`. For a concrete example, see [nimh_plant_emissions.csv](https://github.com/ANL-CEEESA/RELOG/blob/master/test/fixtures/nimh_plant_emissions.csv).
 
 | Column                                | Description
-|:--------------------------------------|---------------|
+|:--------------------------------------|:---------------|
 | `plant type` | Plant type.
 | `location name` | Location name.
 | `year` | Year.
@@ -139,17 +138,33 @@ sns.barplot(x="plant type",
                      .reset_index());
 ```
 
-<img src="../images/ex_emissions.png" width="500px"/>
+```@raw html
+<img src="../assets/ex_emissions.png" width="500px"/>
+```
+
+## Products report
+
+Report showing primary product amounts, locations and marginal costs. Generated by `RELOG.write_products_report(solution, filename)`.
+
+| Column                                | Description
+|:--------------------------------------|:---------------|
+| `product name`  | Product name.
+| `location name`  | Name of the collection center.
+| `latitude (deg)` | Latitude of the collection center.
+| `longitude (deg)` | Longitude of the collection center.
+| `year`  | What year this row corresponds to. This reports includes one row for each year.
+| `amount (tonne)` | Amount of product available at this collection center.
+| `amount disposed (tonne)` | Amount of product disposed of at this collection center.
+| `marginal cost ($/tonne)` | Cost to process one additional tonne of this product coming from this collection center.
+
 
 ## Transportation report
 
-Report showing amount of product sent from initial locations to plants, and from one plant to another. Includes the distance between each pair of locations, amount-distance shipped, transportation costs and energy expenditure.
+Report showing amount of product sent from initial locations to plants, and from one plant to another. Includes the distance between each pair of locations, amount-distance shipped, transportation costs and energy expenditure. Generated by `RELOG.write_transportation_report(solution, filename)`.
-
-Generated by `RELOG.write_transportation_report(solution, filename)`. For a concrete example, see [nimh_transportation.csv](https://github.com/ANL-CEEESA/RELOG/blob/master/test/fixtures/nimh_transportation.csv).
 
 
 | Column                                | Description
-|:--------------------------------------|---------------|
+|:--------------------------------------|:---------------|
 | `source type` | If product is being shipped from an initial location, equals `Origin`. If product is being shipped from a plant, equals plant type.
 | `source location name` | Name of the location where the product is being shipped from.
 | `source latitude (deg)` | Latitude of the source location.
@@ -183,7 +198,9 @@ sns.barplot(x="product",
                      .reset_index());
 ```
 
-<img src="../images/ex_transportation_amount_distance.png" width="500px"/>
+```@raw html
+<img src="../assets/ex_transportation_amount_distance.png" width="500px"/>
+```
 
 * Map of transportation lines (in Python):
 
@@ -226,17 +243,17 @@ gp.GeoDataFrame(data, geometry=points).plot(ax=ax,
                                             markersize=50);
 ```
 
-<img src="../images/ex_transportation.png" width="1000px"/>
+```@raw html
+<img src="../assets/ex_transportation.png" width="1000px"/>
+```
 
 
 ## Transportation emissions report
 
-Report showing emissions for each trip between initial locations and plants, and between pairs of plants.
+Report showing emissions for each trip between initial locations and plants, and between pairs of plants. Generated by `RELOG.write_transportation_emissions_report(solution, filename)`.
-
-Generated by `RELOG.write_transportation_emissions_report(solution, filename)`. For a concrete example, see [nimh_transportation_emissions.csv](https://github.com/ANL-CEEESA/RELOG/blob/master/test/fixtures/nimh_transportation_emissions.csv).
 
 | Column                                | Description
-|:--------------------------------------|---------------|
+|:--------------------------------------|:---------------|
 | `source type` | If product is being shipped from an initial location, equals `Origin`. If product is being shipped from a plant, equals plant type.
 | `source location name` | Name of the location where the product is being shipped from.
 | `source latitude (deg)` | Latitude of the source location.
@@ -270,4 +287,6 @@ sns.barplot(x="emission type",
                      .reset_index());
 ```
 
-<img src="../images/ex_transportation_emissions.png" width="500px"/>
+```@raw html
+<img src="../assets/ex_transportation_emissions.png" width="500px"/>
+```

docs/src/usage.md

@@ -1,24 +1,12 @@
-Usage
+# Usage
-=====
 
 ## 1. Installation
 
-To use RELOG, the first step is to install the [Julia programming language](https://julialang.org/) on your machine. Note that RELOG was developed and tested with Julia 1.5 and may not be compatible with newer versions. After Julia is installed, launch the Julia console, type `]` to switch to package manger mode, then run:
+To use RELOG, the first step is to install the [Julia programming language](https://julialang.org/) on your machine. Note that RELOG was developed and tested with Julia 1.8 and may not be compatible with newer versions. After Julia is installed, launch the Julia console, then run:
 
-```text
+```julia
-(@v1.5) pkg> add https://github.com/ANL-CEEESA/RELOG.git
+using Pkg
-```
+Pkg.add(name="RELOG", version="0.7")
-
-After the package and all its dependencies have been installed, please run the RELOG test suite, as shown below, to make sure that the package has been correctly installed:
-
-```text
-(@v1.5) pkg> test RELOG
-```
-
-To update the package to a newer version, type `]` to enter the package manager mode, then run:
-
-```text
-(@v1.5) pkg> update RELOG
 ```
 
 ## 2. Modeling the problem
@@ -27,21 +15,21 @@ The two main model components in RELOG are **products** and **plants**.
 
 A **product** is any material that needs to be recycled, any intermediary product produced during the recycling process, or any product recovered at the end of the process. For example, in a NiMH battery recycling study case, products could include (i) the original batteries to be recycled; (ii) the cathode and anode parts of the battery; (iii) rare-earth elements and (iv) scrap metals.
 
-* The model assumes that some products are initially available at user-specified locations (described by their latitude, longitude and the amount available), while other products only become available during the recycling process.
+- The model assumes that some products are initially available at user-specified locations (described by their latitude, longitude and the amount available), while other products only become available during the recycling process.
 
-* Products that are initially available must be sent to a plant for processing during the same time period they became available.
+- Products that are initially available must be sent to a plant for processing during the same time period they became available.
 
-* Transporting products from one location to another incurs a transportation cost (`$/km/tonne`), spends some amount of energy (`J/km/tonne`) and may generate multiple types of emissions (`tonne/tonne`). All these parameters are user-specified and may be product- and time-specific.
+- Transporting products from one location to another incurs a transportation cost (`$/km/tonne`), spends some amount of energy (`J/km/tonne`) and may generate multiple types of emissions (`tonne/tonne`). All these parameters are user-specified and may be product- and time-specific.
 
-A **plant** is a facility that converts one type of product to another. RELOG assumes that each plant receives a single type of product as input and converts this input into multiple types of products. Multiple types of plants, with different inputs, outputs and performance characteristics, may be specified. In the NiMH battery recycling study case, for example, one type of plant could be a *disassembly plant*, which converts *batteries* into *cathode* and *anode*. Another type of plant could be *anode recycling plant*, which converts *anode* into *rare-earth elements* and *scrap metals*.
+A **plant** is a facility that converts one type of product to another. RELOG assumes that each plant receives a single type of product as input and converts this input into multiple types of products. Multiple types of plants, with different inputs, outputs and performance characteristics, may be specified. In the NiMH battery recycling study case, for example, one type of plant could be a _disassembly plant_, which converts _batteries_ into _cathode_ and _anode_. Another type of plant could be _anode recycling plant_, which converts _anode_ into _rare-earth elements_ and _scrap metals_.
 
-* To process each tonne of input material, plants incur a variable operating cost (`$/tonne`), spend some amount of energy (`GJ/tonne`), and produce multiple types of emissions (`tonne/tonne`). Plants also incur a fixed operating cost (`$`) regardless of the amount of material they process. All these parameters are user-specified and may be region- and time-specific.
+- To process each tonne of input material, plants incur a variable operating cost (`$/tonne`), spend some amount of energy (`GJ/tonne`), and produce multiple types of emissions (`tonne/tonne`). Plants also incur a fixed operating cost (`$`) regardless of the amount of material they process. All these parameters are user-specified and may be region- and time-specific.
 
-* Plants can be built at user-specified potential locations. Opening a plant incurs a one-time opening cost (`$`) which may be region- and time-specific. Plants also have a limited capacity (in `tonne`), which indicates the maximum amount of input material they are able to process per year. When specifying potential locations for each type of plant, it is also possible to specify the minimum and maximum capacity of the plants that can be built at that particular location. Different plants sizes may have different opening costs and fixed operating costs. After a plant is built, it can be further expanded in the following years, up to its maximum capacity.
+- Plants can be built at user-specified potential locations. Opening a plant incurs a one-time opening cost (`$`) which may be region- and time-specific. Plants also have a limited capacity (in `tonne`), which indicates the maximum amount of input material they are able to process per year. When specifying potential locations for each type of plant, it is also possible to specify the minimum and maximum capacity of the plants that can be built at that particular location. Different plants sizes may have different opening costs and fixed operating costs. After a plant is built, it can be further expanded in the following years, up to its maximum capacity.
 
-* Products received by a plant can be either processed immediately or stored for later processing. Plants have a maximum storage capacity (`tonne`). Storage costs (`$/tonne`) can also be specified.
+- Products received by a plant can be either processed immediately or stored for later processing. Plants have a maximum storage capacity (`tonne`). Storage costs (`$/tonne`) can also be specified.
 
-* All products generated by a plant can either be sent to another plant for further processing, or disposed of locally for either a profit or a loss (`$/tonne`). To model environmental regulations, it is also possible to specify the maximum amount of each product that can be disposed of at each location.
+- All products generated by a plant can either be sent to another plant for further processing, or disposed of locally for either a profit or a loss (`$/tonne`). To model environmental regulations, it is also possible to specify the maximum amount of each product that can be disposed of at each location.
 
 All user parameters specified above must be provided to RELOG as a JSON file, which is fully described in the [data format page](format.md).
 
@@ -66,25 +54,64 @@ RELOG.write_transportation_report(solution, "transportation.csv")
 
 For a complete description of the file formats above, and for a complete list of available reports, see the [data format page](format.md).
 
-## 4. Advanced options
+## 4. What-If Analysis
 
-### 4.1 Changing the solver
+Fundamentally, RELOG decides when and where to build plants based on a deterministic optimization problem that minimizes costs for a particular input file provided by the user. In practical situations, it may not be possible to perfectly estimate some (or most) entries in this input file in advance, such as costs, demands and emissions. In this situation, it may be interesting to evaluate how well does the facility location plan produced by RELOG work if costs, demands and emissions turn out to be different.
 
-By default, RELOG internally uses [Cbc](https://github.com/coin-or/Cbc), an open-source and freely-available Mixed-Integer Linear Programming solver developed by the [COIN-OR Project](https://www.coin-or.org/). For larger-scale test cases, a commercial solver such as Gurobi, CPLEX or XPRESS is recommended. The following snippet shows how to switch from Cbc to Gurobi, for example:
+To simplify this what-if analysis, RELOG provides the `resolve` method, which updates a previous solution based on a new scenario, but keeps some of the previous decisions fixed. More precisely, given an optimal solution produced by RELOG and a new input file describing the new scenario, the `resolve` method reoptimizes the supply chain and produces a new solution which still builds the same set of plants as before, in exactly the same locations and with the same capacities, but that may now utilize the plants differently, based on the new data. For example, in the new solution, plants that were previously used at full capacity may now be utilized at half-capacity instead. As another example, regions that were previously served by a certain plant may now be served by a different one.
+
+The following snippet shows how to use the method:
+
+```julia
+# Import package
+using RELOG
+
+# Optimize for the average scenario
+solution_avg, model_avg = RELOG.solve("input_avg.json", return_model=true)
+
+# Write reports for the average scenario
+RELOG.write_plants_report(solution_avg, "plants_avg.csv")
+RELOG.write_transportation_report(solution_avg, "transportation_avg.csv")
+
+# Re-optimize for the high-demand scenario, keeping plants fixed
+solution_high = RELOG.resolve(model_avg, "input_high.json")
+
+# Write reports for the high-demand scenario
+RELOG.write_plants_report(solution_high, "plants_high.csv")
+RELOG.write_transportation_report(solution_high, "transportation_high.csv")
+```
+
+To use the `resolve` method, the new input file should be very similar to the original one. Only the following entries are allowed to change:
+
+- **Products:** Transportation costs, energy, emissions and initial amounts (latitude, longitude and amount).
+- **Plants:** Energy and emissions.
+- **Plant's location:** Latitude and longitude.
+- **Plant's storage:** Cost.
+- **Plant's capacity:** Opening cost, fixed operating cost and variable operating cost.
+
+## 5. Advanced options
+
+### 5.1 Changing the solver
+
+By default, RELOG internally uses [HiGHS](https://github.com/ERGO-Code/HiGHS), an open-source and freely-available Mixed-Integer Linear Programming solver. For larger-scale test cases, a commercial solver such as Gurobi, CPLEX or XPRESS is recommended. The following snippet shows how to switch to Gurobi, for example:
 
 ```julia
 using RELOG, Gurobi, JuMP
 
-gurobi = optimizer_with_attributes(Gurobi.Optimizer,
+gurobi = optimizer_with_attributes(
+    Gurobi.Optimizer,
     "TimeLimit" => 3600,
-                                   "MIPGap" => 0.001)
+    "MIPGap" => 0.001,
+)
 
-RELOG.solve("instance.json",
+RELOG.solve(
+    "instance.json",
     output="solution.json",
-            optimizer=gurobi)
+    optimizer=gurobi,
+)
 ```
 
-### 4.2 Multi-period heuristics
+### 5.2 Multi-period heuristics
 
 For large-scale instances, it may be too time-consuming to find an exact optimal solution to the multi-period version of the problem. For these situations, RELOG includes a heuristic solution method, which proceeds as follows:
 
@@ -97,6 +124,8 @@ To solve an instance using this heuristic, use the option `heuristic=true`, as s
 ```julia
 using RELOG
 
-solution = RELOG.solve("/home/user/instance.json",
+solution = RELOG.solve(
-                       heuristic=true)
+    "/home/user/instance.json",
+    heuristic=true,
+)
 ```

instances/s1.json

@@ -1,202 +0,0 @@
-{
-    "parameters": {
-        "time horizon (years)": 2
-    },
-    "products": {
-        "P1": {
-            "transportation cost ($/km/tonne)": [0.015, 0.015],
-            "transportation energy (J/km/tonne)": [0.12, 0.11],
-            "transportation emissions (tonne/km/tonne)": {
-                "CO2": [0.052, 0.050],
-                "CH4": [0.003, 0.002]
-            },            
-            "initial amounts": {
-                "C1": {
-                    "latitude (deg)": 7.0,
-                    "longitude (deg)": 7.0,
-                    "amount (tonne)": [934.56, 934.56]
-                },
-                "C2": {
-                    "latitude (deg)": 7.0,
-                    "longitude (deg)": 19.0,
-                    "amount (tonne)": [198.95, 198.95]
-                },
-                "C3": {
-                    "latitude (deg)": 84.0,
-                    "longitude (deg)": 76.0,
-                    "amount (tonne)": [212.97, 212.97]
-                },
-                "C4": {
-                    "latitude (deg)": 21.0,
-                    "longitude (deg)": 16.0,
-                    "amount (tonne)": [352.19, 352.19]
-                },
-                "C5": {
-                    "latitude (deg)": 32.0,
-                    "longitude (deg)": 92.0,
-                    "amount (tonne)": [510.33, 510.33]
-                },
-                "C6": {
-                    "latitude (deg)": 14.0,
-                    "longitude (deg)": 62.0,
-                    "amount (tonne)": [471.66, 471.66]
-                },
-                "C7": {
-                    "latitude (deg)": 30.0,
-                    "longitude (deg)": 83.0,
-                    "amount (tonne)": [785.21, 785.21]
-                },
-                "C8": {
-                    "latitude (deg)": 35.0,
-                    "longitude (deg)": 40.0,
-                    "amount (tonne)": [706.17, 706.17]
-                },
-                "C9": {
-                    "latitude (deg)": 74.0,
-                    "longitude (deg)": 52.0,
-                    "amount (tonne)": [30.08, 30.08]
-                },
-                "C10": {
-                    "latitude (deg)": 22.0,
-                    "longitude (deg)": 54.0,
-                    "amount (tonne)": [536.52, 536.52]
-                }
-            }
-        },
-        "P2": {
-            "transportation cost ($/km/tonne)": [0.02, 0.02]
-        },
-        "P3": {
-            "transportation cost ($/km/tonne)": [0.0125, 0.0125]
-        },
-        "P4": {
-            "transportation cost ($/km/tonne)": [0.0175, 0.0175]
-        }
-    },
-    "plants": {
-        "F1": {
-            "input": "P1",
-            "outputs (tonne/tonne)": {
-                "P2": 0.2,
-                "P3": 0.5
-            },
-            "energy (GJ/tonne)": [0.12, 0.11],
-            "emissions (tonne/tonne)": {
-                "CO2": [0.052, 0.050],
-                "CH4": [0.003, 0.002]
-            },            
-            "locations": {
-                "L1": {
-                    "latitude (deg)": 0.0,
-                    "longitude (deg)": 0.0,
-                    "disposal": {
-                        "P2": {
-                            "cost ($/tonne)": [-10.0, -10.0],
-                            "limit (tonne)": [1.0, 1.0]
-                        },
-                        "P3": {
-                            "cost ($/tonne)": [-10.0, -10.0],
-                            "limit (tonne)": [1.0, 1.0]
-                        }
-                    },
-                    "capacities (tonne)": {
-                        "250.0": {
-                            "opening cost ($)": [500.0, 500.0],
-                            "fixed operating cost ($)": [30.0, 30.0],
-                            "variable operating cost ($/tonne)": [30.0, 30.0]
-                        },
-                        "1000.0": {
-                            "opening cost ($)": [1250.0, 1250.0],
-                            "fixed operating cost ($)": [30.0, 30.0],
-                            "variable operating cost ($/tonne)": [30.0, 30.0]
-                        }
-                    }
-                },
-                "L2": {
-                    "latitude (deg)": 0.5,
-                    "longitude (deg)": 0.5,
-                    "capacities (tonne)": {
-                        "0.0": {
-                            "opening cost ($)": [1000, 1000],
-                            "fixed operating cost ($)": [50.0, 50.0],
-                            "variable operating cost ($/tonne)": [50.0, 50.0]
-                        },
-                        "10000.0": {
-                            "opening cost ($)": [10000, 10000],
-                            "fixed operating cost ($)": [50.0, 50.0],
-                            "variable operating cost ($/tonne)": [50.0, 50.0]
-                        }
-                    }
-                }               
-            }
-        },
-        "F2": {
-            "input": "P2",
-            "outputs (tonne/tonne)": {
-                "P3": 0.05,
-                "P4": 0.80
-            },
-            "locations": {
-                "L3": {
-                    "latitude (deg)": 25.0,
-                    "longitude (deg)": 65.0,
-                    "disposal": {
-                        "P3": {
-                            "cost ($/tonne)": [100.0, 100.0]
-                        }
-                    },
-                    "capacities (tonne)": {
-                        "1000.0": {
-                            "opening cost ($)": [3000, 3000],
-                            "fixed operating cost ($)": [50.0, 50.0],
-                            "variable operating cost ($/tonne)": [50.0, 50.0]
-                        }
-                    }
-                },
-                "L4": {
-                    "latitude (deg)": 0.75,
-                    "longitude (deg)": 0.20,
-                    "capacities (tonne)": {
-                        "10000": {
-                            "opening cost ($)": [3000, 3000],
-                            "fixed operating cost ($)": [50.0, 50.0],
-                            "variable operating cost ($/tonne)": [50.0, 50.0]
-                        }
-                    }
-                }
-            }
-        },
-        "F3": {
-            "input": "P4",
-            "locations": {
-                "L5": {
-                    "latitude (deg)": 100.0,
-                    "longitude (deg)": 100.0,
-                    "capacities (tonne)": {
-                        "15000": {
-                            "opening cost ($)": [0.0, 0.0],
-                            "fixed operating cost ($)": [0.0, 0.0],
-                            "variable operating cost ($/tonne)": [-15.0, -15.0]
-                        }
-                    }
-                }           
-            }
-        },
-        "F4": {
-            "input": "P3",
-            "locations": {
-                "L6": {
-                    "latitude (deg)": 50.0,
-                    "longitude (deg)": 50.0,
-                    "capacities (tonne)": {
-                        "10000": {
-                            "opening cost ($)": [0.0, 0.0],
-                            "fixed operating cost ($)": [0.0, 0.0],
-                            "variable operating cost ($/tonne)": [-15.0, -15.0]
-                        }
-                    }
-                }           
-            }
-        }
-    }
-}

instances/s2.json

@@ -1,348 +0,0 @@
-{
-    "parameters": {
-        "time horizon (years)": 2
-    },
-    "products": {
-        "P1": {
-            "transportation cost ($/km/tonne)": [
-                0.015,
-                0.015
-            ],
-            "transportation energy (J/km/tonne)": [
-                0.12,
-                0.11
-            ],
-            "transportation emissions (tonne/km/tonne)": {
-                "CO2": [
-                    0.052,
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instances/solutions/s1.json

@@ -1,950 +0,0 @@
-{
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-              "Transportation cost ($)": [
-                14803.179642,
-                14803.179642
-              ],
-              "Longitude (deg)": 16.0,
-              "Variable operating cost ($)": [
-                17609.5,
-                17609.5
-              ],
-              "Latitude (deg)": 21.0,
-              "Emissions (tonne)": {
-                "CH4": [
-                  1.05657,
-                  0.70438
-                ],
-                "CO2": [
-                  18.313879999999997,
-                  17.6095
-                ]
-              }
-            },
-            "C7": {
-              "Distance (km)": 8469.86,
-              "Amount (tonne)": [
-                538.59,
-                538.59
-              ],
-              "Transportation energy (J)": [
-                547413.827688,
-                501796.008714
-              ],
-              "Transportation cost ($)": [
-                68426.728461,
-                68426.728461
-              ],
-              "Longitude (deg)": 83.0,
-              "Variable operating cost ($)": [
-                26929.5,
-                26929.5
-              ],
-              "Latitude (deg)": 30.0,
-              "Emissions (tonne)": {
-                "CH4": [
-                  1.6157700000000002,
-                  1.07718
-                ],
-                "CO2": [
-                  28.00668,
-                  26.929500000000004
-                ]
-              }
-            }
-          }
-        }
-      }
-    },
-    "F2": {
-      "L4": {
-        "Opening cost ($)": [
-          2999.9999999999995,
-          0.0
-        ],
-        "Emissions (tonne)": {},
-        "Expansion cost ($)": [
-          0.0,
-          0.0
-        ],
-        "Longitude (deg)": 0.2,
-        "Energy (GJ)": [
-          0.0,
-          0.0
-        ],
-        "Total output": {
-          "P4": [
-            757.3824000000001,
-            757.3824000000001
-          ],
-          "P3": [
-            47.336400000000005,
-            47.336400000000005
-          ]
-        },
-        "Capacity (tonne)": [
-          10000.0,
-          10000.0
-        ],
-        "Latitude (deg)": 0.75,
-        "Output": {
-          "Send": {
-            "P4": {
-              "F3": {
-                "L5": {
-                  "Distance (km)": 8811.73,
-                  "Amount (tonne)": [
-                    757.3824000000001,
-                    757.3824000000001
-                  ],
-                  "Longitude (deg)": 100.0,
-                  "Latitude (deg)": 100.0
-                }
-              }
-            },
-            "P3": {
-              "F4": {
-                "L6": {
-                  "Distance (km)": 6824.63,
-                  "Amount (tonne)": [
-                    47.336400000000005,
-                    47.336400000000005
-                  ],
-                  "Longitude (deg)": 50.0,
-                  "Latitude (deg)": 50.0
-                }
-              }
-            }
-          },
-          "Dispose": {}
-        },
-        "Total input (tonne)": [
-          946.728,
-          946.728
-        ],
-        "Fixed operating cost ($)": [
-          50.0,
-          50.0
-        ],
-        "Input": {
-          "F1": {
-            "L1": {
-              "Distance (km)": 85.87,
-              "Amount (tonne)": [
-                199.0,
-                199.0
-              ],
-              "Transportation energy (J)": [
-                0.0,
-                0.0
-              ],
-              "Transportation cost ($)": [
-                341.7626,
-                341.7626
-              ],
-              "Longitude (deg)": 0.0,
-              "Variable operating cost ($)": [
-                9950.0,
-                9950.0
-              ],
-              "Latitude (deg)": 0.0,
-              "Emissions (tonne)": {}
-            },
-            "L2": {
-              "Distance (km)": 43.35,
-              "Amount (tonne)": [
-                747.728,
-                747.728
-              ],
-              "Transportation energy (J)": [
-                0.0,
-                0.0
-              ],
-              "Transportation cost ($)": [
-                648.280176,
-                648.280176
-              ],
-              "Longitude (deg)": 0.5,
-              "Variable operating cost ($)": [
-                37386.399999999994,
-                37386.399999999994
-              ],
-              "Latitude (deg)": 0.5,
-              "Emissions (tonne)": {}
-            }
-          }
-        }
-      }
-    },
-    "F4": {
-      "L6": {
-        "Opening cost ($)": [
-          0.0,
-          0.0
-        ],
-        "Emissions (tonne)": {},
-        "Expansion cost ($)": [
-          0.0,
-          0.0
-        ],
-        "Longitude (deg)": 50.0,
-        "Energy (GJ)": [
-          0.0,
-          0.0
-        ],
-        "Total output": {},
-        "Capacity (tonne)": [
-          10000.0,
-          10000.0
-        ],
-        "Latitude (deg)": 50.0,
-        "Output": {
-          "Send": {},
-          "Dispose": {}
-        },
-        "Total input (tonne)": [
-          2415.6564,
-          2415.6564
-        ],
-        "Fixed operating cost ($)": [
-          0.0,
-          0.0
-        ],
-        "Input": {
-          "F1": {
-            "L1": {
-              "Distance (km)": 6893.41,
-              "Amount (tonne)": [
-                499.0,
-                499.0
-              ],
-              "Transportation energy (J)": [
-                0.0,
-                0.0
-              ],
-              "Transportation cost ($)": [
-                42997.644875000005,
-                42997.644875000005
-              ],
-              "Longitude (deg)": 0.0,
-              "Variable operating cost ($)": [
-                -7485.0,
-                -7485.0
-              ],
-              "Latitude (deg)": 0.0,
-              "Emissions (tonne)": {}
-            },
-            "L2": {
-              "Distance (km)": 6828.89,
-              "Amount (tonne)": [
-                1869.32,
-                1869.32
-              ],
-              "Transportation energy (J)": [
-                0.0,
-                0.0
-              ],
-              "Transportation cost ($)": [
-                159567.258185,
-                159567.258185
-              ],
-              "Longitude (deg)": 0.5,
-              "Variable operating cost ($)": [
-                -28039.8,
-                -28039.8
-              ],
-              "Latitude (deg)": 0.5,
-              "Emissions (tonne)": {}
-            }
-          },
-          "F2": {
-            "L4": {
-              "Distance (km)": 6824.63,
-              "Amount (tonne)": [
-                47.336400000000005,
-                47.336400000000005
-              ],
-              "Transportation energy (J)": [
-                0.0,
-                0.0
-              ],
-              "Transportation cost ($)": [
-                4038.1676941500004,
-                4038.1676941500004
-              ],
-              "Longitude (deg)": 0.2,
-              "Variable operating cost ($)": [
-                -710.046,
-                -710.046
-              ],
-              "Latitude (deg)": 0.75,
-              "Emissions (tonne)": {}
-            }
-          }
-        }
-      }
-    }
-  },
-  "Emissions": {
-    "Transportation (tonne)": {
-      "CH4": [
-        14.21592,
-        9.477279999999999
-      ],
-      "CO2": [
-        246.40927999999994,
-        236.93200000000002
-      ]
-    },
-    "Plants (tonne)": {
-      "CH4": [
-        14.21592,
-        9.47728
-      ],
-      "CO2": [
-        246.40928,
-        236.93200000000002
-      ]
-    }
-  },
-  "Products": {
-    "P1": {
-      "C1": {
-        "Marginal cost ($/tonne)": [
-          133.59,
-          134.49
-        ]
-      },
-      "C2": {
-        "Marginal cost ($/tonne)": [
-          150.81,
-          151.71
-        ]
-      },
-      "C3": {
-        "Marginal cost ($/tonne)": [
-          250.83,
-          251.73
-        ]
-      },
-      "C8": {
-        "Marginal cost ($/tonne)": [
-          199.65,
-          200.55
-        ]
-      },
-      "C6": {
-        "Marginal cost ($/tonne)": [
-          217.26,
-          218.16
-        ]
-      },
-      "C10": {
-        "Marginal cost ($/tonne)": [
-          208.54,
-          209.44
-        ]
-      },
-      "C4": {
-        "Marginal cost ($/tonne)": [
-          160.36,
-          161.26
-        ]
-      },
-      "C5": {
-        "Marginal cost ($/tonne)": [
-          254.71,
-          255.61
-        ]
-      },
-      "C7": {
-        "Marginal cost ($/tonne)": [
-          245.38,
-          246.28
-        ]
-      },
-      "C9": {
-        "Marginal cost ($/tonne)": [
-          240.5,
-          241.4
-        ]
-      }
-    }
-  }
-}

instances/solutions/s1.log

@@ -1,11 +0,0 @@
-[ Info: Reading s1.json...
-[ Info: Building graph...
-[ Info:                2 time periods
-[ Info:                6 process nodes
-[ Info:                8 shipping nodes (plant)
-[ Info:               10 shipping nodes (collection)
-[ Info:               38 arcs
-[ Info: Building optimization model...
-[ Info: Optimizing MILP...
-[ Info: Re-optimizing with integer variables fixed...
-[ Info: Extracting solution...

mkdocs.yml

@@ -1,23 +0,0 @@
-site_name: RELOG
-theme: cinder
-copyright: "Copyright © 2020, UChicago Argonne, LLC. All Rights Reserved."
-repo_url: https://github.com/ANL-CEEESA/RELOG
-edit_uri: edit/master/src/docs/
-nav:
-    - Home: index.md
-    - Usage: usage.md
-    - Data Format: format.md
-    - Reports: reports.md
-    - Optimization Model: model.md
-plugins:
-  - search
-markdown_extensions:
-  - admonition  
-  - mdx_math  
-extra_javascript: 
-    - https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.0/MathJax.js?config=TeX-AMS-MML_HTMLorMML
-    - js/mathjax.js
-docs_dir: src/docs
-site_dir: docs
-extra_css:
-    - "css/custom.css"

src/RELOG.jl

@@ -1,26 +1,20 @@
-# RELOG: Reverse Logistics Optimization
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
 module RELOG
 
-include("instance/structs.jl")
+function _round(x::Number)
-
+    if abs(x) < 1e-5
-include("graph/structs.jl")
+        return 0
-
+    else
-include("graph/build.jl")
+        return round(x, digits = 5)
-include("graph/csv.jl")
+    end
-include("instance/compress.jl")
-include("instance/geodb.jl")
-include("instance/parse.jl")
-include("instance/validate.jl")
-include("model/build.jl")
-include("model/getsol.jl")
-include("model/solve.jl")
-include("reports/plant_emissions.jl")
-include("reports/plant_outputs.jl")
-include("reports/plants.jl")
-include("reports/tr_emissions.jl")
-include("reports/tr.jl")
-include("reports/write.jl")
 end
+
+include("instance/structs.jl")
+include("instance/parse.jl")
+include("model/jumpext.jl")
+include("model/dist.jl")
+include("model/build.jl")
+include("reports/plants.jl")
+include("reports/transportation.jl")
+include("reports/centers.jl")
+
+end # module RELOG

src/docs/css/custom.css

@@ -1,28 +0,0 @@
-.navbar-default {
-  border-bottom: 0px;
-  background-color: #fff;
-  box-shadow: 0px 0px 15px rgba(0, 0, 0, 0.2);
-}
-
-a, .navbar-default a {
-  color: #06a !important;
-  font-weight: normal;
-}
-
-.disabled > a {
-  color: #999 !important;
-}
-
-.navbar-default a:hover,
-.navbar-default .active,
-.active > a {
-  background-color: #f0f0f0 !important;
-}
-
-.icon-bar {
-  background-color: #666 !important;
-}
-
-.navbar-collapse {
-  border-color: #fff !important;
-}

src/docs/format.md

@@ -1,195 +0,0 @@
-# Input and Output Data Formats
-
-In this page, we describe the input and output JSON formats used by RELOG. In addition to these, RELOG can also produce [simplified reports](reports.md) in tabular data format.
-
-## Input Data Format (JSON)
-
-RELOG accepts as input a JSON file with three sections: `parameters`, `products` and `plants`. Below, we describe each section in more detail.
-
-### Parameters
-
-The **parameters** section describes details about the simulation itself.
-
-| Key                       | Description
-|:--------------------------|---------------|
-|`time horizon (years)`     | Number of years in the simulation.
-|`building period (years)`  | List of years in which we are allowed to open new plants. For example, if this parameter is set to `[1,2,3]`, we can only open plants during the first three years. By default, this equals `[1]`; that is, plants can only be opened during the first year. |
-
-
-#### Example
-```json
-{
-    "parameters": {
-        "time horizon (years)": 2,
-        "building period (years)": [1]
-    }
-}
-```
-
-### Products
-
-The **products** section describes all products and subproducts in the simulation. The field `instance["Products"]` is a dictionary mapping the name of the product to a dictionary which describes its characteristics. Each product description contains the following keys:
-
-| Key                                   | Description
-|:--------------------------------------|---------------|
-|`transportation cost ($/km/tonne)`     | The cost to transport this product. Must be a time series.
-|`transportation energy (J/km/tonne)`   | The energy required to transport this product. Must be a time series. Optional.
-|`transportation emissions (tonne/km/tonne)`  | A dictionary mapping the name of each greenhouse gas, produced to transport one tonne of this product along one kilometer, to the amount of gas produced (in tonnes). Must be a time series. Optional.
-|`initial amounts`                      | A dictionary mapping the name of each location to its description (see below). If this product is not initially available, this key may be omitted. Must be a time series.
-
-Each product may have some amount available at the beginning of each time period. In this case, the key `initial amounts` maps to a dictionary with the following keys:
-
-| Key                     | Description
-|:------------------------|---------------|
-| `latitude (deg)`        | The latitude of the location.
-| `longitude (deg)`       | The longitude of the location.
-| `amount (tonne)`       | The amount of the product initially available at the location. Must be a time series.
-
-#### Example
-
-```json
-{
-    "products": {
-        "P1": {
-            "initial amounts": {
-                "C1": {
-                    "latitude (deg)": 7.0,
-                    "longitude (deg)": 7.0,
-                    "amount (tonne)": [934.56, 934.56]
-                },
-                "C2": {
-                    "latitude (deg)": 7.0,
-                    "longitude (deg)": 19.0,
-                    "amount (tonne)": [198.95, 198.95]
-                },
-                "C3": {
-                    "latitude (deg)": 84.0,
-                    "longitude (deg)": 76.0,
-                    "amount (tonne)": [212.97, 212.97]
-                }
-            },
-            "transportation cost ($/km/tonne)": [0.015, 0.015],
-            "transportation energy (J/km/tonne)": [0.12, 0.11],
-            "transportation emissions (tonne/km/tonne)": {
-                "CO2": [0.052, 0.050],
-                "CH4": [0.003, 0.002]
-            }
-        },
-        "P2": {
-            "transportation cost ($/km/tonne)": [0.022, 0.020]
-        },
-        "P3": {
-            "transportation cost ($/km/tonne)": [0.0125, 0.0125]
-        },
-        "P4": {
-            "transportation cost ($/km/tonne)": [0.0175, 0.0175]
-        }
-    }
-}
-```
-
-### Processing plants
-
-The **plants** section describes the available types of reverse manufacturing plants, their potential locations and associated costs, as well as their inputs and outputs. The field `instance["Plants"]` is a dictionary mapping the name of the plant to a dictionary with the following keys:
-
-| Key                     | Description
-|:------------------------|---------------|
-| `input`                 | The name of the product that this plant takes as input. Only one input is accepted per plant.
-| `outputs (tonne/tonne)`               | A dictionary specifying how many tonnes of each product is produced for each tonnes of input. For example, if the plant outputs 0.5 tonnes of P2 and 0.25 tonnes of P3 for each tonnes of P1 provided, then this entry should be `{"P2": 0.5, "P3": 0.25}`. If the plant does not output anything, this key may be omitted.
-|`energy (GJ/tonne)`   | The energy required to process 1 tonne of the input. Must be a time series. Optional.
-|`emissions (tonne/tonne)`  | A dictionary mapping the name of each greenhouse gas, produced to process each tonne of input, to the amount of gas produced (in tonne). Must be a time series. Optional.
-| `locations`             | A dictionary mapping the name of the location to a dictionary which describes the site characteristics (see below).
-
-Each type of plant is associated with a set of potential locations where it can be built. Each location is represented by a dictionary with the following keys:
-
-| Key                           | Description
-|:------------------------------|---------------|
-| `latitude (deg)`              | The latitude of the location, in degrees.
-| `longitude (deg)`             | The longitude of the location, in degrees.
-| `disposal`                    | A dictionary describing what products can be disposed locally at the plant.
-| `storage`                     | A dictionary describing the plant's storage.
-| `capacities (tonne)`          | A dictionary describing what plant sizes are allowed, and their characteristics.
-
-The `storage` dictionary should contain the following keys:
-
-| Key                     | Description
-|:------------------------|---------------|
-| `cost ($/tonne)`       | The cost to store a tonne of input product for one time period. Must be a time series.
-| `limit (tonne)`        | The maximum amount of input product this plant can have in storage at any given time.
-
-The keys in the `disposal` dictionary should be the names of the products. The values are dictionaries with the following keys:
-
-| Key                     | Description
-|:------------------------|---------------|
-| `cost ($/tonne)`       | The cost to dispose of the product. Must be a time series.
-| `limit (tonne)`        | The maximum amount that can be disposed of. If an unlimited amount can be disposed, this key may be omitted. Must be a time series.
-
-
-The keys in the `capacities (tonne)` dictionary should be the amounts (in tonnes). The values are dictionaries with the following keys:
-
-| Key                                   | Description
-|:--------------------------------------|---------------|
-| `opening cost ($)`                    | The cost to open a plant of this size.
-| `fixed operating cost ($)`            | The cost to keep the plant open, even if the plant doesn't process anything. Must be a time series.
-| `variable operating cost ($/tonne)`  | The cost that the plant incurs to process each tonne of input. Must be a time series.
-
-#### Example
-
-```json
-{
-    "plants": {
-        "F1": {
-            "input": "P1",
-            "outputs (tonne/tonne)": {
-                "P2": 0.2,
-                "P3": 0.5
-            },
-            "energy (GJ/tonne)": [0.12, 0.11],
-            "emissions (tonne/tonne)": {
-                "CO2": [0.052, 0.050],
-                "CH4": [0.003, 0.002]
-            },
-            "locations": {
-                "L1": {
-                    "latitude (deg)": 0.0,
-                    "longitude (deg)": 0.0,
-                    "disposal": {
-                        "P2": {
-                            "cost ($/tonne)": [-10.0, -12.0],
-                            "limit (tonne)": [1.0, 1.0]
-                        }
-                    },
-                    "storage": {
-                        "cost ($/tonne)": [5.0, 5.3],
-                        "limit (tonne)": 100.0,
-                    },
-                    "capacities (tonne)": {
-                        "100": {
-                            "opening cost ($)": [500, 530],
-                            "fixed operating cost ($)": [300.0, 310.0],
-                            "variable operating cost ($/tonne)": [5.0, 5.2],
-                        },
-                        "500": {
-                            "opening cost ($)": [750, 760],
-                            "fixed operating cost ($)": [400.0, 450.0],
-                            "variable operating cost ($/tonne)": [5.0, 5.2]
-                        }
-                    }
-                }
-            }
-        }
-    }
-}
-```
-
-### Current limitations
-
-* Each plant can only be opened exactly once. After open, the plant remains open until the end of the simulation.
-* Plants can be expanded at any time, even long after they are open.
-* All material available at the beginning of a time period must be entirely processed by the end of that time period. It is not possible to store unprocessed materials from one time period to the next.
-* Up to two plant sizes are currently supported. Variable operating costs must be the same for all plant sizes.
-
-## Output Data Format (JSON)
-
-To be documented.
-

src/docs/js/mathjax.js

@@ -1,8 +0,0 @@
-MathJax.Hub.Config({
-  "tex2jax": { inlineMath: [ [ '$', '$' ] ] }
-});
-MathJax.Hub.Config({
-  config: ["MMLorHTML.js"],
-  jax: ["input/TeX", "output/HTML-CSS", "output/NativeMML"],
-  extensions: ["MathMenu.js", "MathZoom.js"]
-});

src/docs/model.md

@@ -1,165 +0,0 @@
-# Optimization Model
-
-In this page, we describe the precise mathematical optimization model used by RELOG to find the optimal logistics plan. This model is a variation of the classical Facility Location Problem, which has been widely studied in the operations research literature. To simplify the exposition, we present the simplified case where there is only one type of plant.
-
-## Mathematical Description
-
-### Sets
-
-* $L$ - Set of locations holding the original material to be recycled
-* $M$ - Set of materials recovered during the reverse manufacturing process
-* $P$ - Set of potential plants to open
-* $T = \{ 1, \ldots, t^{max} \} $ - Set of time periods
-
-### Constants
-
-**Plants:**
-
-* $c^\text{disp}_{pmt}$ - Cost of disposing one tonne of material $m$ at plant $p$ during time $t$ (`$/tonne/km`)
-* $c^\text{exp}_{pt}$ - Cost of adding one tonne of capacity to plant $p$ at time $t$ (`$/tonne`)
-* $c^\text{open}_{pt}$ - Cost of opening plant $p$ at time $t$, at minimum capacity (`$`)
-* $c^\text{f-base}_{pt}$ - Fixed cost of keeping plant $p$ open during time period $t$ (`$`)
-* $c^\text{f-exp}_{pt}$ - Increase in fixed cost for each additional tonne of capacity (`$/tonne`)
-* $c^\text{var}_{pt}$ - Variable cost of processing one tonne of input at plant $p$ at time $t$ (`$/tonne`)
-* $c^\text{store}_{pt}$ - Cost of storing one tonne of original material at plant $p$ at time $t$ (`$/tonne`)
-* $m^\text{min}_p$ - Minimum capacity of plant $p$ (`tonne`)
-* $m^\text{max}_p$ - Maximum capacity of plant $p$ (`tonne`)
-* $m^\text{disp}_{pmt}$ - Maximum amount of material $m$ that plant $p$ can dispose of during time $t$ (`tonne`)
-* $m^\text{store}_p$ - Maximum amount of original material that plant $p$ can store for later processing.
-
-**Products:**
-
-* $\alpha_{pm}$ - Amount of material $m$ recovered by plant $t$ for each tonne of original material (`tonne/tonne`)
-* $m^\text{initial}_{lt}$ - Amount of original material to be recycled at location $l$ during time $t$ (`tonne`)
-
-**Transportation:**
-
-* $c^\text{tr}_{t}$ - Transportation cost during time $t$ (`$/tonne/km`)
-* $d_{lp}$ - Distance between plant $p$ and location $l$ (`km`)
-
-
-### Decision variables
-* $q_{mpt}$ - Amount of material $m$ recovered by plant $p$ during time $t$ (`tonne`)
-* $u_{pt}$ - Binary variable that equals 1 if plant $p$ starts operating at time $t$ (`bool`)
-* $w_{pt}$ - Extra capacity (amount above the minimum) added to plant $p$ during time $t$ (`tonne`)
-* $x_{pt}$ - Binary variable that equals 1 if plant $p$ is operational at time $t$ (`bool`)
-* $y_{lpt}$ - Amount of product sent from location $l$ to plant $p$ during time $t$ (`tonne`)
-* $z^{\text{disp}}_{mpt}$ - Amount of material $m$ disposed of by plant $p$ during time $t$ (`tonne`)
-* $z^{\text{store}}_{pt}$ - Amount of original material in storage at plant $p$ by the end of time period $t$ (`tonne`)
-* $z^{\text{proc}}_{mpt}$ - Amount of original material processed by plant $p$ during time period $t$ (`tonne`)
-
-
-### Objective function
-
-RELOG minimizes the overall capital, production and transportation costs:
-
-\begin{align*}
-    \text{minimize} \;\; &
-        \sum_{t \in T} \sum_{p \in P} \left[
-                c^\text{open}_{pt} u_{pt} +
-                c^\text{f-base}_{pt} x_{pt} +
-                \sum_{i=1}^t c^\text{f-exp}_{pt} w_{pi} +
-                c^{\text{exp}}_{pt} w_{pt}
-            \right] + \\
-    & 
-        \sum_{t \in T} \sum_{p \in P} \left[
-                c^{\text{store}}_{pt} z^{\text{store}}_{pt} +
-                c^{\text{proc}}_{pt} z^{\text{proc}}_{pt}
-            \right] + \\
-    &
-        \sum_{t \in T} \sum_{l \in L} \sum_{p \in P}
-            c^{\text{tr}}_t d_{lp} y_{lpt}
-        \\
-    &
-        \sum_{t \in T} \sum_{p \in P} \sum_{m \in M} c^{\text{disp}}_{pmt} z_{pmt}
-\end{align*}
-
-In the first line, we have (i) opening costs, if plant starts operating at time $t$, (ii) fixed operating costs, if plant is operational, (iii) additional fixed operating costs coming from expansion performed in all previous time periods up to the current one, and finally (iv) the expansion costs during the current time period.
-In the second line, we have storage and variable processing costs.
-In the third line, we have transportation costs.
-In the fourth line, we have the disposal costs.
-
-### Constraints
-
-* All original materials must be sent to a plant:
-
-\begin{align}
-    & \sum_{p \in P} y_{lpt} = m^\text{initial}_{lt} 
-        & \forall l \in L, t \in T
-\end{align}
-
-* Amount received equals amount processed plus stored. Furthermore, all original material should be processed by the end of the simulation.
-
-\begin{align}
-    & \sum_{l \in L} y_{lpt} + z^{\text{store}}_{p,t-1}
-        = z^{\text{proc}}_{pt} + z^{\text{store}}_{p,t}
-        & \forall p \in P, t \in T \\
-    & z^{\text{store}}_{p,0} = 0
-        & \forall p \in P \\
-    & z^{\text{store}}_{p,t^{\max}} = 0
-        & \forall p \in P
-\end{align}
-
-* Plants have a limited processing capacity. Furthermore, if a plant is closed, it has zero processing capacity:
-
-\begin{align}
-    & z^{\text{proc}}_{pt} \leq m^\text{min}_p x_p + \sum_{i=1}^t w_p
-        & \forall p \in P, t \in T
-\end{align}
-
-* Plants have limited storage capacity. Furthermore, if a plant is closed, is has zero storage capacity:
-
-\begin{align}
-    & z^{\text{store}}_{pt} \leq m^\text{store}_p x_p
-        & \forall p \in P, t \in T
-\end{align}
-
-* Plants can only be expanded up to their maximum capacity. Furthermore, if a plant is closed, it cannot be expanded:
-
-\begin{align}
-    & \sum_{i=1}^t w_p \leq m^\text{max}_p x_p
-        & \forall p \in P, t \in T
-\end{align}
-
-* Amount of recovered material is proportional to amount processed: 
-
-\begin{align}
-    & q_{mpt} = \alpha_{pm} z^{\text{proc}}_{pt}
-        & \forall m \in M, p \in P, t \in T
-\end{align}
-
-* Because we only consider a single type of plant, all recovered material must be immediately disposed of. In RELOG's full model, recovered materials may be sent to another plant for further processing.
-
-\begin{align}
-    & q_{mpt} = z_{mpt}
-        & \forall m \in M, p \in P, t \in T
-\end{align}
-
-* A plant is operational at time $t$ if it was operational at time $t-1$ or it was built at time $t$. This constraint also prevents a plant from being built multiple times.
-
-\begin{align}
-    & x_{pt} = x_{p,t-1} + u_{pt}
-        & \forall p \in P, t \in T \setminus \{1\} \\
-    & x_{p,1} = u_{p,1}
-        & \forall p \in P
-\end{align}
-
-
-* Variable bounds:
-
-\begin{align}
-    & q_{mpt} \geq 0
-        & \forall m \in M, p \in P, t \in T \\
-    & u_{pt} \in \{0,1\}
-        & \forall p \in P, t \in T \\
-    & w_{pt} \geq 0
-        & \forall p \in P, t \in T \\
-    & x_{pt} \in \{0,1\}
-        & \forall p \in P, t \in T \\
-    & y_{lpt} \geq 0
-        & \forall l \in L, p \in P, t \in T \\
-    & z^{\text{store}}_{pt} \geq 0
-        & p \in P, t \in T \\
-    & z^{\text{disp}}_{mpt}, z^{\text{proc}}_{mpt} \geq 0
-        & \forall m \in M, p \in P, t \in T
-\end{align}

src/graph/build.jl

@@ -1,77 +0,0 @@
-# RELOG: Reverse Logistics Optimization
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-using Geodesy
-
-function calculate_distance(source_lat, source_lon, dest_lat, dest_lon)::Float64
-    x = LLA(source_lat, source_lon, 0.0)
-    y = LLA(dest_lat, dest_lon, 0.0)
-    return round(distance(x, y) / 1000.0, digits = 2)
-end
-
-function build_graph(instance::Instance)::Graph
-    arcs = []
-    next_index = 0
-    process_nodes = ProcessNode[]
-    plant_shipping_nodes = ShippingNode[]
-    collection_shipping_nodes = ShippingNode[]
-
-    process_nodes_by_input_product =
-        Dict(product => ProcessNode[] for product in instance.products)
-    shipping_nodes_by_plant = Dict(plant => [] for plant in instance.plants)
-
-    # Build collection center shipping nodes
-    for center in instance.collection_centers
-        node = ShippingNode(next_index, center, center.product, [], [])
-        next_index += 1
-        push!(collection_shipping_nodes, node)
-    end
-
-    # Build process and shipping nodes for plants
-    for plant in instance.plants
-        pn = ProcessNode(next_index, plant, [], [])
-        next_index += 1
-        push!(process_nodes, pn)
-        push!(process_nodes_by_input_product[plant.input], pn)
-
-        for product in keys(plant.output)
-            sn = ShippingNode(next_index, plant, product, [], [])
-            next_index += 1
-            push!(plant_shipping_nodes, sn)
-            push!(shipping_nodes_by_plant[plant], sn)
-        end
-    end
-
-    # Build arcs from collection centers to plants, and from one plant to another
-    for source in [collection_shipping_nodes; plant_shipping_nodes]
-        for dest in process_nodes_by_input_product[source.product]
-            distance = calculate_distance(
-                source.location.latitude,
-                source.location.longitude,
-                dest.location.latitude,
-                dest.location.longitude,
-            )
-            values = Dict("distance" => distance)
-            arc = Arc(source, dest, values)
-            push!(source.outgoing_arcs, arc)
-            push!(dest.incoming_arcs, arc)
-            push!(arcs, arc)
-        end
-    end
-
-    # Build arcs from process nodes to shipping nodes within a plant
-    for source in process_nodes
-        plant = source.location
-        for dest in shipping_nodes_by_plant[plant]
-            weight = plant.output[dest.product]
-            values = Dict("weight" => weight)
-            arc = Arc(source, dest, values)
-            push!(source.outgoing_arcs, arc)
-            push!(dest.incoming_arcs, arc)
-            push!(arcs, arc)
-        end
-    end
-
-    return Graph(process_nodes, plant_shipping_nodes, collection_shipping_nodes, arcs)
-end

src/graph/csv.jl

@@ -1,11 +0,0 @@
-# RELOG: Reverse Logistics Optimization
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-function to_csv(graph::Graph)
-    result = ""
-    for a in graph.arcs
-        result *= "$(a.source.index),$(a.dest.index)\n"
-    end
-    return result
-end

src/graph/structs.jl

@@ -1,35 +0,0 @@
-# RELOG: Reverse Logistics Optimization
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-using Geodesy
-
-abstract type Node end
-
-mutable struct Arc
-    source::Node
-    dest::Node
-    values::Dict{String,Float64}
-end
-
-mutable struct ProcessNode <: Node
-    index::Int
-    location::Plant
-    incoming_arcs::Vector{Arc}
-    outgoing_arcs::Vector{Arc}
-end
-
-mutable struct ShippingNode <: Node
-    index::Int
-    location::Union{Plant,CollectionCenter}
-    product::Product
-    incoming_arcs::Vector{Arc}
-    outgoing_arcs::Vector{Arc}
-end
-
-mutable struct Graph
-    process_nodes::Vector{ProcessNode}
-    plant_shipping_nodes::Vector{ShippingNode}
-    collection_shipping_nodes::Vector{ShippingNode}
-    arcs::Vector{Arc}
-end

src/instance/compress.jl

@@ -1,60 +0,0 @@
-# RELOG: Reverse Logistics Optimization
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-using DataStructures
-using JSON
-using JSONSchema
-using Printf
-using Statistics
-
-"""
-    _compress(instance::Instance)
-
-Create a single-period instance from a multi-period one. Specifically,
-replaces every time-dependent attribute, such as initial_amounts,
-by a list with a single element, which is either a sum, an average,
-or something else that makes sense to that specific attribute.
-"""
-function _compress(instance::Instance)::Instance
-    T = instance.time
-    compressed = deepcopy(instance)
-    compressed.time = 1
-    compressed.building_period = [1]
-
-    # Compress products
-    for p in compressed.products
-        p.transportation_cost = [mean(p.transportation_cost)]
-        p.transportation_energy = [mean(p.transportation_energy)]
-        for (emission_name, emission_value) in p.transportation_emissions
-            p.transportation_emissions[emission_name] = [mean(emission_value)]
-        end
-    end
-
-    # Compress collection centers
-    for c in compressed.collection_centers
-        c.amount = [maximum(c.amount) * T]
-    end
-
-    # Compress plants
-    for plant in compressed.plants
-        plant.energy = [mean(plant.energy)]
-        for (emission_name, emission_value) in plant.emissions
-            plant.emissions[emission_name] = [mean(emission_value)]
-        end
-        for s in plant.sizes
-            s.capacity *= T
-            s.variable_operating_cost = [mean(s.variable_operating_cost)]
-            s.opening_cost = [s.opening_cost[1]]
-            s.fixed_operating_cost = [sum(s.fixed_operating_cost)]
-        end
-        for (prod_name, disp_limit) in plant.disposal_limit
-            plant.disposal_limit[prod_name] = [sum(disp_limit)]
-        end
-        for (prod_name, disp_cost) in plant.disposal_cost
-            plant.disposal_cost[prod_name] = [mean(disp_cost)]
-        end
-    end
-
-    return compressed
-end

src/instance/geodb.jl

@@ -1,229 +0,0 @@
-# RELOG: Reverse Logistics Optimization
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-using CRC
-using CSV
-using DataFrames
-using Shapefile
-using Statistics
-using ZipFile
-using ProgressBars
-using OrderedCollections
-
-import Downloads: download
-import Base: parse
-
-crc32 = crc(CRC_32)
-
-struct GeoPoint
-    lat::Float64
-    lon::Float64
-end
-
-struct GeoRegion
-    centroid::GeoPoint
-    population::Int
-    GeoRegion(; centroid, population) = new(centroid, population)
-end
-
-DB_CACHE = Dict{String,Dict{String,GeoRegion}}()
-
-function centroid(geom::Shapefile.Polygon)::GeoPoint
-    x_max, x_min, y_max, y_min = -Inf, Inf, -Inf, Inf
-    for p in geom.points
-        x_max = max(x_max, p.x)
-        x_min = min(x_min, p.x)
-        y_max = max(y_max, p.y)
-        y_min = min(y_min, p.y)
-    end
-    x_center = (x_max + x_min) / 2.0
-    y_center = (y_max + y_min) / 2.0
-    return GeoPoint(round(y_center, digits = 5), round(x_center, digits = 5))
-end
-
-function _download(url, output, expected_crc32)::Nothing
-    if isfile(output)
-        return
-    end
-    mkpath(dirname(output))
-    @info "Downloading: $url"
-    fname = download(url)
-    actual_crc32 = open(crc32, fname)
-    expected_crc32 == actual_crc32 || error("CRC32 mismatch")
-    cp(fname, output)
-    return
-end
-
-function _download_zip(url, outputdir, expected_crc32)::Nothing
-    if isdir(outputdir)
-        return
-    end
-    mkpath(outputdir)
-    @info "Downloading: $url"
-    zip_filename = _download(url)
-    actual_crc32 = open(crc32, zip_filename)
-    expected_crc32 == actual_crc32 || error("CRC32 mismatch")
-    open(zip_filename) do zip_file
-        zr = ZipFile.Reader(zip_file)
-        for file in zr.files
-            open(joinpath(outputdir, file.name), "w") do output_file
-                write(output_file, read(file))
-            end
-        end
-    end
-    return
-end
-
-function _geodb_load_gov_census(;
-    db_name,
-    extract_cols,
-    shp_crc32,
-    shp_filename,
-    shp_url,
-    population_url,
-    population_crc32,
-    population_col,
-    population_preprocess,
-    population_join,
-)::Dict{String,GeoRegion}
-    basedir = joinpath(dirname(@__FILE__), "..", "..", "data", db_name)
-    csv_filename = "$basedir/locations.csv"
-    if !isfile(csv_filename)
-        # Download required files
-        _download(population_url, "$basedir/population.csv", population_crc32)
-        _download_zip(shp_url, basedir, shp_crc32)
-
-        # Read shapefile
-        @info "Processing: $shp_filename"
-        table = Shapefile.Table(joinpath(basedir, shp_filename))
-        geoms = Shapefile.shapes(table)
-
-        # Build empty dataframe
-        df = DataFrame()
-        cols = extract_cols(table, 1)
-        for k in keys(cols)
-            df[!, k] = []
-        end
-        df[!, "latitude"] = Float64[]
-        df[!, "longitude"] = Float64[]
-
-        # Add regions to dataframe
-        for (i, geom) in tqdm(enumerate(geoms))
-            c = centroid(geom)
-            cols = extract_cols(table, i)
-            push!(df, [values(cols)..., c.lat, c.lon])
-        end
-        sort!(df)
-
-        # Join with population data
-        population = DataFrame(CSV.File("$basedir/population.csv"))
-        population_preprocess(population)
-        population = population[:, [population_join, population_col]]
-        rename!(population, population_col => "population")
-        df = leftjoin(df, population, on = population_join)
-
-        # Write output
-        CSV.write(csv_filename, df)
-    end
-    if db_name ∉ keys(DB_CACHE)
-        csv = CSV.File(csv_filename)
-        DB_CACHE[db_name] = Dict(
-            string(row.id) => GeoRegion(
-                centroid = GeoPoint(row.latitude, row.longitude),
-                population = (row.population === missing ? 0 : row.population),
-            ) for row in csv
-        )
-    end
-    return DB_CACHE[db_name]
-end
-
-# 2018 US counties
-# -----------------------------------------------------------------------------
-function _extract_cols_2018_us_county(table::Shapefile.Table, i::Int)::OrderedDict{String,Any}
-    return OrderedDict(
-        "id" => table.STATEFP[i] * table.COUNTYFP[i],
-        "statefp" => table.STATEFP[i],
-        "countyfp" => table.COUNTYFP[i],
-        "name" => table.NAME[i]
-    )
-end
-
-function _population_preprocess_2018_us_county(df)
-    df[!, "id"] = [@sprintf("%02d%03d", row.STATE, row.COUNTY) for row in eachrow(df)]
-end
-
-function _geodb_load_2018_us_county()::Dict{String,GeoRegion}
-    return _geodb_load_gov_census(
-        db_name = "2018-us-county",
-        extract_cols = _extract_cols_2018_us_county,
-        shp_crc32 = 0x83eaec6d,
-        shp_filename = "cb_2018_us_county_500k.shp",
-        shp_url = "https://www2.census.gov/geo/tiger/GENZ2018/shp/cb_2018_us_county_500k.zip",
-        population_url = "https://www2.census.gov/programs-surveys/popest/datasets/2010-2019/counties/totals/co-est2019-alldata.csv",
-        population_crc32 = 0xf85b0405,
-        population_col = "POPESTIMATE2019",
-        population_join = "id",
-        population_preprocess = _population_preprocess_2018_us_county,
-    )
-end
-
-# # 2018 US ZIP codes
-# # -----------------------------------------------------------------------------
-# function _extract_cols_2018_us_zcta(table::Shapefile.Table, i::Int)::OrderedDict{String,Any}
-#     return OrderedDict("id" => table.ZCTA5CE10[i])
-# end
-
-# function _geodb_load_2018_us_zcta()::Dict{String,GeoRegion}
-#     return _geodb_load_gov_census(
-#         db_name = "2018-us-zcta",
-#         extract_cols = _extract_cols_2018_us_zcta,
-#         shp_crc32 = 0x6391f5fc,
-#         shp_filename = "cb_2018_us_zcta510_500k.shp",
-#         shp_url = "https://www2.census.gov/geo/tiger/GENZ2018/shp/cb_2018_us_zcta510_500k.zip",
-#         population_url = "http://www2.census.gov/programs-surveys/popest/datasets/2010-2019/national/totals/nst-est2019-alldata.csv",
-#         population_crc32 = 0x191cc64c,
-#         population_col = "POPESTIMATE2019",
-#     )
-# end
-
-# US States
-# -----------------------------------------------------------------------------
-function _extract_cols_us_state(table::Shapefile.Table, i::Int)::OrderedDict{String,Any}
-    return OrderedDict(
-        "id" => table.STUSPS[i],
-        "statefp" => parse(Int, table.STATEFP[i]),
-        "name" => table.NAME[i],
-    )
-end
-
-function _population_preprocess_us_state(df)
-    rename!(df, "STATE" => "statefp")
-end
-
-function _geodb_load_us_state()::Dict{String,GeoRegion}
-    return _geodb_load_gov_census(
-        db_name = "us-state",
-        extract_cols = _extract_cols_us_state,
-        shp_crc32 = 0x9469e5ca,
-        shp_filename = "cb_2018_us_state_500k.shp",
-        shp_url = "https://www2.census.gov/geo/tiger/GENZ2018/shp/cb_2018_us_state_500k.zip",
-        population_url = "http://www2.census.gov/programs-surveys/popest/datasets/2010-2019/national/totals/nst-est2019-alldata.csv",
-        population_crc32 = 0x191cc64c,
-        population_col = "POPESTIMATE2019",
-        population_join = "statefp",
-        population_preprocess = _population_preprocess_us_state,
-    )
-end
-
-function geodb_load(db_name::AbstractString)::Dict{String,GeoRegion}
-    db_name == "2018-us-county" && return _geodb_load_2018_us_county()
-    db_name == "2018-us-zcta" && return _geodb_load_2018_us_zcta()
-    db_name == "us-state" && return _geodb_load_us_state()
-    error("Unknown database: $db_name")
-end
-
-function geodb_query(name)::GeoRegion
-    db_name, id = split(name, ":")
-    return geodb_load(db_name)[id]
-end

src/instance/parse.jl

@@ -1,173 +1,183 @@
-# RELOG: Reverse Logistics Optimization
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-using DataStructures
 using JSON
-using JSONSchema
+using OrderedCollections
-using Printf
-using Statistics
 
 function parsefile(path::String)::Instance
-    return RELOG.parse(JSON.parsefile(path))
+    return RELOG.parse(JSON.parsefile(path; dicttype = OrderedDict))
 end
 
 function parse(json)::Instance
-    basedir = dirname(@__FILE__)
+    # Read parameters
-    json_schema = JSON.parsefile("$basedir/../schemas/input.json")
+    time_horizon = json["parameters"]["time horizon (years)"]
-    validate(json, Schema(json_schema))
+    building_period = json["parameters"]["building period (years)"]
 
-    T = json["parameters"]["time horizon (years)"]
+    # Read distance metric
-    json_schema["definitions"]["TimeSeries"]["minItems"] = T
+    distance_metric_str = lowercase(json["parameters"]["distance metric"])
-    json_schema["definitions"]["TimeSeries"]["maxItems"] = T
+    if distance_metric_str == "driving"
-    validate(json, Schema(json_schema))
+        distance_metric = KnnDrivingDistance()
+    elseif distance_metric_str == "euclidean"
+        distance_metric = EuclideanDistance()
+    else
+        error("Invalid distance metric: $distance_metric_str")
+    end
 
-    building_period = [1]
+    timeseries(::Nothing; null_val = nothing) = repeat([null_val], time_horizon)
-    if "building period (years)" in keys(json)
+    timeseries(x::Number; null_val = nothing) = repeat([x], time_horizon)
-        building_period = json["building period (years)"]
+    timeseries(x::Array; null_val = nothing) = [xi === nothing ? null_val : xi for xi in x]
+    timeseries(d::OrderedDict; null_val = nothing) =
+        OrderedDict(k => timeseries(v; null_val) for (k, v) in d)
+
+    # Read products
+    products = Product[]
+    products_by_name = OrderedDict{String,Product}()
+    for (name, pdict) in json["products"]
+        tr_cost = timeseries(pdict["transportation cost (\$/km/tonne)"])
+        tr_energy = timeseries(pdict["transportation energy (J/km/tonne)"])
+        tr_emissions = timeseries(pdict["transportation emissions (tonne/km/tonne)"])
+        disposal_limit = timeseries(pdict["disposal limit (tonne)"], null_val = Inf)
+        prod = Product(; name, tr_cost, tr_energy, tr_emissions, disposal_limit)
+        push!(products, prod)
+        products_by_name[name] = prod
+    end
+
+    # Read centers
+    centers = Center[]
+    centers_by_name = OrderedDict{String,Center}()
+    for (name, cdict) in json["centers"]
+        latitude = cdict["latitude (deg)"]
+        longitude = cdict["longitude (deg)"]
+        input = nothing
+        revenue = [0.0 for t = 1:time_horizon]
+        if cdict["input"] !== nothing
+            input = products_by_name[cdict["input"]]
+            revenue = timeseries(cdict["revenue (\$/tonne)"])
+        end
+        outputs = [products_by_name[p] for p in cdict["outputs"]]
+        operating_cost = timeseries(cdict["operating cost (\$)"])
+        prod_dict(key, null_val) =
+            OrderedDict(p => timeseries(cdict[key][p.name]; null_val) for p in outputs)
+        fixed_output = prod_dict("fixed output (tonne)", 0.0)
+        var_output = prod_dict("variable output (tonne/tonne)", 0.0)
+        collection_cost = prod_dict("collection cost (\$/tonne)", 0.0)
+        disposal_limit = prod_dict("disposal limit (tonne)", Inf)
+        disposal_cost = prod_dict("disposal cost (\$/tonne)", 0.0)
+
+        center = Center(;
+            name,
+            latitude,
+            longitude,
+            input,
+            outputs,
+            revenue,
+            operating_cost,
+            fixed_output,
+            var_output,
+            collection_cost,
+            disposal_cost,
+            disposal_limit,
+        )
+        push!(centers, center)
+        centers_by_name[name] = center
     end
 
     plants = Plant[]
-    products = Product[]
+    plants_by_name = OrderedDict{String,Plant}()
-    collection_centers = CollectionCenter[]
+    for (name, pdict) in json["plants"]
-    prod_name_to_product = Dict{String,Product}()
+        prod_dict(key; scale = 1.0, null_val = Inf) = OrderedDict{Product,Vector{Float64}}(
-
+            products_by_name[p] => [
-    # Create products
+                v === nothing ? null_val : v * scale for v in timeseries(pdict[key][p])
-    for (product_name, product_dict) in json["products"]
+            ] for p in keys(pdict[key])
-        cost = product_dict["transportation cost (\$/km/tonne)"]
-        energy = zeros(T)
-        emissions = Dict()
-
-        if "transportation energy (J/km/tonne)" in keys(product_dict)
-            energy = product_dict["transportation energy (J/km/tonne)"]
-        end
-
-        if "transportation emissions (tonne/km/tonne)" in keys(product_dict)
-            emissions = product_dict["transportation emissions (tonne/km/tonne)"]
-        end
-
-        product = Product(product_name, cost, energy, emissions)
-        push!(products, product)
-        prod_name_to_product[product_name] = product
-
-        # Create collection centers
-        if "initial amounts" in keys(product_dict)
-            for (center_name, center_dict) in product_dict["initial amounts"]
-                if "location" in keys(center_dict)
-                    region = geodb_query(center_dict["location"])
-                    center_dict["latitude (deg)"] = region.centroid.lat
-                    center_dict["longitude (deg)"] = region.centroid.lon
-                end
-                center = CollectionCenter(
-                    length(collection_centers) + 1,
-                    center_name,
-                    center_dict["latitude (deg)"],
-                    center_dict["longitude (deg)"],
-                    product,
-                    center_dict["amount (tonne)"],
         )
-                push!(collection_centers, center)
-            end
-        end
-    end
 
-    # Create plants
+        latitude = pdict["latitude (deg)"]
-    for (plant_name, plant_dict) in json["plants"]
+        longitude = pdict["longitude (deg)"]
-        input = prod_name_to_product[plant_dict["input"]]
+        input_mix = prod_dict("input mix (%)", scale = 0.01)
-        output = Dict()
+        output = prod_dict("output (tonne)")
-
+        emissions = timeseries(pdict["processing emissions (tonne)"])
-        # Plant outputs
+        storage_cost = prod_dict("storage cost (\$/tonne)")
-        if "outputs (tonne/tonne)" in keys(plant_dict)
+        storage_limit = prod_dict("storage limit (tonne)")
-            output = Dict(
+        disposal_cost = prod_dict("disposal cost (\$/tonne)")
-                prod_name_to_product[key] => value for
+        disposal_limit = prod_dict("disposal limit (tonne)")
-                (key, value) in plant_dict["outputs (tonne/tonne)"] if value > 0
+        initial_capacity = pdict["initial capacity (tonne)"]
-            )
+        capacities = PlantCapacity[]
-        end
+        for cdict in pdict["capacities"]
-
+            size = cdict["size (tonne)"]
-        energy = zeros(T)
+            opening_cost = timeseries(cdict["opening cost (\$)"])
-        emissions = Dict()
+            fix_operating_cost = timeseries(cdict["fixed operating cost (\$)"])
-
+            var_operating_cost = timeseries(cdict["variable operating cost (\$/tonne)"])
-        if "energy (GJ/tonne)" in keys(plant_dict)
-            energy = plant_dict["energy (GJ/tonne)"]
-        end
-
-        if "emissions (tonne/tonne)" in keys(plant_dict)
-            emissions = plant_dict["emissions (tonne/tonne)"]
-        end
-
-        for (location_name, location_dict) in plant_dict["locations"]
-            sizes = PlantSize[]
-            disposal_limit = Dict(p => [0.0 for t = 1:T] for p in keys(output))
-            disposal_cost = Dict(p => [0.0 for t = 1:T] for p in keys(output))
-
-            # Disposal
-            if "disposal" in keys(location_dict)
-                for (product_name, disposal_dict) in location_dict["disposal"]
-                    limit = [1e8 for t = 1:T]
-                    if "limit (tonne)" in keys(disposal_dict)
-                        limit = disposal_dict["limit (tonne)"]
-                    end
-                    disposal_limit[prod_name_to_product[product_name]] = limit
-                    disposal_cost[prod_name_to_product[product_name]] =
-                        disposal_dict["cost (\$/tonne)"]
-                end
-            end
-
-            # Capacities
-            for (capacity_name, capacity_dict) in location_dict["capacities (tonne)"]
             push!(
-                    sizes,
+                capacities,
-                    PlantSize(
+                PlantCapacity(; size, opening_cost, fix_operating_cost, var_operating_cost),
-                        Base.parse(Float64, capacity_name),
-                        capacity_dict["variable operating cost (\$/tonne)"],
-                        capacity_dict["fixed operating cost (\$)"],
-                        capacity_dict["opening cost (\$)"],
-                    ),
             )
         end
-            length(sizes) > 1 || push!(sizes, sizes[1])
-            sort!(sizes, by = x -> x.capacity)
 
-            # Storage
+        # Validate capacity count and duplicate if needed
-            storage_limit = 0
+        if length(capacities) == 0
-            storage_cost = zeros(T)
+            error("Plant '$name' must have at least one capacity defined")
-            if "storage" in keys(location_dict)
+        elseif length(capacities) == 1
-                storage_dict = location_dict["storage"]
+            # Duplicate the single capacity
-                storage_limit = storage_dict["limit (tonne)"]
+            push!(capacities, capacities[1])
-                storage_cost = storage_dict["cost (\$/tonne)"]
+        elseif length(capacities) > 2
+            error(
+                "Plant '$name' cannot have more than 2 capacities, got $(length(capacities))",
+            )
         end
 
-            # Validation: Capacities
+        # Validate capacity sizes are non-decreasing
-            if length(sizes) != 2
+        if capacities[1].size > capacities[2].size
-                throw("At most two capacities are supported")
+            error(
-            end
+                "Plant '$name' capacity sizes must be non-decreasing: $(capacities[1].size) > $(capacities[2].size)",
-            if sizes[1].variable_operating_cost != sizes[2].variable_operating_cost
+            )
-                throw("Variable operating costs must be the same for all capacities")
         end
 
-            plant = Plant(
+        # Validate variable operating costs are the same
-                length(plants) + 1,
+        if capacities[1].var_operating_cost != capacities[2].var_operating_cost
-                plant_name,
+            error(
-                location_name,
+                "Plant '$name' variable operating costs must be the same across all capacities",
-                input,
+            )
+        end
+
+        plant = Plant(;
+            name,
+            latitude,
+            longitude,
+            input_mix,
             output,
-                location_dict["latitude (deg)"],
-                location_dict["longitude (deg)"],
-                disposal_limit,
-                disposal_cost,
-                sizes,
-                energy,
             emissions,
-                storage_limit,
             storage_cost,
+            storage_limit,
+            disposal_cost,
+            disposal_limit,
+            capacities,
+            initial_capacity,
         )
-
         push!(plants, plant)
+        plants_by_name[name] = plant
+    end
+
+    # Read emissions
+    emissions = Emissions[]
+    emissions_by_name = OrderedDict{String,Emissions}()
+    if haskey(json, "emissions")
+        for (name, edict) in json["emissions"]
+            limit = timeseries(edict["limit (tonne)"], null_val = Inf)
+            penalty = timeseries(edict["penalty (\$/tonne)"])
+            emission = Emissions(; name, limit, penalty)
+            push!(emissions, emission)
+            emissions_by_name[name] = emission
         end
     end
 
-    @info @sprintf("%12d collection centers", length(collection_centers))
+    return Instance(;
-    @info @sprintf("%12d candidate plant locations", length(plants))
+        time_horizon,
-
+        building_period,
-    return Instance(T, products, collection_centers, plants, building_period)
+        distance_metric,
+        products,
+        products_by_name,
+        centers,
+        centers_by_name,
+        plants,
+        plants_by_name,
+        emissions,
+        emissions_by_name,
+    )
 end

src/instance/structs.jl

@@ -1,57 +1,75 @@
-# RELOG: Reverse Logistics Optimization
+using OrderedCollections
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
 
-using DataStructures
+abstract type DistanceMetric end
-using JSON
-using JSONSchema
-using Printf
-using Statistics
 
-mutable struct Product
+Base.@kwdef mutable struct KnnDrivingDistance <: DistanceMetric
-    name::String
+    tree = nothing
-    transportation_cost::Vector{Float64}
+    ratios = nothing
-    transportation_energy::Vector{Float64}
-    transportation_emissions::Dict{String,Vector{Float64}}
 end
 
-mutable struct CollectionCenter
+mutable struct EuclideanDistance <: DistanceMetric end
-    index::Int64
+
+Base.@kwdef struct Product
+    name::String
+    tr_cost::Vector{Float64}
+    tr_energy::Vector{Float64}
+    tr_emissions::OrderedDict{String,Vector{Float64}}
+    disposal_limit::Vector{Float64}
+end
+
+Base.@kwdef struct Center
     name::String
     latitude::Float64
     longitude::Float64
-    product::Product
+    input::Union{Product,Nothing}
-    amount::Vector{Float64}
+    outputs::Vector{Product}
+    fixed_output::OrderedDict{Product,Vector{Float64}}
+    var_output::OrderedDict{Product,Vector{Float64}}
+    revenue::Vector{Float64}
+    collection_cost::OrderedDict{Product,Vector{Float64}}
+    operating_cost::Vector{Float64}
+    disposal_limit::OrderedDict{Product,Vector{Float64}}
+    disposal_cost::OrderedDict{Product,Vector{Float64}}
 end
 
-mutable struct PlantSize
+Base.@kwdef struct PlantCapacity
-    capacity::Float64
+    size::Float64
-    variable_operating_cost::Vector{Float64}
-    fixed_operating_cost::Vector{Float64}
     opening_cost::Vector{Float64}
+    fix_operating_cost::Vector{Float64}
+    var_operating_cost::Vector{Float64}
 end
 
-mutable struct Plant
+Base.@kwdef struct Plant
-    index::Int64
+    name::String
-    plant_name::String
-    location_name::String
-    input::Product
-    output::Dict{Product,Float64}
     latitude::Float64
     longitude::Float64
-    disposal_limit::Dict{Product,Vector{Float64}}
+    input_mix::OrderedDict{Product,Vector{Float64}}
-    disposal_cost::Dict{Product,Vector{Float64}}
+    output::OrderedDict{Product,Vector{Float64}}
-    sizes::Vector{PlantSize}
+    emissions::OrderedDict{String,Vector{Float64}}
-    energy::Vector{Float64}
+    storage_cost::OrderedDict{Product,Vector{Float64}}
-    emissions::Dict{String,Vector{Float64}}
+    storage_limit::OrderedDict{Product,Vector{Float64}}
-    storage_limit::Float64
+    disposal_cost::OrderedDict{Product,Vector{Float64}}
-    storage_cost::Vector{Float64}
+    disposal_limit::OrderedDict{Product,Vector{Float64}}
+    capacities::Vector{PlantCapacity}
+    initial_capacity::Float64
 end
 
-mutable struct Instance
+Base.@kwdef struct Emissions
-    time::Int64
+    name::String
-    products::Vector{Product}
+    limit::Vector{Float64}
-    collection_centers::Vector{CollectionCenter}
+    penalty::Vector{Float64}
-    plants::Vector{Plant}
+end
-    building_period::Vector{Int64}
+
+Base.@kwdef struct Instance
+    building_period::Vector{Int}
+    centers_by_name::OrderedDict{String,Center}
+    centers::Vector{Center}
+    distance_metric::DistanceMetric
+    products_by_name::OrderedDict{String,Product}
+    products::Vector{Product}
+    time_horizon::Int
+    plants::Vector{Plant}
+    plants_by_name::OrderedDict{String,Plant}
+    emissions_by_name::OrderedDict{String,Emissions}
+    emissions::Vector{Emissions}
 end

src/instance/validate.jl

@@ -1,25 +0,0 @@
-# RELOG: Reverse Logistics Optimization
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-using DataStructures
-using JSON
-using JSONSchema
-using Printf
-using Statistics
-
-function validate(json, schema)
-    result = JSONSchema.validate(json, schema)
-    if result !== nothing
-        if result isa JSONSchema.SingleIssue
-            path = join(result.path, " → ")
-            if length(path) == 0
-                path = "root"
-            end
-            msg = "$(result.msg) in $(path)"
-        else
-            msg = convert(String, result)
-        end
-        throw(msg)
-    end
-end

src/model/build.jl

@@ -2,249 +2,498 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.
 
-using JuMP, LinearAlgebra, Geodesy, Cbc, Clp, ProgressBars, Printf, DataStructures
+using JuMP
 
-
+function R_expand(p::Plant, t::Int)
-function build_model(instance::Instance, graph::Graph, optimizer)::JuMP.Model
+    denominator = p.capacities[2].size - p.capacities[1].size
-    model = Model(optimizer)
+    if denominator == 0
-    model[:instance] = instance
+        return 0.0
-    model[:graph] = graph
+    end
-    create_vars!(model)
+    return (p.capacities[2].opening_cost[t] - p.capacities[1].opening_cost[t]) / denominator
-    create_objective_function!(model)
-    create_shipping_node_constraints!(model)
-    create_process_node_constraints!(model)
-    return model
 end
 
-
+function R_fix_exp(p::Plant, t::Int)
-function create_vars!(model::JuMP.Model)
+    denominator = p.capacities[2].size - p.capacities[1].size
-    graph, T = model[:graph], model[:instance].time
+    if denominator == 0
-    model[:flow] =
+        return 0.0
-        Dict((a, t) => @variable(model, lower_bound = 0) for a in graph.arcs, t = 1:T)
+    end
-    model[:dispose] = Dict(
+    return (p.capacities[2].fix_operating_cost[t] - p.capacities[1].fix_operating_cost[t]) /
-        (n, t) => @variable(
+           denominator
-            model,
-            lower_bound = 0,
-            upper_bound = n.location.disposal_limit[n.product][t]
-        ) for n in values(graph.plant_shipping_nodes), t = 1:T
-    )
-    model[:store] = Dict(
-        (n, t) =>
-            @variable(model, lower_bound = 0, upper_bound = n.location.storage_limit)
-        for n in values(graph.process_nodes), t = 1:T
-    )
-    model[:process] = Dict(
-        (n, t) => @variable(model, lower_bound = 0) for
-        n in values(graph.process_nodes), t = 1:T
-    )
-    model[:open_plant] = Dict(
-        (n, t) => @variable(model, binary = true) for n in values(graph.process_nodes),
-        t = 1:T
-    )
-    model[:is_open] = Dict(
-        (n, t) => @variable(model, binary = true) for n in values(graph.process_nodes),
-        t = 1:T
-    )
-    model[:capacity] = Dict(
-        (n, t) => @variable(
-            model,
-            lower_bound = 0,
-            upper_bound = n.location.sizes[2].capacity
-        ) for n in values(graph.process_nodes), t = 1:T
-    )
-    model[:expansion] = Dict(
-        (n, t) => @variable(
-            model,
-            lower_bound = 0,
-            upper_bound = n.location.sizes[2].capacity - n.location.sizes[1].capacity
-        ) for n in values(graph.process_nodes), t = 1:T
-    )
 end
 
+function build_model(instance::Instance; optimizer, variable_names::Bool = false)
+    model = JuMP.Model(optimizer)
+    centers = instance.centers
+    products = instance.products
+    plants = instance.plants
+    T = 1:instance.time_horizon
+    model.ext[:instance] = instance
 
-function slope_open(plant, t)
+    # Constants
-    if plant.sizes[2].capacity <= plant.sizes[1].capacity
+    # -------------------------------------------------------------------------
-        0.0
+    K_cap_min = Dict(p => p.capacities[1].size for p in plants)
-    else
+    K_cap_max = Dict(p => p.capacities[2].size for p in plants)
-        (plant.sizes[2].opening_cost[t] - plant.sizes[1].opening_cost[t]) /
+    R_open = Dict((p, t) => p.capacities[1].opening_cost[t] for p in plants for t in T)
-        (plant.sizes[2].capacity - plant.sizes[1].capacity)
+    R_fix_min =
-    end
+        Dict((p, t) => p.capacities[1].fix_operating_cost[t] for p in plants for t in T)
-end
 
-function slope_fix_oper_cost(plant, t)
-    if plant.sizes[2].capacity <= plant.sizes[1].capacity
-        0.0
-    else
-        (plant.sizes[2].fixed_operating_cost[t] - plant.sizes[1].fixed_operating_cost[t]) /
-        (plant.sizes[2].capacity - plant.sizes[1].capacity)
-    end
-end
 
-function create_objective_function!(model::JuMP.Model)
+    # Transportation edges
-    graph, T = model[:graph], model[:instance].time
+    # -------------------------------------------------------------------------
-    obj = AffExpr(0.0)
 
-    # Process node costs
+    # Connectivity
-    for n in values(graph.process_nodes), t = 1:T
+    model.ext[:E] = E = []
+    model.ext[:E_in] = E_in = Dict(src => [] for src in plants ∪ centers)
+    model.ext[:E_out] = E_out = Dict(src => [] for src in plants ∪ centers)
 
-        # Transportation and variable operating costs
+    function push_edge!(src, dst, m)
-        for a in n.incoming_arcs
+        push!(E, (src, dst, m))
-            c = n.location.input.transportation_cost[t] * a.values["distance"]
+        push!(E_out[src], (dst, m))
-            add_to_expression!(obj, c, model[:flow][a, t])
+        push!(E_in[dst], (src, m))
     end
 
-        # Opening costs
+    for m in products
-        add_to_expression!(
+        for p1 in plants
-            obj,
+            m ∈ keys(p1.output) || continue
-            n.location.sizes[1].opening_cost[t],
-            model[:open_plant][n, t],
-        )
 
-        # Fixed operating costs (base)
+            # Plant to plant
-        add_to_expression!(
+            for p2 in plants
-            obj,
+                p1 != p2 || continue
-            n.location.sizes[1].fixed_operating_cost[t],
+                m ∈ keys(p2.input_mix) || continue
-            model[:is_open][n, t],
+                push_edge!(p1, p2, m)
-        )
+            end
 
-        # Fixed operating costs (expansion)
+            # Plant to center
-        add_to_expression!(obj, slope_fix_oper_cost(n.location, t), model[:expansion][n, t])
+            for c in centers
-
+                m == c.input || continue
-        # Processing costs
+                push_edge!(p1, c, m)
-        add_to_expression!(
-            obj,
-            n.location.sizes[1].variable_operating_cost[t],
-            model[:process][n, t],
-        )
-
-        # Storage costs
-        add_to_expression!(obj, n.location.storage_cost[t], model[:store][n, t])
-
-        # Expansion costs
-        if t < T
-            add_to_expression!(
-                obj,
-                slope_open(n.location, t) - slope_open(n.location, t + 1),
-                model[:expansion][n, t],
-            )
-        else
-            add_to_expression!(obj, slope_open(n.location, t), model[:expansion][n, t])
             end
         end
 
-    # Shipping node costs
+        for c1 in centers
-    for n in values(graph.plant_shipping_nodes), t = 1:T
+            m ∈ c1.outputs || continue
 
-        # Disposal costs
+            # Center to plant
+            for p in plants
+                m ∈ keys(p.input_mix) || continue
+                push_edge!(c1, p, m)
+            end
+
+            # Center to center
+            for c2 in centers
+                m == c2.input || continue
+                push_edge!(c1, c2, m)
+            end
+        end
+    end
+
+    # Distances
+    model.ext[:distances] = distances = Dict()
+    for (p1, p2, m) in E
+        d = _calculate_distance(
+            p1.latitude,
+            p1.longitude,
+            p2.latitude,
+            p2.longitude,
+            instance.distance_metric,
+        )
+        distances[p1, p2, m] = d
+    end
+
+    # Decision variables
+    # -------------------------------------------------------------------------
+
+    # Plant p is operational at time t
+    x = _init(model, :x)
+    for p in plants
+        x[p.name, 0] = p.initial_capacity > 0 ? 1 : 0
+    end
+    for p in plants, t in T
+        x[p.name, t] = @variable(model, binary = true)
+    end
+
+    # Amount of product m sent from center/plant u to center/plant v at time T
+    y = _init(model, :y)
+    for (p1, p2, m) in E, t in T
+        y[p1.name, p2.name, m.name, t] = @variable(model, lower_bound = 0)
+    end
+
+    # Amount of product m produced by plant/center at time T
+    z_prod = _init(model, :z_prod)
+    for p in plants, m in keys(p.output), t in T
+        z_prod[p.name, m.name, t] = @variable(model, lower_bound = 0)
+    end
+
+    # Amount of product m disposed at plant/center p at time T
+    z_disp = _init(model, :z_disp)
+    for p in plants, m in keys(p.output), t in T
+        z_disp[p.name, m.name, t] = @variable(model, lower_bound = 0)
+    end
+    for c in centers, m in c.outputs, t in T
+        z_disp[c.name, m.name, t] = @variable(model, lower_bound = 0)
+    end
+
+    # Total plant/center input
+    z_input = _init(model, :z_input)
+    for p in plants, t in T
+        z_input[p.name, t] = @variable(model, lower_bound = 0)
+    end
+    for c in centers, t in T
+        z_input[c.name, t] = @variable(model, lower_bound = 0)
+    end
+
+    # Plant expansion
+    z_exp = _init(model, :z_exp)
+    for p in plants
+        z_exp[p.name, 0] = max(0, p.initial_capacity - K_cap_min[p])
+    end
+    for p in plants, t in T
+        z_exp[p.name, t] = @variable(model, lower_bound = 0)
+    end
+
+    # Total amount collected by the center
+    z_collected = _init(model, :z_collected)
+    for c in centers, m in c.outputs, t in T
+        z_collected[c.name, m.name, t] = @variable(model, lower_bound = 0)
+    end
+
+    # Amount of input material stored at plant at end of time period
+    z_storage = _init(model, :z_storage)
+    for p in plants
+        for m in keys(p.input_mix)
+            z_storage[p.name, m.name, 0] = 0  # Initial storage is zero
+        end
+    end
+    for p in plants, m in keys(p.input_mix), t in T
+        z_storage[p.name, m.name, t] = @variable(model, lower_bound = 0)
+    end
+
+    # Total amount of input material processed by plant
+    z_process = _init(model, :z_process)
+    for p in plants, t in T
+        z_process[p.name, t] = @variable(model, lower_bound = 0)
+    end
+
+    # Transportation emissions by greenhouse gas
+    z_em_tr = _init(model, :z_em_tr)
+    for (p1, p2, m) in E, t in T, g in keys(m.tr_emissions)
+        z_em_tr[g, p1.name, p2.name, m.name, t] = @variable(model, lower_bound = 0)
+    end
+
+    # Plant emissions by greenhouse gas
+    z_em_plant = _init(model, :z_em_plant)
+    for p in plants, t in T, g in keys(p.emissions)
+        z_em_plant[g, p.name, t] = @variable(model, lower_bound = 0)
+    end
+
+
+    # Objective function
+    # -------------------------------------------------------------------------
+    obj = AffExpr()
+
+    # Transportation cost
+    for (p1, p2, m) in E, t in T
         add_to_expression!(
             obj,
-            n.location.disposal_cost[n.product][t],
+            distances[p1, p2, m] * m.tr_cost[t],
-            model[:dispose][n, t],
+            y[p1.name, p2.name, m.name, t],
         )
     end
 
+    # Center: Revenue
+    for c in centers, (p, m) in E_in[c], t in T
+        add_to_expression!(obj, -c.revenue[t], y[p.name, c.name, m.name, t])
+    end
+
+    # Center: Collection cost
+    for c in centers, (p, m) in E_out[c], t in T
+        add_to_expression!(obj, c.collection_cost[m][t], y[c.name, p.name, m.name, t])
+    end
+
+    # Center: Disposal cost
+    for c in centers, m in c.outputs, t in T
+        add_to_expression!(obj, c.disposal_cost[m][t], z_disp[c.name, m.name, t])
+    end
+
+    # Center: Operating cost
+    for c in centers, t in T
+        add_to_expression!(obj, c.operating_cost[t])
+    end
+
+    # Plants: Disposal cost
+    for p in plants, m in keys(p.output), t in T
+        add_to_expression!(obj, p.disposal_cost[m][t], z_disp[p.name, m.name, t])
+    end
+
+    # Plants: Opening cost
+    for p in plants, t in T
+        add_to_expression!(obj, R_open[p, t], (x[p.name, t] - x[p.name, t-1]))
+    end
+
+    # Plants: Fixed operating cost
+    for p in plants, t in T
+        add_to_expression!(obj, R_fix_min[p, t], x[p.name, t])
+        add_to_expression!(obj, R_fix_exp(p, t), z_exp[p.name, t])
+    end
+
+    # Plants: Expansion cost
+    for p in plants, t in T
+        add_to_expression!(obj, R_expand(p, t), z_exp[p.name, t] - z_exp[p.name, t-1])
+    end
+
+    # Plants: Variable operating cost
+    for p in plants, (src, m) in E_in[p], t in T
+        add_to_expression!(
+            obj,
+            p.capacities[1].var_operating_cost[t],
+            y[src.name, p.name, m.name, t],
+        )
+    end
+
+    # Plants: Storage cost
+    for p in plants, m in keys(p.storage_cost), t in T
+        add_to_expression!(obj, p.storage_cost[m][t], z_storage[p.name, m.name, t])
+    end
+
+    # Emissions penalty cost
+    for emission in instance.emissions, t in T
+        # Plant emissions penalty
+        for p in plants
+            if emission.name in keys(p.emissions)
+                add_to_expression!(
+                    obj,
+                    emission.penalty[t],
+                    z_em_plant[emission.name, p.name, t],
+                )
+            end
+        end
+        # Transportation emissions penalty
+        for (p1, p2, m) in E
+            if emission.name in keys(m.tr_emissions)
+                add_to_expression!(
+                    obj,
+                    emission.penalty[t],
+                    z_em_tr[emission.name, p1.name, p2.name, m.name, t],
+                )
+            end
+        end
+    end
+
     @objective(model, Min, obj)
-end
+
-
+    # Constraints
-
+    # -------------------------------------------------------------------------
-function create_shipping_node_constraints!(model::JuMP.Model)
+
-    graph, T = model[:graph], model[:instance].time
+    # Plants: Definition of total plant input
-    model[:eq_balance] = OrderedDict()
+    eq_z_input = _init(model, :eq_z_input)
-    for t = 1:T
+    for p in plants, t in T
-        # Collection centers
+        eq_z_input[p.name, t] = @constraint(
-        for n in graph.collection_shipping_nodes
+            model,
-            model[:eq_balance][n, t] = @constraint(
+            z_input[p.name, t] ==
-                model,
+            sum(y[src.name, p.name, m.name, t] for (src, m) in E_in[p])
-                sum(model[:flow][a, t] for a in n.outgoing_arcs) == n.location.amount[t]
+        )
-            )
+    end
-        end
+
-
+    # Plants: Definition of total processing amount
-        # Plants
+    eq_z_process = _init(model, :eq_z_process)
-        for n in graph.plant_shipping_nodes
+    for p in plants, t in T
-            @constraint(
+        eq_z_process[p.name, t] = @constraint(
-                model,
+            model,
-                sum(model[:flow][a, t] for a in n.incoming_arcs) ==
+            z_process[p.name, t] ==
-                sum(model[:flow][a, t] for a in n.outgoing_arcs) + model[:dispose][n, t]
+            z_input[p.name, t] + sum(
-            )
+                z_storage[p.name, m.name, t-1] - z_storage[p.name, m.name, t] for
-        end
+                m in keys(p.input_mix)
-    end
+            )
-
+        )
-end
+    end
-
+
-
+    # Plants: Processing mix must have correct proportion
-function create_process_node_constraints!(model::JuMP.Model)
+    eq_process_mix = _init(model, :eq_process_mix)
-    graph, T = model[:graph], model[:instance].time
+    for p in plants, m in keys(p.input_mix), t in T
-
+        eq_process_mix[p.name, m.name, t] = @constraint(
-    for t = 1:T, n in graph.process_nodes
+            model,
-        input_sum = AffExpr(0.0)
+            sum(y[src.name, p.name, m.name, t] for (src, m2) in E_in[p] if m == m2) +
-        for a in n.incoming_arcs
+            z_storage[p.name, m.name, t-1] - z_storage[p.name, m.name, t] ==
-            add_to_expression!(input_sum, 1.0, model[:flow][a, t])
+            z_process[p.name, t] * p.input_mix[m][t]
-        end
+        )
-
+    end
-        # Output amount is implied by amount processed
+
-        for a in n.outgoing_arcs
+    # Plants: Calculate amount produced
-            @constraint(
+    eq_z_prod = _init(model, :eq_z_prod)
-                model,
+    for p in plants, m in keys(p.output), t in T
-                model[:flow][a, t] == a.values["weight"] * model[:process][n, t]
+        eq_z_prod[p.name, m.name, t] = @constraint(
-            )
+            model,
-        end
+            z_prod[p.name, m.name, t] == z_process[p.name, t] * p.output[m][t]
-
+        )
-        # If plant is closed, capacity is zero
+    end
-        @constraint(
+
-            model,
+    # Plants: Produced material must be sent or disposed
-            model[:capacity][n, t] <= n.location.sizes[2].capacity * model[:is_open][n, t]
+    eq_balance = _init(model, :eq_balance)
-        )
+    for p in plants, m in keys(p.output), t in T
-
+        eq_balance[p.name, m.name, t] = @constraint(
-        # If plant is open, capacity is greater than base
+            model,
-        @constraint(
+            z_prod[p.name, m.name, t] ==
-            model,
+            sum(y[p.name, dst.name, m.name, t] for (dst, m2) in E_out[p] if m == m2) +
-            model[:capacity][n, t] >= n.location.sizes[1].capacity * model[:is_open][n, t]
+            z_disp[p.name, m.name, t]
-        )
+        )
-
+    end
-        # Capacity is linked to expansion
+
-        @constraint(
+    # Plants: Expansion upper bound
-            model,
+    eq_exp_ub = _init(model, :eq_exp_ub)
-            model[:capacity][n, t] <=
+    for p in plants, t in T
-            n.location.sizes[1].capacity + model[:expansion][n, t]
+        eq_exp_ub[p.name, t] = @constraint(
-        )
+            model,
-
+            z_exp[p.name, t] <= (K_cap_max[p] - K_cap_min[p]) * x[p.name, t]
-        # Can only process up to capacity
+        )
-        @constraint(model, model[:process][n, t] <= model[:capacity][n, t])
+    end
-
+
-        if t > 1
+    # Plants: Processing limit
-            # Plant capacity can only increase over time
+    eq_process_limit = _init(model, :eq_process_limit)
-            @constraint(model, model[:capacity][n, t] >= model[:capacity][n, t-1])
+    for p in plants, t in T
-            @constraint(model, model[:expansion][n, t] >= model[:expansion][n, t-1])
+        eq_process_limit[p.name, t] = @constraint(
-        end
+            model,
-
+            z_process[p.name, t] <= K_cap_min[p] * x[p.name, t] + z_exp[p.name, t]
-        # Amount received equals amount processed plus stored
+        )
-        store_in = 0
+    end
-        if t > 1
+
-            store_in = model[:store][n, t-1]
+    # Plants: Disposal limit
-        end
+    eq_disposal_limit = _init(model, :eq_disposal_limit)
-        if t == T
+    for p in plants, m in keys(p.output), t in T
-            @constraint(model, model[:store][n, t] == 0)
+        isfinite(p.disposal_limit[m][t]) || continue
-        end
+        eq_disposal_limit[p.name, m.name, t] =
-        @constraint(
+            @constraint(model, z_disp[p.name, m.name, t] <= p.disposal_limit[m][t])
-            model,
+    end
-            input_sum + store_in == model[:store][n, t] + model[:process][n, t]
+
-        )
+    # Plants: Plant remains open
-
+    eq_keep_open = _init(model, :eq_keep_open)
-
+    for p in plants, t in T
-        # Plant is currently open if it was already open in the previous time period or
+        eq_keep_open[p.name, t] = @constraint(model, x[p.name, t] >= x[p.name, t-1])
-        # if it was built just now
+    end
-        if t > 1
+
-            @constraint(
+    # Plants: Capacity cannot decrease over time
-                model,
+    eq_capacity_nondecreasing = _init(model, :eq_capacity_nondecreasing)
-                model[:is_open][n, t] == model[:is_open][n, t-1] + model[:open_plant][n, t]
+    for p in plants, t in T
-            )
+        eq_capacity_nondecreasing[p.name, t] =
-        else
+            @constraint(model, z_exp[p.name, t] >= z_exp[p.name, t-1])
-            @constraint(model, model[:is_open][n, t] == model[:open_plant][n, t])
+    end
-        end
+
-
+    # Plants: Building period
-        # Plant can only be opened during building period
+    eq_building_period = _init(model, :eq_building_period)
-        if t ∉ model[:instance].building_period
+    for p in plants, t in T
-            @constraint(model, model[:open_plant][n, t] == 0)
+        if t ∉ instance.building_period
-        end
+            eq_building_period[p.name, t] =
-    end
+                @constraint(model, x[p.name, t] - x[p.name, t-1] <= 0)
+        end
+    end
+
+    # Centers: Definition of total center input
+    eq_z_input = _init(model, :eq_z_input)
+    for c in centers, t in T
+        eq_z_input[c.name, t] = @constraint(
+            model,
+            z_input[c.name, t] ==
+            sum(y[src.name, c.name, m.name, t] for (src, m) in E_in[c])
+        )
+    end
+
+    # Centers: Calculate amount collected
+    eq_z_collected = _init(model, :eq_z_collected)
+    for c in centers, m in c.outputs, t in T
+        M = length(c.var_output[m])
+        eq_z_collected[c.name, m.name, t] = @constraint(
+            model,
+            z_collected[c.name, m.name, t] ==
+            sum(
+                z_input[c.name, t-offset] * c.var_output[m][offset+1] for
+                offset = 0:min(M-1, t-1)
+            ) + c.fixed_output[m][t]
+        )
+    end
+
+    # Centers: Collected products must be disposed or sent
+    eq_balance = _init(model, :eq_balance)
+    for c in centers, m in c.outputs, t in T
+        eq_balance[c.name, m.name, t] = @constraint(
+            model,
+            z_collected[c.name, m.name, t] ==
+            sum(y[c.name, dst.name, m.name, t] for (dst, m2) in E_out[c] if m == m2) +
+            z_disp[c.name, m.name, t]
+        )
+    end
+
+    # Centers: Disposal limit
+    eq_disposal_limit = _init(model, :eq_disposal_limit)
+    for c in centers, m in c.outputs, t in T
+        isfinite(c.disposal_limit[m][t]) || continue
+        eq_disposal_limit[c.name, m.name, t] =
+            @constraint(model, z_disp[c.name, m.name, t] <= c.disposal_limit[m][t])
+    end
+
+    # Global disposal limit
+    eq_disposal_limit = _init(model, :eq_disposal_limit)
+    for m in products, t in T
+        isfinite(m.disposal_limit[t]) || continue
+        eq_disposal_limit[m.name, t] = @constraint(
+            model,
+            sum(z_disp[p.name, m.name, t] for p in plants if m in keys(p.output)) +
+            sum(z_disp[c.name, m.name, t] for c in centers if m in c.outputs) <=
+            m.disposal_limit[t]
+        )
+    end
+
+    # Transportation emissions
+    eq_emission_tr = _init(model, :eq_emission_tr)
+    for (p1, p2, m) in E, t in T, g in keys(m.tr_emissions)
+        eq_emission_tr[g, p1.name, p2.name, m.name, t] = @constraint(
+            model,
+            z_em_tr[g, p1.name, p2.name, m.name, t] ==
+            distances[p1, p2, m] * m.tr_emissions[g][t] * y[p1.name, p2.name, m.name, t]
+        )
+    end
+
+    # Plant emissions
+    eq_emission_plant = _init(model, :eq_emission_plant)
+    for p in plants, t in T, g in keys(p.emissions)
+        eq_emission_plant[g, p.name, t] = @constraint(
+            model,
+            z_em_plant[g, p.name, t] == p.emissions[g][t] * z_process[p.name, t]
+        )
+    end
+
+    # Storage limit at plants
+    eq_storage_limit = _init(model, :eq_storage_limit)
+    for p in plants, m in keys(p.storage_limit), t in T
+        if isfinite(p.storage_limit[m][t])
+            eq_storage_limit[p.name, m.name, t] =
+                @constraint(model, z_storage[p.name, m.name, t] <= p.storage_limit[m][t])
+        end
+    end
+
+    # All stored materials must be processed by end of time horizon
+    eq_storage_final = _init(model, :eq_storage_final)
+    for p in plants, m in keys(p.input_mix)
+        eq_storage_final[p.name, m.name] =
+            @constraint(model, z_storage[p.name, m.name, instance.time_horizon] == 0)
+    end
+
+    # Global emissions limit
+    eq_emission_limit = _init(model, :eq_emission_limit)
+    for emission in instance.emissions, t in T
+        isfinite(emission.limit[t]) || continue
+        eq_emission_limit[emission.name, t] = @constraint(
+            model,
+            sum(
+                z_em_plant[emission.name, p.name, t] for
+                p in plants if emission.name in keys(p.emissions)
+            ) + sum(
+                z_em_tr[emission.name, p1.name, p2.name, m.name, t] for
+                (p1, p2, m) in E if emission.name in keys(m.tr_emissions)
+            ) <= emission.limit[t]
+        )
+    end
+
+    if variable_names
+        _set_names!(model)
+    end
+    return model
 end

src/model/dist.jl

@@ -0,0 +1,110 @@
+# RELOG: Reverse Logistics Optimization
+# Copyright (C) 2020-2025, UChicago Argonne, LLC. All rights reserved.
+# Released under the modified BSD license. See COPYING.md for more details.
+
+using Geodesy
+using NearestNeighbors
+using DataFrames
+using CRC
+using ZipFile
+using Statistics
+using TimerOutputs
+
+crc32 = crc(CRC_32)
+
+function _calculate_distance(
+    source_lat,
+    source_lon,
+    dest_lat,
+    dest_lon,
+    ::EuclideanDistance,
+)::Float64
+    x = LLA(source_lat, source_lon, 0.0)
+    y = LLA(dest_lat, dest_lon, 0.0)
+    return round(euclidean_distance(x, y) / 1000.0, digits = 3)
+end
+
+function _download_file(url, output, expected_crc32)::Nothing
+    if isfile(output)
+        return
+    end
+    mkpath(dirname(output))
+    @info "Downloading: $url"
+    fname = download(url)
+    actual_crc32 = open(crc32, fname)
+    expected_crc32 == actual_crc32 || error("CRC32 mismatch")
+    cp(fname, output)
+    return
+end
+
+function _download_zip(url, outputdir, expected_output_file, expected_crc32)::Nothing
+    if isfile(expected_output_file)
+        return
+    end
+    mkpath(outputdir)
+    @info "Downloading: $url"
+    zip_filename = download(url)
+    actual_crc32 = open(crc32, zip_filename)
+    expected_crc32 == actual_crc32 || error("CRC32 mismatch")
+    open(zip_filename) do zip_file
+        zr = ZipFile.Reader(zip_file)
+        for file in zr.files
+            open(joinpath(outputdir, file.name), "w") do output_file
+                write(output_file, read(file))
+            end
+        end
+    end
+    return
+end
+
+function _calculate_distance(
+    source_lat,
+    source_lon,
+    dest_lat,
+    dest_lon,
+    metric::KnnDrivingDistance,
+)::Float64
+    if metric.tree === nothing
+        basedir = joinpath(dirname(@__FILE__), "data")
+        csv_filename = joinpath(basedir, "dist_driving.csv")
+
+        # Download pre-computed driving data
+        @timeit "Download data" begin
+            if !isfile(csv_filename)
+                _download_zip(
+                    "https://axavier.org/RELOG/0.6/data/dist_driving_0b9a6ad6.zip",
+                    basedir,
+                    csv_filename,
+                    0x0b9a6ad6,
+                )
+            end
+        end
+
+        @timeit "Fit KNN model" begin
+            df = DataFrame(CSV.File(csv_filename, missingstring = "NaN"))
+            dropmissing!(df)
+            coords = Matrix(df[!, [:source_lat, :source_lon, :dest_lat, :dest_lon]])'
+            metric.ratios = Matrix(df[!, [:ratio]])
+            metric.tree = KDTree(coords)
+        end
+    end
+
+    @timeit "Compute Euclidean distance" begin
+        dist_euclidean = _calculate_distance(
+            source_lat,
+            source_lon,
+            dest_lat,
+            dest_lon,
+            EuclideanDistance(),
+        )
+    end
+
+    @timeit "Predict driving distance" begin
+        idxs, _ = knn(metric.tree, [source_lat, source_lon, dest_lat, dest_lon], 5)
+        ratio_pred = mean(metric.ratios[idxs])
+        dist_pred = round(dist_euclidean * ratio_pred, digits = 3)
+        isfinite(dist_pred) || error("non-finite distance detected: $dist_pred")
+    end
+
+    return dist_pred
+end

src/model/getsol.jl

@@ -1,224 +0,0 @@
-# RELOG: Reverse Logistics Optimization
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-using JuMP, LinearAlgebra, Geodesy, Cbc, Clp, ProgressBars, Printf, DataStructures
-
-function get_solution(model::JuMP.Model; marginal_costs = true)
-    graph, instance = model[:graph], model[:instance]
-    T = instance.time
-
-    output = OrderedDict(
-        "Plants" => OrderedDict(),
-        "Products" => OrderedDict(),
-        "Costs" => OrderedDict(
-            "Fixed operating (\$)" => zeros(T),
-            "Variable operating (\$)" => zeros(T),
-            "Opening (\$)" => zeros(T),
-            "Transportation (\$)" => zeros(T),
-            "Disposal (\$)" => zeros(T),
-            "Expansion (\$)" => zeros(T),
-            "Storage (\$)" => zeros(T),
-            "Total (\$)" => zeros(T),
-        ),
-        "Energy" =>
-            OrderedDict("Plants (GJ)" => zeros(T), "Transportation (GJ)" => zeros(T)),
-        "Emissions" => OrderedDict(
-            "Plants (tonne)" => OrderedDict(),
-            "Transportation (tonne)" => OrderedDict(),
-        ),
-    )
-
-    plant_to_process_node = OrderedDict(n.location => n for n in graph.process_nodes)
-    plant_to_shipping_nodes = OrderedDict()
-    for p in instance.plants
-        plant_to_shipping_nodes[p] = []
-        for a in plant_to_process_node[p].outgoing_arcs
-            push!(plant_to_shipping_nodes[p], a.dest)
-        end
-    end
-
-    # Products
-    if marginal_costs
-        for n in graph.collection_shipping_nodes
-            location_dict = OrderedDict{Any,Any}(
-                "Marginal cost (\$/tonne)" => [
-                    round(abs(JuMP.shadow_price(model[:eq_balance][n, t])), digits = 2) for t = 1:T
-                ],
-            )
-            if n.product.name ∉ keys(output["Products"])
-                output["Products"][n.product.name] = OrderedDict()
-            end
-            output["Products"][n.product.name][n.location.name] = location_dict
-        end
-    end
-
-    # Plants
-    for plant in instance.plants
-        skip_plant = true
-        process_node = plant_to_process_node[plant]
-        plant_dict = OrderedDict{Any,Any}(
-            "Input" => OrderedDict(),
-            "Output" =>
-                OrderedDict("Send" => OrderedDict(), "Dispose" => OrderedDict()),
-            "Input product" => plant.input.name,
-            "Total input (tonne)" => [0.0 for t = 1:T],
-            "Total output" => OrderedDict(),
-            "Latitude (deg)" => plant.latitude,
-            "Longitude (deg)" => plant.longitude,
-            "Capacity (tonne)" =>
-                [JuMP.value(model[:capacity][process_node, t]) for t = 1:T],
-            "Opening cost (\$)" => [
-                JuMP.value(model[:open_plant][process_node, t]) *
-                plant.sizes[1].opening_cost[t] for t = 1:T
-            ],
-            "Fixed operating cost (\$)" => [
-                JuMP.value(model[:is_open][process_node, t]) *
-                plant.sizes[1].fixed_operating_cost[t] +
-                JuMP.value(model[:expansion][process_node, t]) *
-                slope_fix_oper_cost(plant, t) for t = 1:T
-            ],
-            "Expansion cost (\$)" => [
-                (
-                    if t == 1
-                        slope_open(plant, t) * JuMP.value(model[:expansion][process_node, t])
-                    else
-                        slope_open(plant, t) * (
-                            JuMP.value(model[:expansion][process_node, t]) -
-                            JuMP.value(model[:expansion][process_node, t-1])
-                        )
-                    end
-                ) for t = 1:T
-            ],
-            "Process (tonne)" =>
-                [JuMP.value(model[:process][process_node, t]) for t = 1:T],
-            "Variable operating cost (\$)" => [
-                JuMP.value(model[:process][process_node, t]) *
-                plant.sizes[1].variable_operating_cost[t] for t = 1:T
-            ],
-            "Storage (tonne)" =>
-                [JuMP.value(model[:store][process_node, t]) for t = 1:T],
-            "Storage cost (\$)" => [
-                JuMP.value(model[:store][process_node, t]) * plant.storage_cost[t]
-                for t = 1:T
-            ],
-        )
-        output["Costs"]["Fixed operating (\$)"] += plant_dict["Fixed operating cost (\$)"]
-        output["Costs"]["Variable operating (\$)"] +=
-            plant_dict["Variable operating cost (\$)"]
-        output["Costs"]["Opening (\$)"] += plant_dict["Opening cost (\$)"]
-        output["Costs"]["Expansion (\$)"] += plant_dict["Expansion cost (\$)"]
-        output["Costs"]["Storage (\$)"] += plant_dict["Storage cost (\$)"]
-
-        # Inputs
-        for a in process_node.incoming_arcs
-            vals = [JuMP.value(model[:flow][a, t]) for t = 1:T]
-            if sum(vals) <= 1e-3
-                continue
-            end
-            skip_plant = false
-            dict = OrderedDict{Any,Any}(
-                "Amount (tonne)" => vals,
-                "Distance (km)" => a.values["distance"],
-                "Latitude (deg)" => a.source.location.latitude,
-                "Longitude (deg)" => a.source.location.longitude,
-                "Transportation cost (\$)" =>
-                    a.source.product.transportation_cost .* vals .* a.values["distance"],
-                "Transportation energy (J)" =>
-                    vals .* a.values["distance"] .* a.source.product.transportation_energy,
-                "Emissions (tonne)" => OrderedDict(),
-            )
-            emissions_dict = output["Emissions"]["Transportation (tonne)"]
-            for (em_name, em_values) in a.source.product.transportation_emissions
-                dict["Emissions (tonne)"][em_name] =
-                    em_values .* dict["Amount (tonne)"] .* a.values["distance"]
-                if em_name ∉ keys(emissions_dict)
-                    emissions_dict[em_name] = zeros(T)
-                end
-                emissions_dict[em_name] += dict["Emissions (tonne)"][em_name]
-            end
-            if a.source.location isa CollectionCenter
-                plant_name = "Origin"
-                location_name = a.source.location.name
-            else
-                plant_name = a.source.location.plant_name
-                location_name = a.source.location.location_name
-            end
-
-            if plant_name ∉ keys(plant_dict["Input"])
-                plant_dict["Input"][plant_name] = OrderedDict()
-            end
-            plant_dict["Input"][plant_name][location_name] = dict
-            plant_dict["Total input (tonne)"] += vals
-            output["Costs"]["Transportation (\$)"] += dict["Transportation cost (\$)"]
-            output["Energy"]["Transportation (GJ)"] +=
-                dict["Transportation energy (J)"] / 1e9
-        end
-
-        plant_dict["Energy (GJ)"] = plant_dict["Total input (tonne)"] .* plant.energy
-        output["Energy"]["Plants (GJ)"] += plant_dict["Energy (GJ)"]
-
-        plant_dict["Emissions (tonne)"] = OrderedDict()
-        emissions_dict = output["Emissions"]["Plants (tonne)"]
-        for (em_name, em_values) in plant.emissions
-            plant_dict["Emissions (tonne)"][em_name] =
-                em_values .* plant_dict["Total input (tonne)"]
-            if em_name ∉ keys(emissions_dict)
-                emissions_dict[em_name] = zeros(T)
-            end
-            emissions_dict[em_name] += plant_dict["Emissions (tonne)"][em_name]
-        end
-
-        # Outputs
-        for shipping_node in plant_to_shipping_nodes[plant]
-            product_name = shipping_node.product.name
-            plant_dict["Total output"][product_name] = zeros(T)
-            plant_dict["Output"]["Send"][product_name] = product_dict = OrderedDict()
-
-            disposal_amount = [JuMP.value(model[:dispose][shipping_node, t]) for t = 1:T]
-            if sum(disposal_amount) > 1e-5
-                skip_plant = false
-                plant_dict["Output"]["Dispose"][product_name] =
-                    disposal_dict = OrderedDict()
-                disposal_dict["Amount (tonne)"] =
-                    [JuMP.value(model[:dispose][shipping_node, t]) for t = 1:T]
-                disposal_dict["Cost (\$)"] = [
-                    disposal_dict["Amount (tonne)"][t] *
-                    plant.disposal_cost[shipping_node.product][t] for t = 1:T
-                ]
-                plant_dict["Total output"][product_name] += disposal_amount
-                output["Costs"]["Disposal (\$)"] += disposal_dict["Cost (\$)"]
-            end
-
-            for a in shipping_node.outgoing_arcs
-                vals = [JuMP.value(model[:flow][a, t]) for t = 1:T]
-                if sum(vals) <= 1e-3
-                    continue
-                end
-                skip_plant = false
-                dict = OrderedDict(
-                    "Amount (tonne)" => vals,
-                    "Distance (km)" => a.values["distance"],
-                    "Latitude (deg)" => a.dest.location.latitude,
-                    "Longitude (deg)" => a.dest.location.longitude,
-                )
-                if a.dest.location.plant_name ∉ keys(product_dict)
-                    product_dict[a.dest.location.plant_name] = OrderedDict()
-                end
-                product_dict[a.dest.location.plant_name][a.dest.location.location_name] =
-                    dict
-                plant_dict["Total output"][product_name] += vals
-            end
-        end
-
-        if !skip_plant
-            if plant.plant_name ∉ keys(output["Plants"])
-                output["Plants"][plant.plant_name] = OrderedDict()
-            end
-            output["Plants"][plant.plant_name][plant.location_name] = plant_dict
-        end
-    end
-
-    output["Costs"]["Total (\$)"] = sum(values(output["Costs"]))
-    return output
-end

src/model/jumpext.jl

@@ -0,0 +1,120 @@
+# This file extends some JuMP functions so that decision variables can be safely
+# replaced by (constant) floating point numbers.
+
+using Printf
+using JuMP
+
+import JuMP: value, fix, set_name
+
+function value(x::Float64)
+    return x
+end
+
+function fix(x::Float64, v::Float64; force)
+    return abs(x - v) < 1e-6 || error("Value mismatch: $x != $v")
+end
+
+function set_name(::Number, ::String)
+    # nop
+end
+
+function _init(model::JuMP.Model, key::Symbol)::OrderedDict
+    if !(key in keys(object_dictionary(model)))
+        model[key] = OrderedDict()
+    end
+    return model[key]
+end
+
+function _set_names!(model::JuMP.Model)
+    @info "Setting variable and constraint names..."
+    time_varnames = @elapsed begin
+        _set_names!(object_dictionary(model))
+    end
+    @info @sprintf("Set names in %.2f seconds", time_varnames)
+end
+
+function _set_names!(dict::Dict)
+    for name in keys(dict)
+        dict[name] isa AbstractDict || continue
+        for idx in keys(dict[name])
+            if dict[name][idx] isa AffExpr
+                continue
+            end
+            idx_str = join(map(string, idx), ",")
+            set_name(dict[name][idx], "$name[$idx_str]")
+        end
+    end
+end
+
+
+"""
+    _add_pwl_constraints(model, xvar, yvars, xpts, ypts)
+
+Add piecewise-linear constraints to a JuMP model for multiple y variables.
+
+Creates constraints y_i = f_i(x) where each f_i is a piecewise-linear function 
+defined by the breakpoints (xpts, ypts[:, i]).
+
+# Arguments
+- `model`: JuMP model
+- `xvar`: The x variable (JuMP variable)
+- `yvars`: Vector of y variables (JuMP variables)  
+- `xpts`: Vector of x values for breakpoints (must be in non-decreasing order)
+- `ypts`: Matrix of y values where ypts[i, j] is the y value for the j-th variable 
+         at the i-th breakpoint
+
+# Example
+```julia
+@variable(model, y1)
+@variable(model, y2)
+ypts_matrix = [1.5 2.0; 0.0 1.5; 3.0 0.5]  # 3 breakpoints, 2 y variables
+_add_pwl_constraints(model, x, [y1, y2], [0.0, 1.0, 2.0], ypts_matrix, name="multiPWL")
+```
+"""
+function _add_pwl_constraints(model, xvar, yvars, xpts, ypts)
+    # Input validation
+    ypts isa AbstractMatrix || throw(ArgumentError("ypts must be a matrix"))
+    length(xpts) == size(ypts, 1) ||
+        throw(ArgumentError("xpts length must match number of rows in ypts"))
+    length(yvars) == size(ypts, 2) ||
+        throw(ArgumentError("Number of y variables must match number of columns in ypts"))
+    length(xpts) >= 1 || throw(ArgumentError("At least one breakpoint is required"))
+
+    # Check that xpts is increasing
+    for i = 2:length(xpts)
+        xpts[i] > xpts[i-1] || throw(ArgumentError("xpts must be in increasing order"))
+    end
+
+    n_points = length(xpts)
+    n_yvars = length(yvars)
+
+    if n_points == 1
+        # Single point case: y_j = ypts[1,j], x = xpts[1]
+        @constraint(model, xvar == xpts[1])
+        for j = 1:n_yvars
+            @constraint(model, yvars[j] == ypts[1, j])
+        end
+
+    elseif n_points == 2
+        # Two points case: single linear segment for each y variable
+        x1, x2 = xpts[1], xpts[2]
+
+        # Linear relationship for each y variable: y_j = y1_j + slope_j * (x-x1)
+        for j = 1:n_yvars
+            y1, y2 = ypts[1, j], ypts[2, j]
+            slope = (y2 - y1) / (x2 - x1)
+            @constraint(model, yvars[j] == y1 + slope * (xvar - x1))
+        end
+    else
+        # Multiple segments case (3+ points): use SOS2 formulation
+        λ = @variable(model, [1:n_points], lower_bound = 0, upper_bound = 1)
+        @constraint(model, λ in SOS2())
+        @constraint(model, sum(λ) == 1)
+        @constraint(model, xvar == sum(xpts[i] * λ[i] for i = 1:n_points))
+        for j = 1:n_yvars
+            @constraint(model, yvars[j] == sum(ypts[i, j] * λ[i] for i = 1:n_points))
+        end
+    end
+
+    return
+end

src/model/solve.jl

@@ -1,94 +0,0 @@
-# RELOG: Reverse Logistics Optimization
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-using JuMP, LinearAlgebra, Geodesy, Cbc, Clp, ProgressBars, Printf, DataStructures
-
-default_milp_optimizer = optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
-default_lp_optimizer = optimizer_with_attributes(Clp.Optimizer, "LogLevel" => 0)
-
-function solve(
-    instance::Instance;
-    optimizer = nothing,
-    output = nothing,
-    marginal_costs = true,
-)
-
-    milp_optimizer = lp_optimizer = optimizer
-    if optimizer == nothing
-        milp_optimizer = default_milp_optimizer
-        lp_optimizer = default_lp_optimizer
-    end
-
-    @info "Building graph..."
-    graph = RELOG.build_graph(instance)
-    @info @sprintf("    %12d time periods", instance.time)
-    @info @sprintf("    %12d process nodes", length(graph.process_nodes))
-    @info @sprintf("    %12d shipping nodes (plant)", length(graph.plant_shipping_nodes))
-    @info @sprintf(
-        "    %12d shipping nodes (collection)",
-        length(graph.collection_shipping_nodes)
-    )
-    @info @sprintf("    %12d arcs", length(graph.arcs))
-
-    @info "Building optimization model..."
-    model = RELOG.build_model(instance, graph, milp_optimizer)
-
-    @info "Optimizing MILP..."
-    JuMP.optimize!(model)
-
-    if !has_values(model)
-        @warn "No solution available"
-        return OrderedDict()
-    end
-
-    if marginal_costs
-        @info "Re-optimizing with integer variables fixed..."
-        all_vars = JuMP.all_variables(model)
-        vals = OrderedDict(var => JuMP.value(var) for var in all_vars)
-        JuMP.set_optimizer(model, lp_optimizer)
-        for var in all_vars
-            if JuMP.is_binary(var)
-                JuMP.unset_binary(var)
-                JuMP.fix(var, vals[var])
-            end
-        end
-        JuMP.optimize!(model)
-    end
-
-    @info "Extracting solution..."
-    solution = get_solution(model, marginal_costs = marginal_costs)
-
-    if output != nothing
-        write(solution, output)
-    end
-
-    return solution
-end
-
-function solve(filename::AbstractString; heuristic = false, kwargs...)
-    @info "Reading $filename..."
-    instance = RELOG.parsefile(filename)
-    if heuristic && instance.time > 1
-        @info "Solving single-period version..."
-        compressed = _compress(instance)
-        csol = solve(compressed; output = nothing, marginal_costs = false, kwargs...)
-        @info "Filtering candidate locations..."
-        selected_pairs = []
-        for (plant_name, plant_dict) in csol["Plants"]
-            for (location_name, location_dict) in plant_dict
-                push!(selected_pairs, (plant_name, location_name))
-            end
-        end
-        filtered_plants = []
-        for p in instance.plants
-            if (p.plant_name, p.location_name) in selected_pairs
-                push!(filtered_plants, p)
-            end
-        end
-        instance.plants = filtered_plants
-        @info "Solving original version..."
-    end
-    sol = solve(instance; kwargs...)
-    return sol
-end

src/reports/centers.jl

@@ -0,0 +1,101 @@
+# RELOG: Reverse Logistics Optimization
+# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+# Released under the modified BSD license. See COPYING.md for more details.
+
+using DataFrames
+using CSV
+
+function centers_report(model)::DataFrame
+    df = DataFrame()
+    df."center" = String[]
+    df."latitude" = Float64[]
+    df."longitude" = Float64[]
+    df."year" = Int[]
+    df."input product" = String[]
+    df."input amount (tonne)" = Float64[]
+    df."revenue (\$)" = Float64[]
+    df."operating cost (\$)" = Float64[]
+
+    centers = model.ext[:instance].centers
+    T = 1:model.ext[:instance].time_horizon
+    E_in = model.ext[:E_in]
+
+    for c in centers, t in T
+        input_name = (c.input === nothing) ? "" : c.input.name
+        input = value(model[:z_input][c.name, t])
+        if isempty(E_in[c])
+            revenue = 0
+        else
+            revenue = sum(
+                c.revenue[t] * value(model[:y][p.name, c.name, m.name, t]) for
+                (p, m) in E_in[c]
+            )
+        end
+        push!(
+            df,
+            Dict(
+                "center" => c.name,
+                "latitude" => c.latitude,
+                "longitude" => c.longitude,
+                "year" => t,
+                "input product" => input_name,
+                "input amount (tonne)" => _round(input),
+                "revenue (\$)" => _round(revenue),
+                "operating cost (\$)" => _round(c.operating_cost[t]),
+            ),
+        )
+    end
+    return df
+end
+
+function center_outputs_report(model)::DataFrame
+    df = DataFrame()
+    df."center" = String[]
+    df."latitude" = Float64[]
+    df."longitude" = Float64[]
+    df."output product" = String[]
+    df."year" = Int[]
+    df."amount collected (tonne)" = Float64[]
+    df."amount disposed (tonne)" = Float64[]
+    df."disposal limit (tonne)" = Float64[]
+    df."collection cost (\$)" = Float64[]
+    df."disposal cost (\$)" = Float64[]
+
+    centers = model.ext[:instance].centers
+    T = 1:model.ext[:instance].time_horizon
+    E_out = model.ext[:E_out]
+
+    for c in centers, m in c.outputs, t in T
+        collected = value(model[:z_collected][c.name, m.name, t])
+        disposed = value(model[:z_disp][c.name, m.name, t])
+        disposal_cost = c.disposal_cost[m][t] * disposed
+        if isempty(E_out[c])
+            collection_cost = 0
+        else
+            collection_cost = sum(
+                c.collection_cost[m][t] * value(model[:y][c.name, p.name, m.name, t])
+                for (p, m) in E_out[c]
+            )
+        end
+        push!(
+            df,
+            Dict(
+                "center" => c.name,
+                "latitude" => c.latitude,
+                "longitude" => c.longitude,
+                "output product" => m.name,
+                "year" => t,
+                "amount collected (tonne)" => _round(collected),
+                "amount disposed (tonne)" => _round(disposed),
+                "disposal limit (tonne)" => _round(c.disposal_limit[m][t]),
+                "collection cost (\$)" => _round(collection_cost),
+                "disposal cost (\$)" => _round(disposal_cost),
+            ),
+        )
+    end
+    return df
+end
+
+write_centers_report(solution, filename) = CSV.write(filename, centers_report(solution))
+write_center_outputs_report(solution, filename) =
+    CSV.write(filename, center_outputs_report(solution))

src/reports/plant_emissions.jl

@@ -1,38 +0,0 @@
-# RELOG: Reverse Logistics Optimization
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-using DataFrames
-using CSV
-
-function plant_emissions_report(solution)::DataFrame
-    df = DataFrame()
-    df."plant type" = String[]
-    df."location name" = String[]
-    df."year" = Int[]
-    df."emission type" = String[]
-    df."emission amount (tonne)" = Float64[]
-    T = length(solution["Energy"]["Plants (GJ)"])
-    for (plant_name, plant_dict) in solution["Plants"]
-        for (location_name, location_dict) in plant_dict
-            for (emission_name, emission_amount) in location_dict["Emissions (tonne)"]
-                for year = 1:T
-                    push!(
-                        df,
-                        [
-                            plant_name,
-                            location_name,
-                            year,
-                            emission_name,
-                            round(emission_amount[year], digits = 2),
-                        ],
-                    )
-                end
-            end
-        end
-    end
-    return df
-end
-
-write_plant_emissions_report(solution, filename) =
-    CSV.write(filename, plant_emissions_report(solution))

src/reports/plant_outputs.jl

@@ -1,66 +0,0 @@
-# RELOG: Reverse Logistics Optimization
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-using DataFrames
-using CSV
-
-function plant_outputs_report(solution)::DataFrame
-    df = DataFrame()
-    df."plant type" = String[]
-    df."location name" = String[]
-    df."year" = Int[]
-    df."product name" = String[]
-    df."amount produced (tonne)" = Float64[]
-    df."amount sent (tonne)" = Float64[]
-    df."amount disposed (tonne)" = Float64[]
-    df."disposal cost (\$)" = Float64[]
-    T = length(solution["Energy"]["Plants (GJ)"])
-    for (plant_name, plant_dict) in solution["Plants"]
-        for (location_name, location_dict) in plant_dict
-            for (product_name, amount_produced) in location_dict["Total output"]
-                send_dict = location_dict["Output"]["Send"]
-                disposal_dict = location_dict["Output"]["Dispose"]
-
-                sent = zeros(T)
-                if product_name in keys(send_dict)
-                    for (dst_plant_name, dst_plant_dict) in send_dict[product_name]
-                        for (dst_location_name, dst_location_dict) in dst_plant_dict
-                            sent += dst_location_dict["Amount (tonne)"]
-                        end
-                    end
-                end
-                sent = round.(sent, digits = 2)
-
-                disposal_amount = zeros(T)
-                disposal_cost = zeros(T)
-                if product_name in keys(disposal_dict)
-                    disposal_amount += disposal_dict[product_name]["Amount (tonne)"]
-                    disposal_cost += disposal_dict[product_name]["Cost (\$)"]
-                end
-                disposal_amount = round.(disposal_amount, digits = 2)
-                disposal_cost = round.(disposal_cost, digits = 2)
-
-                for year = 1:T
-                    push!(
-                        df,
-                        [
-                            plant_name,
-                            location_name,
-                            year,
-                            product_name,
-                            round(amount_produced[year], digits = 2),
-                            sent[year],
-                            disposal_amount[year],
-                            disposal_cost[year],
-                        ],
-                    )
-                end
-            end
-        end
-    end
-    return df
-end
-
-write_plant_outputs_report(solution, filename) =
-    CSV.write(filename, plant_outputs_report(solution))

src/reports/plants.jl

@@ -5,75 +5,201 @@
 using DataFrames
 using CSV
 
-function plants_report(solution)::DataFrame
+function plants_report(model)::DataFrame
     df = DataFrame()
-    df."plant type" = String[]
+    df."plant" = String[]
-    df."location name" = String[]
+    df."latitude" = Float64[]
+    df."longitude" = Float64[]
+    df."initial capacity" = Float64[]
+    df."current capacity" = Float64[]
     df."year" = Int[]
-    df."latitude (deg)" = Float64[]
+    df."operational?" = Bool[]
-    df."longitude (deg)" = Float64[]
+    df."input amount (tonne)" = Float64[]
-    df."capacity (tonne)" = Float64[]
+    df."stored amount (tonne)" = Float64[]
-    df."amount processed (tonne)" = Float64[]
+    df."processed amount (tonne)" = Float64[]
-    df."amount received (tonne)" = Float64[]
-    df."amount in storage (tonne)" = Float64[]
-    df."utilization factor (%)" = Float64[]
-    df."energy (GJ)" = Float64[]
     df."opening cost (\$)" = Float64[]
-    df."expansion cost (\$)" = Float64[]
     df."fixed operating cost (\$)" = Float64[]
     df."variable operating cost (\$)" = Float64[]
+    df."expansion cost (\$)" = Float64[]
     df."storage cost (\$)" = Float64[]
-    df."total cost (\$)" = Float64[]
+
-    T = length(solution["Energy"]["Plants (GJ)"])
+    plants = model.ext[:instance].plants
-    for (plant_name, plant_dict) in solution["Plants"]
+    T = 1:model.ext[:instance].time_horizon
-        for (location_name, location_dict) in plant_dict
+
-            for year = 1:T
+    for p in plants, t in T
-                capacity = round(location_dict["Capacity (tonne)"][year], digits = 2)
+        operational = JuMP.value(model[:x][p.name, t]) > 0.5
-                received = round(location_dict["Total input (tonne)"][year], digits = 2)
+        input = value(model[:z_input][p.name, t])
-                processed = round(location_dict["Process (tonne)"][year], digits = 2)
+        processed = value(model[:z_process][p.name, t])
-                in_storage = round(location_dict["Storage (tonne)"][year], digits = 2)
+
-                utilization_factor = round(processed / capacity * 100.0, digits = 2)
+        # Calculate total stored amount across all input materials
-                energy = round(location_dict["Energy (GJ)"][year], digits = 2)
+        stored = sum(value(model[:z_storage][p.name, m.name, t]) for m in keys(p.input_mix))
-                latitude = round(location_dict["Latitude (deg)"], digits = 6)
+
-                longitude = round(location_dict["Longitude (deg)"], digits = 6)
+        # Calculate total storage cost
-                opening_cost = round(location_dict["Opening cost (\$)"][year], digits = 2)
+        storage_cost = sum(
-                expansion_cost =
+            p.storage_cost[m][t] * value(model[:z_storage][p.name, m.name, t]) for
-                    round(location_dict["Expansion cost (\$)"][year], digits = 2)
+            m in keys(p.storage_cost)
-                fixed_cost =
-                    round(location_dict["Fixed operating cost (\$)"][year], digits = 2)
-                var_cost =
-                    round(location_dict["Variable operating cost (\$)"][year], digits = 2)
-                storage_cost = round(location_dict["Storage cost (\$)"][year], digits = 2)
-                total_cost = round(
-                    opening_cost + expansion_cost + fixed_cost + var_cost + storage_cost,
-                    digits = 2,
         )
+
+        var_operating_cost = input * p.capacities[1].var_operating_cost[t]
+        opening_cost = 0
+        curr_capacity = 0
+        expansion_cost = 0
+        fix_operating_cost = 0
+
+        if value(model[:x][p.name, t]) > 0.5 && value(model[:x][p.name, t-1]) < 0.5
+            opening_cost = p.capacities[1].opening_cost[t]
+        end
+
+        if operational
+            curr_expansion = JuMP.value(model[:z_exp][p.name, t])
+            prev_expansion = JuMP.value(model[:z_exp][p.name, t-1])
+            curr_capacity = p.capacities[1].size + curr_expansion
+            expansion_cost = R_expand(p, t) * (curr_expansion - prev_expansion)
+            fix_operating_cost =
+                p.capacities[1].fix_operating_cost[t] + R_fix_exp(p, t) * curr_expansion
+        end
+
         push!(
             df,
-                    [
+            Dict(
-                        plant_name,
+                "plant" => p.name,
-                        location_name,
+                "latitude" => p.latitude,
-                        year,
+                "longitude" => p.longitude,
-                        latitude,
+                "initial capacity" => p.initial_capacity,
-                        longitude,
+                "current capacity" => curr_capacity,
-                        capacity,
+                "year" => t,
-                        processed,
+                "operational?" => operational,
-                        received,
+                "input amount (tonne)" => _round(input),
-                        in_storage,
+                "stored amount (tonne)" => _round(stored),
-                        utilization_factor,
+                "processed amount (tonne)" => _round(processed),
-                        energy,
+                "opening cost (\$)" => _round(opening_cost),
-                        opening_cost,
+                "fixed operating cost (\$)" => _round(fix_operating_cost),
-                        expansion_cost,
+                "variable operating cost (\$)" => _round(var_operating_cost),
-                        fixed_cost,
+                "expansion cost (\$)" => _round(expansion_cost),
-                        var_cost,
+                "storage cost (\$)" => _round(storage_cost),
-                        storage_cost,
+            ),
-                        total_cost,
-                    ],
         )
     end
+    return df
+end
+
+function plant_inputs_report(model)::DataFrame
+    df = DataFrame()
+    df."plant" = String[]
+    df."latitude" = Float64[]
+    df."longitude" = Float64[]
+    df."input product" = String[]
+    df."year" = Int[]
+    df."amount received (tonne)" = Float64[]
+    df."current storage level (tonne)" = Float64[]
+    df."storage limit (tonne)" = Float64[]
+    df."storage cost (\$)" = Float64[]
+
+    plants = model.ext[:instance].plants
+    T = 1:model.ext[:instance].time_horizon
+
+    for p in plants, m in keys(p.input_mix), t in T
+        amount_received = sum(
+            value(model[:y][src.name, p.name, m.name, t]) for
+            (src, prod) in model.ext[:E_in][p] if prod == m
+        )
+        storage_level = value(model[:z_storage][p.name, m.name, t])
+        storage_cost = p.storage_cost[m][t] * storage_level
+        push!(
+            df,
+            Dict(
+                "plant" => p.name,
+                "latitude" => p.latitude,
+                "longitude" => p.longitude,
+                "input product" => m.name,
+                "year" => t,
+                "amount received (tonne)" => _round(amount_received),
+                "current storage level (tonne)" => _round(storage_level),
+                "storage limit (tonne)" => _round(p.storage_limit[m][t]),
+                "storage cost (\$)" => _round(storage_cost),
+            ),
+        )
     end
+    return df
+end
+
+function plant_outputs_report(model)::DataFrame
+    df = DataFrame()
+    df."plant" = String[]
+    df."latitude" = Float64[]
+    df."longitude" = Float64[]
+    df."output product" = String[]
+    df."year" = Int[]
+    df."amount produced (tonne)" = Float64[]
+    df."amount disposed (tonne)" = Float64[]
+    df."disposal limit (tonne)" = Float64[]
+    df."disposal cost (\$)" = Float64[]
+
+    plants = model.ext[:instance].plants
+    T = 1:model.ext[:instance].time_horizon
+
+    for p in plants, m in keys(p.output), t in T
+        produced = JuMP.value(model[:z_prod][p.name, m.name, t])
+        disposed = JuMP.value(model[:z_disp][p.name, m.name, t])
+        disposal_cost = p.disposal_cost[m][t] * disposed
+        push!(
+            df,
+            Dict(
+                "plant" => p.name,
+                "latitude" => p.latitude,
+                "longitude" => p.longitude,
+                "output product" => m.name,
+                "year" => t,
+                "amount produced (tonne)" => _round(produced),
+                "amount disposed (tonne)" => _round(disposed),
+                "disposal limit (tonne)" => _round(p.disposal_limit[m][t]),
+                "disposal cost (\$)" => _round(disposal_cost),
+            ),
+        )
+    end
+    return df
+end
+
+function plant_emissions_report(model)::DataFrame
+    df = DataFrame()
+    df."plant" = String[]
+    df."latitude" = Float64[]
+    df."longitude" = Float64[]
+    df."emission" = String[]
+    df."year" = Int[]
+    df."processed amount (tonne)" = Float64[]
+    df."emission factor (tonne/tonne)" = Float64[]
+    df."emissions amount (tonne)" = Float64[]
+
+    plants = model.ext[:instance].plants
+    T = 1:model.ext[:instance].time_horizon
+
+    for p in plants, t in T, g in keys(p.emissions)
+        processed_amount = JuMP.value(model[:z_process][p.name, t])
+        processed_amount > 1e-3 || continue
+        emissions = JuMP.value(model[:z_em_plant][g, p.name, t])
+        emission_factor = p.emissions[g][t]
+        push!(
+            df,
+            Dict(
+                "plant" => p.name,
+                "latitude" => p.latitude,
+                "longitude" => p.longitude,
+                "emission" => g,
+                "year" => t,
+                "processed amount (tonne)" => _round(processed_amount),
+                "emission factor (tonne/tonne)" => _round(emission_factor),
+                "emissions amount (tonne)" => _round(emissions),
+            ),
+        )
     end
     return df
 end
 
 write_plants_report(solution, filename) = CSV.write(filename, plants_report(solution))
+write_plant_inputs_report(solution, filename) =
+    CSV.write(filename, plant_inputs_report(solution))
+write_plant_outputs_report(solution, filename) =
+    CSV.write(filename, plant_outputs_report(solution))
+write_plant_emissions_report(solution, filename) =
+    CSV.write(filename, plant_emissions_report(solution))

src/reports/tr.jl

@@ -1,75 +0,0 @@
-# RELOG: Reverse Logistics Optimization
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-using DataFrames
-using CSV
-
-function transportation_report(solution)::DataFrame
-    df = DataFrame()
-    df."source type" = String[]
-    df."source location name" = String[]
-    df."source latitude (deg)" = Float64[]
-    df."source longitude (deg)" = Float64[]
-    df."destination type" = String[]
-    df."destination location name" = String[]
-    df."destination latitude (deg)" = Float64[]
-    df."destination longitude (deg)" = Float64[]
-    df."product" = String[]
-    df."year" = Int[]
-    df."distance (km)" = Float64[]
-    df."amount (tonne)" = Float64[]
-    df."amount-distance (tonne-km)" = Float64[]
-    df."transportation cost (\$)" = Float64[]
-    df."transportation energy (GJ)" = Float64[]
-
-    T = length(solution["Energy"]["Plants (GJ)"])
-    for (dst_plant_name, dst_plant_dict) in solution["Plants"]
-        for (dst_location_name, dst_location_dict) in dst_plant_dict
-            for (src_plant_name, src_plant_dict) in dst_location_dict["Input"]
-                for (src_location_name, src_location_dict) in src_plant_dict
-                    for year = 1:T
-                        push!(
-                            df,
-                            [
-                                src_plant_name,
-                                src_location_name,
-                                round(src_location_dict["Latitude (deg)"], digits = 6),
-                                round(src_location_dict["Longitude (deg)"], digits = 6),
-                                dst_plant_name,
-                                dst_location_name,
-                                round(dst_location_dict["Latitude (deg)"], digits = 6),
-                                round(dst_location_dict["Longitude (deg)"], digits = 6),
-                                dst_location_dict["Input product"],
-                                year,
-                                round(src_location_dict["Distance (km)"], digits = 2),
-                                round(
-                                    src_location_dict["Amount (tonne)"][year],
-                                    digits = 2,
-                                ),
-                                round(
-                                    src_location_dict["Amount (tonne)"][year] *
-                                    src_location_dict["Distance (km)"],
-                                    digits = 2,
-                                ),
-                                round(
-                                    src_location_dict["Transportation cost (\$)"][year],
-                                    digits = 2,
-                                ),
-                                round(
-                                    src_location_dict["Transportation energy (J)"][year] /
-                                    1e9,
-                                    digits = 2,
-                                ),
-                            ],
-                        )
-                    end
-                end
-            end
-        end
-    end
-    return df
-end
-
-write_transportation_report(solution, filename) =
-    CSV.write(filename, transportation_report(solution))

src/reports/tr_emissions.jl

@@ -1,71 +0,0 @@
-# RELOG: Reverse Logistics Optimization
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-using DataFrames
-using CSV
-
-function transportation_emissions_report(solution)::DataFrame
-    df = DataFrame()
-    df."source type" = String[]
-    df."source location name" = String[]
-    df."source latitude (deg)" = Float64[]
-    df."source longitude (deg)" = Float64[]
-    df."destination type" = String[]
-    df."destination location name" = String[]
-    df."destination latitude (deg)" = Float64[]
-    df."destination longitude (deg)" = Float64[]
-    df."product" = String[]
-    df."year" = Int[]
-    df."distance (km)" = Float64[]
-    df."shipped amount (tonne)" = Float64[]
-    df."shipped amount-distance (tonne-km)" = Float64[]
-    df."emission type" = String[]
-    df."emission amount (tonne)" = Float64[]
-
-    T = length(solution["Energy"]["Plants (GJ)"])
-    for (dst_plant_name, dst_plant_dict) in solution["Plants"]
-        for (dst_location_name, dst_location_dict) in dst_plant_dict
-            for (src_plant_name, src_plant_dict) in dst_location_dict["Input"]
-                for (src_location_name, src_location_dict) in src_plant_dict
-                    for (emission_name, emission_amount) in
-                        src_location_dict["Emissions (tonne)"]
-                        for year = 1:T
-                            push!(
-                                df,
-                                [
-                                    src_plant_name,
-                                    src_location_name,
-                                    round(src_location_dict["Latitude (deg)"], digits = 6),
-                                    round(src_location_dict["Longitude (deg)"], digits = 6),
-                                    dst_plant_name,
-                                    dst_location_name,
-                                    round(dst_location_dict["Latitude (deg)"], digits = 6),
-                                    round(dst_location_dict["Longitude (deg)"], digits = 6),
-                                    dst_location_dict["Input product"],
-                                    year,
-                                    round(src_location_dict["Distance (km)"], digits = 2),
-                                    round(
-                                        src_location_dict["Amount (tonne)"][year],
-                                        digits = 2,
-                                    ),
-                                    round(
-                                        src_location_dict["Amount (tonne)"][year] *
-                                        src_location_dict["Distance (km)"],
-                                        digits = 2,
-                                    ),
-                                    emission_name,
-                                    round(emission_amount[year], digits = 2),
-                                ],
-                            )
-                        end
-                    end
-                end
-            end
-        end
-    end
-    return df
-end
-
-write_transportation_emissions_report(solution, filename) =
-    CSV.write(filename, transportation_emissions_report(solution))

src/reports/transportation.jl

@@ -0,0 +1,99 @@
+# RELOG: Reverse Logistics Optimization
+# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+# Released under the modified BSD license. See COPYING.md for more details.
+
+using DataFrames
+using CSV
+
+function transportation_report(model)::DataFrame
+    df = DataFrame()
+    df."source" = String[]
+    df."destination" = String[]
+    df."product" = String[]
+    df."year" = Int[]
+    df."amount sent (tonne)" = Float64[]
+    df."distance (km)" = Float64[]
+    df."transportation cost (\$)" = Float64[]
+    df."center revenue (\$)" = Float64[]
+    df."center collection cost (\$)" = Float64[]
+
+    E = model.ext[:E]
+    distances = model.ext[:distances]
+    T = 1:model.ext[:instance].time_horizon
+
+    for (p1, p2, m) in E, t in T
+        amount = value(model[:y][p1.name, p2.name, m.name, t])
+        amount > 1e-3 || continue
+        distance = distances[p1, p2, m]
+        tr_cost = distance * amount * m.tr_cost[t]
+        revenue = 0
+        if isa(p2, Center)
+            revenue = p2.revenue[t] * amount
+        end
+        collection_cost = 0
+        if isa(p1, Center)
+            collection_cost = p1.collection_cost[m][t] * amount
+        end
+        push!(
+            df,
+            Dict(
+                "source" => p1.name,
+                "destination" => p2.name,
+                "product" => m.name,
+                "year" => t,
+                "amount sent (tonne)" => _round(amount),
+                "distance (km)" => _round(distance),
+                "transportation cost (\$)" => _round(tr_cost),
+                "center revenue (\$)" => _round(revenue),
+                "center collection cost (\$)" => _round(collection_cost),
+            ),
+        )
+    end
+    return df
+end
+
+function transportation_emissions_report(model)::DataFrame
+    df = DataFrame()
+    df."source" = String[]
+    df."destination" = String[]
+    df."product" = String[]
+    df."emission" = String[]
+    df."year" = Int[]
+    df."amount sent (tonne)" = Float64[]
+    df."distance (km)" = Float64[]
+    df."emission factor (tonne/km/tonne)" = Float64[]
+    df."emission amount (tonne)" = Float64[]
+
+    E = model.ext[:E]
+    distances = model.ext[:distances]
+    T = 1:model.ext[:instance].time_horizon
+
+    for (p1, p2, m) in E, t in T, g in keys(m.tr_emissions)
+        amount = value(model[:y][p1.name, p2.name, m.name, t])
+        amount > 1e-3 || continue
+        distance = distances[p1, p2, m]
+        emission_factor = m.tr_emissions[g][t]
+        emissions = value(model[:z_em_tr][g, p1.name, p2.name, m.name, t])
+        push!(
+            df,
+            Dict(
+                "source" => p1.name,
+                "destination" => p2.name,
+                "product" => m.name,
+                "emission" => g,
+                "year" => t,
+                "amount sent (tonne)" => _round(amount),
+                "distance (km)" => _round(distance),
+                "emission factor (tonne/km/tonne)" => _round(emission_factor),
+                "emission amount (tonne)" => _round(emissions),
+            ),
+        )
+    end
+    return df
+end
+
+write_transportation_report(solution, filename) =
+    CSV.write(filename, transportation_report(solution))
+
+write_transportation_emissions_report(solution, filename) =
+    CSV.write(filename, transportation_emissions_report(solution))

src/reports/write.jl

@@ -1,14 +0,0 @@
-# RELOG: Reverse Logistics Optimization
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-using DataFrames
-using CSV
-import Base: write
-
-function write(solution::AbstractDict, filename::AbstractString)
-    @info "Writing solution: $filename"
-    open(filename, "w") do file
-        JSON.print(file, solution, 2)
-    end
-end

src/schemas/input.json

@@ -1,197 +0,0 @@
-{
-    "$schema": "http://json-schema.org/draft-07/schema#",
-    "$id": "https://anl-ceeesa.github.io/RELOG/input",
-    "title": "Schema for RELOG Input File",
-    "definitions": {
-        "TimeSeries": {
-            "type": "array",
-            "items": {
-                "type": "number"
-            }
-        },
-        "Parameters": {
-            "type": "object",
-            "properties": {
-                "time horizon (years)": {
-                    "type": "number"
-                }
-            },
-            "required": [
-                "time horizon (years)"
-            ]
-        },
-        "Plant": {
-            "type": "object",
-            "additionalProperties": {
-                "type": "object",
-                "properties": {
-                    "input": {
-                        "type": "string"
-                    },
-                    "outputs (tonne/tonne)": {
-                        "type": "object",
-                        "additionalProperties": {
-                            "type": "number"
-                        }
-                    },
-                    "energy (GJ/tonne)": {
-                        "$ref": "#/definitions/TimeSeries"
-                    },
-                    "emissions (tonne/tonne)": {
-                        "type": "object",
-                        "additionalProperties": {
-                            "$ref": "#/definitions/TimeSeries"
-                        }
-                    },
-                    "locations": {
-                        "$ref": "#/definitions/PlantLocation"
-                    }
-                },
-                "required": [
-                    "input",
-                    "locations"
-                ]
-            }
-        },
-        "PlantLocation": {
-            "type": "object",
-            "additionalProperties": {
-                "type": "object",
-                "properties": {
-                    "location": {
-                        "type": "string"
-                    },
-                    "latitude (deg)": {
-                        "type": "number"
-                    },
-                    "longitude (deg)": {
-                        "type": "number"
-                    },
-                    "disposal": {
-                        "type": "object",
-                        "additionalProperties": {
-                            "type": "object",
-                            "properties": {
-                                "cost ($/tonne)": {
-                                    "$ref": "#/definitions/TimeSeries"
-                                },
-                                "limit (tonne)": {
-                                    "$ref": "#/definitions/TimeSeries"
-                                }
-                            },
-                            "required": [
-                                "cost ($/tonne)"
-                            ]
-                        }
-                    },
-                    "storage": {
-                        "type": "object",
-                        "properties": {
-                            "cost ($/tonne)": {
-                                "$ref": "#/definitions/TimeSeries"
-                            },
-                            "limit (tonne)": {
-                                "type": "number"
-                            }
-                        },
-                        "required": [
-                            "cost ($/tonne)",
-                            "limit (tonne)"
-                        ]
-                    },
-                    "capacities (tonne)": {
-                        "type": "object",
-                        "additionalProperties": {
-                            "type": "object",
-                            "properties": {
-                                "variable operating cost ($/tonne)": {
-                                    "$ref": "#/definitions/TimeSeries"
-                                },
-                                "fixed operating cost ($)": {
-                                    "$ref": "#/definitions/TimeSeries"
-                                },
-                                "opening cost ($)": {
-                                    "$ref": "#/definitions/TimeSeries"
-                                }
-                            },
-                            "required": [
-                                "variable operating cost ($/tonne)",
-                                "fixed operating cost ($)",
-                                "opening cost ($)"
-                            ]
-                        }
-                    }
-                },
-                "required": [
-                    "capacities (tonne)"
-                ]
-            }
-        },
-        "InitialAmount": {
-            "type": "object",
-            "additionalProperties": {
-                "type": "object",
-                "properties": {
-                    "location": {
-                        "type": "string"
-                    },
-                    "latitude (deg)": {
-                        "type": "number"
-                    },
-                    "longitude (deg)": {
-                        "type": "number"
-                    },
-                    "amount (tonne)": {
-                        "$ref": "#/definitions/TimeSeries"
-                    }
-                },
-                "required": [
-                    "amount (tonne)"
-                ]
-            }
-        },
-        "Product": {
-            "type": "object",
-            "additionalProperties": {
-                "type": "object",
-                "properties": {
-                    "transportation cost ($/km/tonne)": {
-                        "$ref": "#/definitions/TimeSeries"
-                    },
-                    "transportation energy (J/km/tonne)": {
-                        "$ref": "#/definitions/TimeSeries"
-                    },
-                    "transportation emissions (tonne/km/tonne)": {
-                        "type": "object",
-                        "additionalProperties": {
-                            "$ref": "#/definitions/TimeSeries"
-                        }
-                    },
-                    "initial amounts": {
-                        "$ref": "#/definitions/InitialAmount"
-                    }
-                },
-                "required": [
-                    "transportation cost ($/km/tonne)"
-                ]
-            }
-        }
-    },
-    "type": "object",
-    "properties": {
-        "parameters": {
-            "$ref": "#/definitions/Parameters"
-        },
-        "plants": {
-            "$ref": "#/definitions/Plant"
-        },
-        "products": {
-            "$ref": "#/definitions/Product"
-        }
-    },
-    "required": [
-        "parameters",
-        "plants",
-        "products"
-    ]
-}

src/sysimage.jl

@@ -1,15 +0,0 @@
-using PackageCompiler
-
-using Cbc
-using Clp
-using Geodesy
-using JSON
-using JSONSchema
-using JuMP
-using MathOptInterface
-using ProgressBars
-
-pkg = [:Cbc, :Clp, :Geodesy, :JSON, :JSONSchema, :JuMP, :MathOptInterface, :ProgressBars]
-
-@info "Building system image..."
-create_sysimage(pkg, sysimage_path = "build/sysimage.so")

test/Project.toml

@@ -0,0 +1,14 @@
+name = "RELOGT"
+uuid = "d5238ab2-e29b-4856-ba0f-d2b80f40b47d"
+authors = ["Alinson S. Xavier <git@axavier.org>"]
+version = "0.1.0"
+
+[deps]
+HiGHS = "87dc4568-4c63-4d18-b0c0-bb2238e4078b"
+JSON = "682c06a0-de6a-54ab-a142-c8b1cf79cde6"
+JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
+JuliaFormatter = "98e50ef6-434e-11e9-1051-2b60c6c9e899"
+OrderedCollections = "bac558e1-5e72-5ebc-8fee-abe8a469f55d"
+RELOG = "7cafaa7a-b311-45f0-b313-80bf15b5e5e5"
+Revise = "295af30f-e4ad-537b-8983-00126c2a3abe"
+Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"

test/fixtures/boat_example.jl

@@ -0,0 +1,188 @@
+using OrderedCollections
+using JSON
+using RELOG
+dict = OrderedDict
+
+function run_boat_example()
+    cities_a = dict(
+        "Chicago" => [41.881832, -87.623177],
+        "New York City" => [40.712776, -74.005974],
+        "Los Angeles" => [34.052235, -118.243683],
+        "Houston" => [29.760427, -95.369804],
+        "Phoenix" => [33.448376, -112.074036],
+        "Philadelphia" => [39.952583, -75.165222],
+        "San Antonio" => [29.424122, -98.493629],
+        "San Diego" => [32.715736, -117.161087],
+        "Dallas" => [32.776664, -96.796988],
+        "San Jose" => [37.338208, -121.886329],
+    )
+
+    cities_b = dict(
+        "Chicago" => [41.881832, -87.623177],
+        "Phoenix" => [33.448376, -112.074036],
+        "Dallas" => [32.776664, -96.796988],
+    )
+
+    parameters = dict(
+        "time horizon (years)" => 5,
+        "building period (years)" => [1],
+        "distance metric" => "Euclidean",
+    )
+
+    nail_factory = dict(
+        "input" => nothing,
+        "outputs" => ["Nail"],
+        "fixed output (tonne)" => dict("Nail" => 1),
+        "variable output (tonne/tonne)" => dict("Nail" => 0),
+        "revenue (\$/tonne)" => nothing,
+        "collection cost (\$/tonne)" => dict("Nail" => 1000),
+        "operating cost (\$)" => 0,
+        "disposal limit (tonne)" => dict("Nail" => nothing),
+        "disposal cost (\$/tonne)" => dict("Nail" => 0),
+    )
+
+    forest = dict(
+        "input" => nothing,
+        "outputs" => ["Wood"],
+        "fixed output (tonne)" => dict("Wood" => 100),
+        "variable output (tonne/tonne)" => dict("Wood" => 0),
+        "revenue (\$/tonne)" => nothing,
+        "collection cost (\$/tonne)" => dict("Wood" => 250),
+        "operating cost (\$)" => 0,
+        "disposal limit (tonne)" => dict("Wood" => nothing),
+        "disposal cost (\$/tonne)" => dict("Wood" => 0),
+    )
+
+    retail = dict(
+        "input" => "NewBoat",
+        "outputs" => ["UsedBoat"],
+        "fixed output (tonne)" => dict("UsedBoat" => 0),
+        "variable output (tonne/tonne)" => dict("UsedBoat" => [0.10, 0.25, 0.10]),
+        "revenue (\$/tonne)" => 12_000,
+        "collection cost (\$/tonne)" => dict("UsedBoat" => 100),
+        "operating cost (\$)" => 125_000,
+        "disposal limit (tonne)" => dict("UsedBoat" => 0),
+        "disposal cost (\$/tonne)" => dict("UsedBoat" => 0),
+    )
+
+    prod = dict(
+        "transportation cost (\$/km/tonne)" => 0.30,
+        "transportation energy (J/km/tonne)" => 7_500,
+        "transportation emissions (tonne/km/tonne)" =>
+            dict("CO2" => 2.68, "NH4" => 1.02),
+        "disposal limit (tonne)" => nothing,
+    )
+
+    boat_factory = dict(
+        "input mix (%)" => dict("Wood" => 95, "Nail" => 5),
+        "output (tonne)" => dict("NewBoat" => 1.0),
+        "processing emissions (tonne)" => dict("CO2" => 5),
+        "storage cost (\$/tonne)" => dict("Wood" => 500, "Nail" => 200),
+        "storage limit (tonne)" => dict("Wood" => 5, "Nail" => 1),
+        "disposal cost (\$/tonne)" => dict("NewBoat" => 0),
+        "disposal limit (tonne)" => dict("NewBoat" => 0),
+        "capacities" => [
+            dict(
+                "size (tonne)" => 500,
+                "opening cost (\$)" => 1_00_000,
+                "fixed operating cost (\$)" => 250_000,
+                "variable operating cost (\$/tonne)" => 5,
+            ),
+            dict(
+                "size (tonne)" => 1000,
+                "opening cost (\$)" => 2_000_000,
+                "fixed operating cost (\$)" => 500_000,
+                "variable operating cost (\$/tonne)" => 5,
+            ),
+        ],
+        "initial capacity (tonne)" => 0,
+    )
+
+    recycling_plant = dict(
+        "input mix (%)" => dict("UsedBoat" => 100),
+        "output (tonne)" => dict("Nail" => 0.025, "Wood" => 0.475),
+        "processing emissions (tonne)" => dict("CO2" => 5),
+        "storage cost (\$/tonne)" => dict("UsedBoat" => 0),
+        "storage limit (tonne)" => dict("UsedBoat" => 0),
+        "disposal cost (\$/tonne)" => dict("Nail" => 0, "Wood" => 0),
+        "disposal limit (tonne)" => dict("Nail" => 0, "Wood" => 0),
+        "capacities" => [
+            dict(
+                "size (tonne)" => 500,
+                "opening cost (\$)" => 500_000,
+                "fixed operating cost (\$)" => 125_000,
+                "variable operating cost (\$/tonne)" => 2.5,
+            ),
+            dict(
+                "size (tonne)" => 1000,
+                "opening cost (\$)" => 1_000_000,
+                "fixed operating cost (\$)" => 250_000,
+                "variable operating cost (\$/tonne)" => 2.5,
+            ),
+        ],
+        "initial capacity (tonne)" => 0,
+    )
+
+    lat_lon_dict(city_location) =
+        dict("latitude (deg)" => city_location[1], "longitude (deg)" => city_location[2])
+
+    data = dict(
+        "parameters" => parameters,
+        "products" =>
+            dict("Nail" => prod, "Wood" => prod, "NewBoat" => prod, "UsedBoat" => prod),
+        "centers" => merge(
+            dict(
+                "NailFactory ($city_name)" =>
+                    merge(nail_factory, lat_lon_dict(city_location)) for
+                (city_name, city_location) in cities_b
+            ),
+            dict(
+                "Forest ($city_name)" => merge(forest, lat_lon_dict(city_location))
+                for (city_name, city_location) in cities_b
+            ),
+            dict(
+                "Retail ($city_name)" => merge(retail, lat_lon_dict(city_location))
+                for (city_name, city_location) in cities_a
+            ),
+        ),
+        "plants" => merge(
+            dict(
+                "BoatFactory ($city_name)" =>
+                    merge(boat_factory, lat_lon_dict(city_location)) for
+                (city_name, city_location) in cities_a
+            ),
+            dict(
+                "RecyclingPlant ($city_name)" =>
+                    merge(recycling_plant, lat_lon_dict(city_location)) for
+                (city_name, city_location) in cities_a
+            ),
+        ),
+    )
+
+    # Generate instance file
+    open(fixture("boat_example.json"), "w") do file
+        JSON.print(file, data, 2)
+    end
+
+    # Load and solve example
+    instance = RELOG.parsefile(fixture("boat_example.json"))
+    model = RELOG.build_model(instance, optimizer = HiGHS.Optimizer, variable_names = true)
+    optimize!(model)
+
+    # Write reports
+    mkpath(fixture("boat_example"))
+    write_to_file(model, fixture("boat_example/model.lp"))
+    RELOG.write_plants_report(model, fixture("boat_example/plants.csv"))
+    RELOG.write_plant_inputs_report(model, fixture("boat_example/plant_inputs.csv"))
+    RELOG.write_plant_outputs_report(model, fixture("boat_example/plant_outputs.csv"))
+    RELOG.write_plant_emissions_report(model, fixture("boat_example/plant_emissions.csv"))
+    RELOG.write_centers_report(model, fixture("boat_example/centers.csv"))
+    RELOG.write_center_outputs_report(model, fixture("boat_example/center_outputs.csv"))
+    RELOG.write_transportation_report(model, fixture("boat_example/transportation.csv"))
+    RELOG.write_transportation_emissions_report(
+        model,
+        fixture("boat_example/tr_emissions.csv"),
+    )
+
+    return
+end

test/fixtures/boat_example/center_outputs.csv

@@ -0,0 +1,81 @@
+center,latitude,longitude,output product,year,amount collected (tonne),amount disposed (tonne),disposal limit (tonne),collection cost ($),disposal cost ($)
+NailFactory (Chicago),41.881832,-87.623177,Nail,1,1.0,0.0,Inf,1000.0,0.0
+NailFactory (Chicago),41.881832,-87.623177,Nail,2,1.0,0.0,Inf,1000.0,0.0
+NailFactory (Chicago),41.881832,-87.623177,Nail,3,1.0,0.0,Inf,1000.0,0.0
+NailFactory (Chicago),41.881832,-87.623177,Nail,4,1.0,0.0,Inf,1000.0,0.0
+NailFactory (Chicago),41.881832,-87.623177,Nail,5,1.0,0.0,Inf,1000.0,0.0
+NailFactory (Phoenix),33.448376,-112.074036,Nail,1,1.0,0.0,Inf,1000.0,0.0
+NailFactory (Phoenix),33.448376,-112.074036,Nail,2,1.0,0.0,Inf,1000.0,0.0
+NailFactory (Phoenix),33.448376,-112.074036,Nail,3,1.0,0.0,Inf,1000.0,0.0
+NailFactory (Phoenix),33.448376,-112.074036,Nail,4,1.0,0.0,Inf,1000.0,0.0
+NailFactory (Phoenix),33.448376,-112.074036,Nail,5,1.0,0.0,Inf,1000.0,0.0
+NailFactory (Dallas),32.776664,-96.796988,Nail,1,1.0,0.0,Inf,1000.0,0.0
+NailFactory (Dallas),32.776664,-96.796988,Nail,2,1.0,0.0,Inf,1000.0,0.0
+NailFactory (Dallas),32.776664,-96.796988,Nail,3,1.0,0.0,Inf,1000.0,0.0
+NailFactory (Dallas),32.776664,-96.796988,Nail,4,1.0,0.0,Inf,1000.0,0.0
+NailFactory (Dallas),32.776664,-96.796988,Nail,5,1.0,0.0,Inf,1000.0,0.0
+Forest (Chicago),41.881832,-87.623177,Wood,1,100.0,100.0,Inf,0.0,0.0
+Forest (Chicago),41.881832,-87.623177,Wood,2,100.0,100.0,Inf,0.0,0.0
+Forest (Chicago),41.881832,-87.623177,Wood,3,100.0,100.0,Inf,0.0,0.0
+Forest (Chicago),41.881832,-87.623177,Wood,4,100.0,100.0,Inf,0.0,0.0
+Forest (Chicago),41.881832,-87.623177,Wood,5,100.0,100.0,Inf,0.0,0.0
+Forest (Phoenix),33.448376,-112.074036,Wood,1,100.0,100.0,Inf,0.0,0.0
+Forest (Phoenix),33.448376,-112.074036,Wood,2,100.0,100.0,Inf,0.0,0.0
+Forest (Phoenix),33.448376,-112.074036,Wood,3,100.0,100.0,Inf,0.0,0.0
+Forest (Phoenix),33.448376,-112.074036,Wood,4,100.0,100.0,Inf,0.0,0.0
+Forest (Phoenix),33.448376,-112.074036,Wood,5,100.0,100.0,Inf,0.0,0.0
+Forest (Dallas),32.776664,-96.796988,Wood,1,100.0,43.0,Inf,14250.0,0.0
+Forest (Dallas),32.776664,-96.796988,Wood,2,100.0,43.0,Inf,14250.0,0.0
+Forest (Dallas),32.776664,-96.796988,Wood,3,100.0,43.0,Inf,14250.0,0.0
+Forest (Dallas),32.776664,-96.796988,Wood,4,100.0,43.0,Inf,14250.0,0.0
+Forest (Dallas),32.776664,-96.796988,Wood,5,100.0,43.0,Inf,14250.0,0.0
+Retail (Chicago),41.881832,-87.623177,UsedBoat,1,0.0,0.0,0.0,0.0,0.0
+Retail (Chicago),41.881832,-87.623177,UsedBoat,2,0.0,0.0,0.0,0.0,0.0
+Retail (Chicago),41.881832,-87.623177,UsedBoat,3,0.0,0.0,0.0,0.0,0.0
+Retail (Chicago),41.881832,-87.623177,UsedBoat,4,0.0,0.0,0.0,0.0,0.0
+Retail (Chicago),41.881832,-87.623177,UsedBoat,5,0.0,0.0,0.0,0.0,0.0
+Retail (New York City),40.712776,-74.005974,UsedBoat,1,0.0,0.0,0.0,0.0,0.0
+Retail (New York City),40.712776,-74.005974,UsedBoat,2,0.0,0.0,0.0,0.0,0.0
+Retail (New York City),40.712776,-74.005974,UsedBoat,3,0.0,0.0,0.0,0.0,0.0
+Retail (New York City),40.712776,-74.005974,UsedBoat,4,0.0,0.0,0.0,0.0,0.0
+Retail (New York City),40.712776,-74.005974,UsedBoat,5,0.0,0.0,0.0,0.0,0.0
+Retail (Los Angeles),34.052235,-118.243683,UsedBoat,1,0.0,0.0,0.0,0.0,0.0
+Retail (Los Angeles),34.052235,-118.243683,UsedBoat,2,0.0,0.0,0.0,0.0,0.0
+Retail (Los Angeles),34.052235,-118.243683,UsedBoat,3,0.0,0.0,0.0,0.0,0.0
+Retail (Los Angeles),34.052235,-118.243683,UsedBoat,4,0.0,0.0,0.0,0.0,0.0
+Retail (Los Angeles),34.052235,-118.243683,UsedBoat,5,0.0,0.0,0.0,0.0,0.0
+Retail (Houston),29.760427,-95.369804,UsedBoat,1,0.0,0.0,0.0,0.0,0.0
+Retail (Houston),29.760427,-95.369804,UsedBoat,2,0.0,0.0,0.0,0.0,0.0
+Retail (Houston),29.760427,-95.369804,UsedBoat,3,0.0,0.0,0.0,0.0,0.0
+Retail (Houston),29.760427,-95.369804,UsedBoat,4,0.0,0.0,0.0,0.0,0.0
+Retail (Houston),29.760427,-95.369804,UsedBoat,5,0.0,0.0,0.0,0.0,0.0
+Retail (Phoenix),33.448376,-112.074036,UsedBoat,1,0.0,0.0,0.0,0.0,0.0
+Retail (Phoenix),33.448376,-112.074036,UsedBoat,2,0.0,0.0,0.0,0.0,0.0
+Retail (Phoenix),33.448376,-112.074036,UsedBoat,3,0.0,0.0,0.0,0.0,0.0
+Retail (Phoenix),33.448376,-112.074036,UsedBoat,4,0.0,0.0,0.0,0.0,0.0
+Retail (Phoenix),33.448376,-112.074036,UsedBoat,5,0.0,0.0,0.0,0.0,0.0
+Retail (Philadelphia),39.952583,-75.165222,UsedBoat,1,0.0,0.0,0.0,0.0,0.0
+Retail (Philadelphia),39.952583,-75.165222,UsedBoat,2,0.0,0.0,0.0,0.0,0.0
+Retail (Philadelphia),39.952583,-75.165222,UsedBoat,3,0.0,0.0,0.0,0.0,0.0
+Retail (Philadelphia),39.952583,-75.165222,UsedBoat,4,0.0,0.0,0.0,0.0,0.0
+Retail (Philadelphia),39.952583,-75.165222,UsedBoat,5,0.0,0.0,0.0,0.0,0.0
+Retail (San Antonio),29.424122,-98.493629,UsedBoat,1,0.0,0.0,0.0,0.0,0.0
+Retail (San Antonio),29.424122,-98.493629,UsedBoat,2,0.0,0.0,0.0,0.0,0.0
+Retail (San Antonio),29.424122,-98.493629,UsedBoat,3,0.0,0.0,0.0,0.0,0.0
+Retail (San Antonio),29.424122,-98.493629,UsedBoat,4,0.0,0.0,0.0,0.0,0.0
+Retail (San Antonio),29.424122,-98.493629,UsedBoat,5,0.0,0.0,0.0,0.0,0.0
+Retail (San Diego),32.715736,-117.161087,UsedBoat,1,0.0,0.0,0.0,0.0,0.0
+Retail (San Diego),32.715736,-117.161087,UsedBoat,2,0.0,0.0,0.0,0.0,0.0
+Retail (San Diego),32.715736,-117.161087,UsedBoat,3,0.0,0.0,0.0,0.0,0.0
+Retail (San Diego),32.715736,-117.161087,UsedBoat,4,0.0,0.0,0.0,0.0,0.0
+Retail (San Diego),32.715736,-117.161087,UsedBoat,5,0.0,0.0,0.0,0.0,0.0
+Retail (Dallas),32.776664,-96.796988,UsedBoat,1,6.31579,0.0,0.0,631.57895,0.0
+Retail (Dallas),32.776664,-96.796988,UsedBoat,2,22.93629,0.0,0.0,2293.62881,0.0
+Retail (Dallas),32.776664,-96.796988,UsedBoat,3,31.7714,0.0,0.0,3177.13952,0.0
+Retail (Dallas),32.776664,-96.796988,UsedBoat,4,33.80867,0.0,0.0,3380.86724,0.0
+Retail (Dallas),32.776664,-96.796988,UsedBoat,5,34.54174,0.0,0.0,3454.17409,0.0
+Retail (San Jose),37.338208,-121.886329,UsedBoat,1,0.0,0.0,0.0,0.0,0.0
+Retail (San Jose),37.338208,-121.886329,UsedBoat,2,0.0,0.0,0.0,0.0,0.0
+Retail (San Jose),37.338208,-121.886329,UsedBoat,3,0.0,0.0,0.0,0.0,0.0
+Retail (San Jose),37.338208,-121.886329,UsedBoat,4,0.0,0.0,0.0,0.0,0.0
+Retail (San Jose),37.338208,-121.886329,UsedBoat,5,0.0,0.0,0.0,0.0,0.0

test/fixtures/boat_example/centers.csv

@@ -0,0 +1,81 @@
+center,latitude,longitude,year,input product,input amount (tonne),revenue ($),operating cost ($)
+NailFactory (Chicago),41.881832,-87.623177,1,,0.0,0.0,0.0
+NailFactory (Chicago),41.881832,-87.623177,2,,0.0,0.0,0.0
+NailFactory (Chicago),41.881832,-87.623177,3,,0.0,0.0,0.0
+NailFactory (Chicago),41.881832,-87.623177,4,,0.0,0.0,0.0
+NailFactory (Chicago),41.881832,-87.623177,5,,0.0,0.0,0.0
+NailFactory (Phoenix),33.448376,-112.074036,1,,0.0,0.0,0.0
+NailFactory (Phoenix),33.448376,-112.074036,2,,0.0,0.0,0.0
+NailFactory (Phoenix),33.448376,-112.074036,3,,0.0,0.0,0.0
+NailFactory (Phoenix),33.448376,-112.074036,4,,0.0,0.0,0.0
+NailFactory (Phoenix),33.448376,-112.074036,5,,0.0,0.0,0.0
+NailFactory (Dallas),32.776664,-96.796988,1,,0.0,0.0,0.0
+NailFactory (Dallas),32.776664,-96.796988,2,,0.0,0.0,0.0
+NailFactory (Dallas),32.776664,-96.796988,3,,0.0,0.0,0.0
+NailFactory (Dallas),32.776664,-96.796988,4,,0.0,0.0,0.0
+NailFactory (Dallas),32.776664,-96.796988,5,,0.0,0.0,0.0
+Forest (Chicago),41.881832,-87.623177,1,,0.0,0.0,0.0
+Forest (Chicago),41.881832,-87.623177,2,,0.0,0.0,0.0
+Forest (Chicago),41.881832,-87.623177,3,,0.0,0.0,0.0
+Forest (Chicago),41.881832,-87.623177,4,,0.0,0.0,0.0
+Forest (Chicago),41.881832,-87.623177,5,,0.0,0.0,0.0
+Forest (Phoenix),33.448376,-112.074036,1,,0.0,0.0,0.0
+Forest (Phoenix),33.448376,-112.074036,2,,0.0,0.0,0.0
+Forest (Phoenix),33.448376,-112.074036,3,,0.0,0.0,0.0
+Forest (Phoenix),33.448376,-112.074036,4,,0.0,0.0,0.0
+Forest (Phoenix),33.448376,-112.074036,5,,0.0,0.0,0.0
+Forest (Dallas),32.776664,-96.796988,1,,0.0,0.0,0.0
+Forest (Dallas),32.776664,-96.796988,2,,0.0,0.0,0.0
+Forest (Dallas),32.776664,-96.796988,3,,0.0,0.0,0.0
+Forest (Dallas),32.776664,-96.796988,4,,0.0,0.0,0.0
+Forest (Dallas),32.776664,-96.796988,5,,0.0,0.0,0.0
+Retail (Chicago),41.881832,-87.623177,1,NewBoat,0.0,0.0,125000.0
+Retail (Chicago),41.881832,-87.623177,2,NewBoat,0.0,0.0,125000.0
+Retail (Chicago),41.881832,-87.623177,3,NewBoat,0.0,0.0,125000.0
+Retail (Chicago),41.881832,-87.623177,4,NewBoat,0.0,0.0,125000.0
+Retail (Chicago),41.881832,-87.623177,5,NewBoat,0.0,0.0,125000.0
+Retail (New York City),40.712776,-74.005974,1,NewBoat,0.0,0.0,125000.0
+Retail (New York City),40.712776,-74.005974,2,NewBoat,0.0,0.0,125000.0
+Retail (New York City),40.712776,-74.005974,3,NewBoat,0.0,0.0,125000.0
+Retail (New York City),40.712776,-74.005974,4,NewBoat,0.0,0.0,125000.0
+Retail (New York City),40.712776,-74.005974,5,NewBoat,0.0,0.0,125000.0
+Retail (Los Angeles),34.052235,-118.243683,1,NewBoat,0.0,0.0,125000.0
+Retail (Los Angeles),34.052235,-118.243683,2,NewBoat,0.0,0.0,125000.0
+Retail (Los Angeles),34.052235,-118.243683,3,NewBoat,0.0,0.0,125000.0
+Retail (Los Angeles),34.052235,-118.243683,4,NewBoat,0.0,0.0,125000.0
+Retail (Los Angeles),34.052235,-118.243683,5,NewBoat,0.0,0.0,125000.0
+Retail (Houston),29.760427,-95.369804,1,NewBoat,0.0,0.0,125000.0
+Retail (Houston),29.760427,-95.369804,2,NewBoat,0.0,0.0,125000.0
+Retail (Houston),29.760427,-95.369804,3,NewBoat,0.0,0.0,125000.0
+Retail (Houston),29.760427,-95.369804,4,NewBoat,0.0,0.0,125000.0
+Retail (Houston),29.760427,-95.369804,5,NewBoat,0.0,0.0,125000.0
+Retail (Phoenix),33.448376,-112.074036,1,NewBoat,0.0,0.0,125000.0
+Retail (Phoenix),33.448376,-112.074036,2,NewBoat,0.0,0.0,125000.0
+Retail (Phoenix),33.448376,-112.074036,3,NewBoat,0.0,0.0,125000.0
+Retail (Phoenix),33.448376,-112.074036,4,NewBoat,0.0,0.0,125000.0
+Retail (Phoenix),33.448376,-112.074036,5,NewBoat,0.0,0.0,125000.0
+Retail (Philadelphia),39.952583,-75.165222,1,NewBoat,0.0,0.0,125000.0
+Retail (Philadelphia),39.952583,-75.165222,2,NewBoat,0.0,0.0,125000.0
+Retail (Philadelphia),39.952583,-75.165222,3,NewBoat,0.0,0.0,125000.0
+Retail (Philadelphia),39.952583,-75.165222,4,NewBoat,0.0,0.0,125000.0
+Retail (Philadelphia),39.952583,-75.165222,5,NewBoat,0.0,0.0,125000.0
+Retail (San Antonio),29.424122,-98.493629,1,NewBoat,0.0,0.0,125000.0
+Retail (San Antonio),29.424122,-98.493629,2,NewBoat,0.0,0.0,125000.0
+Retail (San Antonio),29.424122,-98.493629,3,NewBoat,0.0,0.0,125000.0
+Retail (San Antonio),29.424122,-98.493629,4,NewBoat,0.0,0.0,125000.0
+Retail (San Antonio),29.424122,-98.493629,5,NewBoat,0.0,0.0,125000.0
+Retail (San Diego),32.715736,-117.161087,1,NewBoat,0.0,0.0,125000.0
+Retail (San Diego),32.715736,-117.161087,2,NewBoat,0.0,0.0,125000.0
+Retail (San Diego),32.715736,-117.161087,3,NewBoat,0.0,0.0,125000.0
+Retail (San Diego),32.715736,-117.161087,4,NewBoat,0.0,0.0,125000.0
+Retail (San Diego),32.715736,-117.161087,5,NewBoat,0.0,0.0,125000.0
+Retail (Dallas),32.776664,-96.796988,1,NewBoat,63.15789,757894.73684,125000.0
+Retail (Dallas),32.776664,-96.796988,2,NewBoat,71.46814,857617.72853,125000.0
+Retail (Dallas),32.776664,-96.796988,3,NewBoat,75.8857,910628.37148,125000.0
+Retail (Dallas),32.776664,-96.796988,4,NewBoat,76.90434,922852.03459,125000.0
+Retail (Dallas),32.776664,-96.796988,5,NewBoat,77.27087,927250.44516,125000.0
+Retail (San Jose),37.338208,-121.886329,1,NewBoat,0.0,0.0,125000.0
+Retail (San Jose),37.338208,-121.886329,2,NewBoat,0.0,0.0,125000.0
+Retail (San Jose),37.338208,-121.886329,3,NewBoat,0.0,0.0,125000.0
+Retail (San Jose),37.338208,-121.886329,4,NewBoat,0.0,0.0,125000.0
+Retail (San Jose),37.338208,-121.886329,5,NewBoat,0.0,0.0,125000.0

test/fixtures/boat_example/plant_emissions.csv

@@ -0,0 +1,11 @@
+plant,latitude,longitude,emission,year,processed amount (tonne),emission factor (tonne/tonne),emissions amount (tonne)
+BoatFactory (Dallas),32.776664,-96.796988,CO2,1,63.15789,5.0,315.78947
+BoatFactory (Dallas),32.776664,-96.796988,CO2,2,71.46814,5.0,357.34072
+BoatFactory (Dallas),32.776664,-96.796988,CO2,3,75.8857,5.0,379.42849
+BoatFactory (Dallas),32.776664,-96.796988,CO2,4,76.90434,5.0,384.52168
+BoatFactory (Dallas),32.776664,-96.796988,CO2,5,77.27087,5.0,386.35435
+RecyclingPlant (Dallas),32.776664,-96.796988,CO2,1,6.31579,5.0,31.57895
+RecyclingPlant (Dallas),32.776664,-96.796988,CO2,2,22.93629,5.0,114.68144
+RecyclingPlant (Dallas),32.776664,-96.796988,CO2,3,31.7714,5.0,158.85698
+RecyclingPlant (Dallas),32.776664,-96.796988,CO2,4,33.80867,5.0,169.04336
+RecyclingPlant (Dallas),32.776664,-96.796988,CO2,5,34.54174,5.0,172.7087

test/fixtures/boat_example/plant_inputs.csv

@@ -0,0 +1,151 @@
+plant,latitude,longitude,input product,year,amount received (tonne),current storage level (tonne),storage limit (tonne),storage cost ($)
+BoatFactory (Chicago),41.881832,-87.623177,Wood,1,0.0,0.0,5.0,0.0
+BoatFactory (Chicago),41.881832,-87.623177,Wood,2,0.0,0.0,5.0,0.0
+BoatFactory (Chicago),41.881832,-87.623177,Wood,3,0.0,0.0,5.0,0.0
+BoatFactory (Chicago),41.881832,-87.623177,Wood,4,0.0,0.0,5.0,0.0
+BoatFactory (Chicago),41.881832,-87.623177,Wood,5,0.0,0.0,5.0,0.0
+BoatFactory (Chicago),41.881832,-87.623177,Nail,1,0.0,0.0,1.0,0.0
+BoatFactory (Chicago),41.881832,-87.623177,Nail,2,0.0,0.0,1.0,0.0
+BoatFactory (Chicago),41.881832,-87.623177,Nail,3,0.0,0.0,1.0,0.0
+BoatFactory (Chicago),41.881832,-87.623177,Nail,4,0.0,0.0,1.0,0.0
+BoatFactory (Chicago),41.881832,-87.623177,Nail,5,0.0,0.0,1.0,0.0
+BoatFactory (New York City),40.712776,-74.005974,Wood,1,0.0,0.0,5.0,0.0
+BoatFactory (New York City),40.712776,-74.005974,Wood,2,0.0,0.0,5.0,0.0
+BoatFactory (New York City),40.712776,-74.005974,Wood,3,0.0,0.0,5.0,0.0
+BoatFactory (New York City),40.712776,-74.005974,Wood,4,0.0,0.0,5.0,0.0
+BoatFactory (New York City),40.712776,-74.005974,Wood,5,0.0,0.0,5.0,0.0
+BoatFactory (New York City),40.712776,-74.005974,Nail,1,0.0,0.0,1.0,0.0
+BoatFactory (New York City),40.712776,-74.005974,Nail,2,0.0,0.0,1.0,0.0
+BoatFactory (New York City),40.712776,-74.005974,Nail,3,0.0,0.0,1.0,0.0
+BoatFactory (New York City),40.712776,-74.005974,Nail,4,0.0,0.0,1.0,0.0
+BoatFactory (New York City),40.712776,-74.005974,Nail,5,0.0,0.0,1.0,0.0
+BoatFactory (Los Angeles),34.052235,-118.243683,Wood,1,0.0,0.0,5.0,0.0
+BoatFactory (Los Angeles),34.052235,-118.243683,Wood,2,0.0,0.0,5.0,0.0
+BoatFactory (Los Angeles),34.052235,-118.243683,Wood,3,0.0,0.0,5.0,0.0
+BoatFactory (Los Angeles),34.052235,-118.243683,Wood,4,0.0,0.0,5.0,0.0
+BoatFactory (Los Angeles),34.052235,-118.243683,Wood,5,0.0,0.0,5.0,0.0
+BoatFactory (Los Angeles),34.052235,-118.243683,Nail,1,0.0,0.0,1.0,0.0
+BoatFactory (Los Angeles),34.052235,-118.243683,Nail,2,0.0,0.0,1.0,0.0
+BoatFactory (Los Angeles),34.052235,-118.243683,Nail,3,0.0,0.0,1.0,0.0
+BoatFactory (Los Angeles),34.052235,-118.243683,Nail,4,0.0,0.0,1.0,0.0
+BoatFactory (Los Angeles),34.052235,-118.243683,Nail,5,0.0,0.0,1.0,0.0
+BoatFactory (Houston),29.760427,-95.369804,Wood,1,0.0,0.0,5.0,0.0
+BoatFactory (Houston),29.760427,-95.369804,Wood,2,0.0,0.0,5.0,0.0
+BoatFactory (Houston),29.760427,-95.369804,Wood,3,0.0,0.0,5.0,0.0
+BoatFactory (Houston),29.760427,-95.369804,Wood,4,0.0,0.0,5.0,0.0
+BoatFactory (Houston),29.760427,-95.369804,Wood,5,0.0,0.0,5.0,0.0
+BoatFactory (Houston),29.760427,-95.369804,Nail,1,0.0,0.0,1.0,0.0
+BoatFactory (Houston),29.760427,-95.369804,Nail,2,0.0,0.0,1.0,0.0
+BoatFactory (Houston),29.760427,-95.369804,Nail,3,0.0,0.0,1.0,0.0
+BoatFactory (Houston),29.760427,-95.369804,Nail,4,0.0,0.0,1.0,0.0
+BoatFactory (Houston),29.760427,-95.369804,Nail,5,0.0,0.0,1.0,0.0
+BoatFactory (Phoenix),33.448376,-112.074036,Wood,1,0.0,0.0,5.0,0.0
+BoatFactory (Phoenix),33.448376,-112.074036,Wood,2,0.0,0.0,5.0,0.0
+BoatFactory (Phoenix),33.448376,-112.074036,Wood,3,0.0,0.0,5.0,0.0
+BoatFactory (Phoenix),33.448376,-112.074036,Wood,4,0.0,0.0,5.0,0.0
+BoatFactory (Phoenix),33.448376,-112.074036,Wood,5,0.0,0.0,5.0,0.0
+BoatFactory (Phoenix),33.448376,-112.074036,Nail,1,0.0,0.0,1.0,0.0
+BoatFactory (Phoenix),33.448376,-112.074036,Nail,2,0.0,0.0,1.0,0.0
+BoatFactory (Phoenix),33.448376,-112.074036,Nail,3,0.0,0.0,1.0,0.0
+BoatFactory (Phoenix),33.448376,-112.074036,Nail,4,0.0,0.0,1.0,0.0
+BoatFactory (Phoenix),33.448376,-112.074036,Nail,5,0.0,0.0,1.0,0.0
+BoatFactory (Philadelphia),39.952583,-75.165222,Wood,1,0.0,0.0,5.0,0.0
+BoatFactory (Philadelphia),39.952583,-75.165222,Wood,2,0.0,0.0,5.0,0.0
+BoatFactory (Philadelphia),39.952583,-75.165222,Wood,3,0.0,0.0,5.0,0.0
+BoatFactory (Philadelphia),39.952583,-75.165222,Wood,4,0.0,0.0,5.0,0.0
+BoatFactory (Philadelphia),39.952583,-75.165222,Wood,5,0.0,0.0,5.0,0.0
+BoatFactory (Philadelphia),39.952583,-75.165222,Nail,1,0.0,0.0,1.0,0.0
+BoatFactory (Philadelphia),39.952583,-75.165222,Nail,2,0.0,0.0,1.0,0.0
+BoatFactory (Philadelphia),39.952583,-75.165222,Nail,3,0.0,0.0,1.0,0.0
+BoatFactory (Philadelphia),39.952583,-75.165222,Nail,4,0.0,0.0,1.0,0.0
+BoatFactory (Philadelphia),39.952583,-75.165222,Nail,5,0.0,0.0,1.0,0.0
+BoatFactory (San Antonio),29.424122,-98.493629,Wood,1,0.0,0.0,5.0,0.0
+BoatFactory (San Antonio),29.424122,-98.493629,Wood,2,0.0,0.0,5.0,0.0
+BoatFactory (San Antonio),29.424122,-98.493629,Wood,3,0.0,0.0,5.0,0.0
+BoatFactory (San Antonio),29.424122,-98.493629,Wood,4,0.0,0.0,5.0,0.0
+BoatFactory (San Antonio),29.424122,-98.493629,Wood,5,0.0,0.0,5.0,0.0
+BoatFactory (San Antonio),29.424122,-98.493629,Nail,1,0.0,0.0,1.0,0.0
+BoatFactory (San Antonio),29.424122,-98.493629,Nail,2,0.0,0.0,1.0,0.0
+BoatFactory (San Antonio),29.424122,-98.493629,Nail,3,0.0,0.0,1.0,0.0
+BoatFactory (San Antonio),29.424122,-98.493629,Nail,4,0.0,0.0,1.0,0.0
+BoatFactory (San Antonio),29.424122,-98.493629,Nail,5,0.0,0.0,1.0,0.0
+BoatFactory (San Diego),32.715736,-117.161087,Wood,1,0.0,0.0,5.0,0.0
+BoatFactory (San Diego),32.715736,-117.161087,Wood,2,0.0,0.0,5.0,0.0
+BoatFactory (San Diego),32.715736,-117.161087,Wood,3,0.0,0.0,5.0,0.0
+BoatFactory (San Diego),32.715736,-117.161087,Wood,4,0.0,0.0,5.0,0.0
+BoatFactory (San Diego),32.715736,-117.161087,Wood,5,0.0,0.0,5.0,0.0
+BoatFactory (San Diego),32.715736,-117.161087,Nail,1,0.0,0.0,1.0,0.0
+BoatFactory (San Diego),32.715736,-117.161087,Nail,2,0.0,0.0,1.0,0.0
+BoatFactory (San Diego),32.715736,-117.161087,Nail,3,0.0,0.0,1.0,0.0
+BoatFactory (San Diego),32.715736,-117.161087,Nail,4,0.0,0.0,1.0,0.0
+BoatFactory (San Diego),32.715736,-117.161087,Nail,5,0.0,0.0,1.0,0.0
+BoatFactory (Dallas),32.776664,-96.796988,Wood,1,60.0,0.0,5.0,0.0
+BoatFactory (Dallas),32.776664,-96.796988,Wood,2,67.89474,0.0,5.0,0.0
+BoatFactory (Dallas),32.776664,-96.796988,Wood,3,72.09141,0.0,5.0,0.0
+BoatFactory (Dallas),32.776664,-96.796988,Wood,4,73.05912,0.0,5.0,0.0
+BoatFactory (Dallas),32.776664,-96.796988,Wood,5,73.40733,0.0,5.0,0.0
+BoatFactory (Dallas),32.776664,-96.796988,Nail,1,3.15789,0.0,1.0,0.0
+BoatFactory (Dallas),32.776664,-96.796988,Nail,2,3.57341,0.0,1.0,0.0
+BoatFactory (Dallas),32.776664,-96.796988,Nail,3,3.79428,0.0,1.0,0.0
+BoatFactory (Dallas),32.776664,-96.796988,Nail,4,3.84522,0.0,1.0,0.0
+BoatFactory (Dallas),32.776664,-96.796988,Nail,5,3.86354,0.0,1.0,0.0
+BoatFactory (San Jose),37.338208,-121.886329,Wood,1,0.0,0.0,5.0,0.0
+BoatFactory (San Jose),37.338208,-121.886329,Wood,2,0.0,0.0,5.0,0.0
+BoatFactory (San Jose),37.338208,-121.886329,Wood,3,0.0,0.0,5.0,0.0
+BoatFactory (San Jose),37.338208,-121.886329,Wood,4,0.0,0.0,5.0,0.0
+BoatFactory (San Jose),37.338208,-121.886329,Wood,5,0.0,0.0,5.0,0.0
+BoatFactory (San Jose),37.338208,-121.886329,Nail,1,0.0,0.0,1.0,0.0
+BoatFactory (San Jose),37.338208,-121.886329,Nail,2,0.0,0.0,1.0,0.0
+BoatFactory (San Jose),37.338208,-121.886329,Nail,3,0.0,0.0,1.0,0.0
+BoatFactory (San Jose),37.338208,-121.886329,Nail,4,0.0,0.0,1.0,0.0
+BoatFactory (San Jose),37.338208,-121.886329,Nail,5,0.0,0.0,1.0,0.0
+RecyclingPlant (Chicago),41.881832,-87.623177,UsedBoat,1,0.0,0.0,0.0,0.0
+RecyclingPlant (Chicago),41.881832,-87.623177,UsedBoat,2,0.0,0.0,0.0,0.0
+RecyclingPlant (Chicago),41.881832,-87.623177,UsedBoat,3,0.0,0.0,0.0,0.0
+RecyclingPlant (Chicago),41.881832,-87.623177,UsedBoat,4,0.0,0.0,0.0,0.0
+RecyclingPlant (Chicago),41.881832,-87.623177,UsedBoat,5,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,UsedBoat,1,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,UsedBoat,2,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,UsedBoat,3,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,UsedBoat,4,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,UsedBoat,5,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,UsedBoat,1,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,UsedBoat,2,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,UsedBoat,3,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,UsedBoat,4,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,UsedBoat,5,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,UsedBoat,1,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,UsedBoat,2,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,UsedBoat,3,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,UsedBoat,4,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,UsedBoat,5,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,UsedBoat,1,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,UsedBoat,2,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,UsedBoat,3,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,UsedBoat,4,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,UsedBoat,5,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,UsedBoat,1,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,UsedBoat,2,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,UsedBoat,3,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,UsedBoat,4,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,UsedBoat,5,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,UsedBoat,1,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,UsedBoat,2,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,UsedBoat,3,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,UsedBoat,4,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,UsedBoat,5,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,UsedBoat,1,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,UsedBoat,2,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,UsedBoat,3,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,UsedBoat,4,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,UsedBoat,5,0.0,0.0,0.0,0.0
+RecyclingPlant (Dallas),32.776664,-96.796988,UsedBoat,1,6.31579,0.0,0.0,0.0
+RecyclingPlant (Dallas),32.776664,-96.796988,UsedBoat,2,22.93629,0.0,0.0,0.0
+RecyclingPlant (Dallas),32.776664,-96.796988,UsedBoat,3,31.7714,0.0,0.0,0.0
+RecyclingPlant (Dallas),32.776664,-96.796988,UsedBoat,4,33.80867,0.0,0.0,0.0
+RecyclingPlant (Dallas),32.776664,-96.796988,UsedBoat,5,34.54174,0.0,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,UsedBoat,1,0.0,0.0,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,UsedBoat,2,0.0,0.0,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,UsedBoat,3,0.0,0.0,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,UsedBoat,4,0.0,0.0,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,UsedBoat,5,0.0,0.0,0.0,0.0

test/fixtures/boat_example/plant_outputs.csv

@@ -0,0 +1,151 @@
+plant,latitude,longitude,output product,year,amount produced (tonne),amount disposed (tonne),disposal limit (tonne),disposal cost ($)
+BoatFactory (Chicago),41.881832,-87.623177,NewBoat,1,0.0,0.0,0.0,0.0
+BoatFactory (Chicago),41.881832,-87.623177,NewBoat,2,0.0,0.0,0.0,0.0
+BoatFactory (Chicago),41.881832,-87.623177,NewBoat,3,0.0,0.0,0.0,0.0
+BoatFactory (Chicago),41.881832,-87.623177,NewBoat,4,0.0,0.0,0.0,0.0
+BoatFactory (Chicago),41.881832,-87.623177,NewBoat,5,0.0,0.0,0.0,0.0
+BoatFactory (New York City),40.712776,-74.005974,NewBoat,1,0.0,0.0,0.0,0.0
+BoatFactory (New York City),40.712776,-74.005974,NewBoat,2,0.0,0.0,0.0,0.0
+BoatFactory (New York City),40.712776,-74.005974,NewBoat,3,0.0,0.0,0.0,0.0
+BoatFactory (New York City),40.712776,-74.005974,NewBoat,4,0.0,0.0,0.0,0.0
+BoatFactory (New York City),40.712776,-74.005974,NewBoat,5,0.0,0.0,0.0,0.0
+BoatFactory (Los Angeles),34.052235,-118.243683,NewBoat,1,0.0,0.0,0.0,0.0
+BoatFactory (Los Angeles),34.052235,-118.243683,NewBoat,2,0.0,0.0,0.0,0.0
+BoatFactory (Los Angeles),34.052235,-118.243683,NewBoat,3,0.0,0.0,0.0,0.0
+BoatFactory (Los Angeles),34.052235,-118.243683,NewBoat,4,0.0,0.0,0.0,0.0
+BoatFactory (Los Angeles),34.052235,-118.243683,NewBoat,5,0.0,0.0,0.0,0.0
+BoatFactory (Houston),29.760427,-95.369804,NewBoat,1,0.0,0.0,0.0,0.0
+BoatFactory (Houston),29.760427,-95.369804,NewBoat,2,0.0,0.0,0.0,0.0
+BoatFactory (Houston),29.760427,-95.369804,NewBoat,3,0.0,0.0,0.0,0.0
+BoatFactory (Houston),29.760427,-95.369804,NewBoat,4,0.0,0.0,0.0,0.0
+BoatFactory (Houston),29.760427,-95.369804,NewBoat,5,0.0,0.0,0.0,0.0
+BoatFactory (Phoenix),33.448376,-112.074036,NewBoat,1,0.0,0.0,0.0,0.0
+BoatFactory (Phoenix),33.448376,-112.074036,NewBoat,2,0.0,0.0,0.0,0.0
+BoatFactory (Phoenix),33.448376,-112.074036,NewBoat,3,0.0,0.0,0.0,0.0
+BoatFactory (Phoenix),33.448376,-112.074036,NewBoat,4,0.0,0.0,0.0,0.0
+BoatFactory (Phoenix),33.448376,-112.074036,NewBoat,5,0.0,0.0,0.0,0.0
+BoatFactory (Philadelphia),39.952583,-75.165222,NewBoat,1,0.0,0.0,0.0,0.0
+BoatFactory (Philadelphia),39.952583,-75.165222,NewBoat,2,0.0,0.0,0.0,0.0
+BoatFactory (Philadelphia),39.952583,-75.165222,NewBoat,3,0.0,0.0,0.0,0.0
+BoatFactory (Philadelphia),39.952583,-75.165222,NewBoat,4,0.0,0.0,0.0,0.0
+BoatFactory (Philadelphia),39.952583,-75.165222,NewBoat,5,0.0,0.0,0.0,0.0
+BoatFactory (San Antonio),29.424122,-98.493629,NewBoat,1,0.0,0.0,0.0,0.0
+BoatFactory (San Antonio),29.424122,-98.493629,NewBoat,2,0.0,0.0,0.0,0.0
+BoatFactory (San Antonio),29.424122,-98.493629,NewBoat,3,0.0,0.0,0.0,0.0
+BoatFactory (San Antonio),29.424122,-98.493629,NewBoat,4,0.0,0.0,0.0,0.0
+BoatFactory (San Antonio),29.424122,-98.493629,NewBoat,5,0.0,0.0,0.0,0.0
+BoatFactory (San Diego),32.715736,-117.161087,NewBoat,1,0.0,0.0,0.0,0.0
+BoatFactory (San Diego),32.715736,-117.161087,NewBoat,2,0.0,0.0,0.0,0.0
+BoatFactory (San Diego),32.715736,-117.161087,NewBoat,3,0.0,0.0,0.0,0.0
+BoatFactory (San Diego),32.715736,-117.161087,NewBoat,4,0.0,0.0,0.0,0.0
+BoatFactory (San Diego),32.715736,-117.161087,NewBoat,5,0.0,0.0,0.0,0.0
+BoatFactory (Dallas),32.776664,-96.796988,NewBoat,1,63.15789,0.0,0.0,0.0
+BoatFactory (Dallas),32.776664,-96.796988,NewBoat,2,71.46814,0.0,0.0,0.0
+BoatFactory (Dallas),32.776664,-96.796988,NewBoat,3,75.8857,0.0,0.0,0.0
+BoatFactory (Dallas),32.776664,-96.796988,NewBoat,4,76.90434,0.0,0.0,0.0
+BoatFactory (Dallas),32.776664,-96.796988,NewBoat,5,77.27087,0.0,0.0,0.0
+BoatFactory (San Jose),37.338208,-121.886329,NewBoat,1,0.0,0.0,0.0,0.0
+BoatFactory (San Jose),37.338208,-121.886329,NewBoat,2,0.0,0.0,0.0,0.0
+BoatFactory (San Jose),37.338208,-121.886329,NewBoat,3,0.0,0.0,0.0,0.0
+BoatFactory (San Jose),37.338208,-121.886329,NewBoat,4,0.0,0.0,0.0,0.0
+BoatFactory (San Jose),37.338208,-121.886329,NewBoat,5,0.0,0.0,0.0,0.0
+RecyclingPlant (Chicago),41.881832,-87.623177,Nail,1,0.0,0.0,0.0,0.0
+RecyclingPlant (Chicago),41.881832,-87.623177,Nail,2,0.0,0.0,0.0,0.0
+RecyclingPlant (Chicago),41.881832,-87.623177,Nail,3,0.0,0.0,0.0,0.0
+RecyclingPlant (Chicago),41.881832,-87.623177,Nail,4,0.0,0.0,0.0,0.0
+RecyclingPlant (Chicago),41.881832,-87.623177,Nail,5,0.0,0.0,0.0,0.0
+RecyclingPlant (Chicago),41.881832,-87.623177,Wood,1,0.0,0.0,0.0,0.0
+RecyclingPlant (Chicago),41.881832,-87.623177,Wood,2,0.0,0.0,0.0,0.0
+RecyclingPlant (Chicago),41.881832,-87.623177,Wood,3,0.0,0.0,0.0,0.0
+RecyclingPlant (Chicago),41.881832,-87.623177,Wood,4,0.0,0.0,0.0,0.0
+RecyclingPlant (Chicago),41.881832,-87.623177,Wood,5,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,Nail,1,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,Nail,2,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,Nail,3,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,Nail,4,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,Nail,5,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,Wood,1,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,Wood,2,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,Wood,3,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,Wood,4,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,Wood,5,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,Nail,1,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,Nail,2,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,Nail,3,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,Nail,4,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,Nail,5,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,Wood,1,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,Wood,2,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,Wood,3,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,Wood,4,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,Wood,5,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,Nail,1,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,Nail,2,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,Nail,3,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,Nail,4,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,Nail,5,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,Wood,1,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,Wood,2,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,Wood,3,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,Wood,4,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,Wood,5,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,Nail,1,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,Nail,2,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,Nail,3,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,Nail,4,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,Nail,5,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,Wood,1,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,Wood,2,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,Wood,3,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,Wood,4,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,Wood,5,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,Nail,1,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,Nail,2,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,Nail,3,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,Nail,4,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,Nail,5,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,Wood,1,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,Wood,2,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,Wood,3,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,Wood,4,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,Wood,5,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,Nail,1,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,Nail,2,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,Nail,3,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,Nail,4,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,Nail,5,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,Wood,1,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,Wood,2,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,Wood,3,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,Wood,4,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,Wood,5,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,Nail,1,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,Nail,2,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,Nail,3,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,Nail,4,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,Nail,5,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,Wood,1,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,Wood,2,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,Wood,3,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,Wood,4,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,Wood,5,0.0,0.0,0.0,0.0
+RecyclingPlant (Dallas),32.776664,-96.796988,Nail,1,0.15789,0.0,0.0,0.0
+RecyclingPlant (Dallas),32.776664,-96.796988,Nail,2,0.57341,0.0,0.0,0.0
+RecyclingPlant (Dallas),32.776664,-96.796988,Nail,3,0.79428,0.0,0.0,0.0
+RecyclingPlant (Dallas),32.776664,-96.796988,Nail,4,0.84522,0.0,0.0,0.0
+RecyclingPlant (Dallas),32.776664,-96.796988,Nail,5,0.86354,0.0,0.0,0.0
+RecyclingPlant (Dallas),32.776664,-96.796988,Wood,1,3.0,0.0,0.0,0.0
+RecyclingPlant (Dallas),32.776664,-96.796988,Wood,2,10.89474,0.0,0.0,0.0
+RecyclingPlant (Dallas),32.776664,-96.796988,Wood,3,15.09141,0.0,0.0,0.0
+RecyclingPlant (Dallas),32.776664,-96.796988,Wood,4,16.05912,0.0,0.0,0.0
+RecyclingPlant (Dallas),32.776664,-96.796988,Wood,5,16.40733,0.0,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,Nail,1,0.0,0.0,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,Nail,2,0.0,0.0,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,Nail,3,0.0,0.0,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,Nail,4,0.0,0.0,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,Nail,5,0.0,0.0,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,Wood,1,0.0,0.0,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,Wood,2,0.0,0.0,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,Wood,3,0.0,0.0,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,Wood,4,0.0,0.0,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,Wood,5,0.0,0.0,0.0,0.0

test/fixtures/boat_example/plants.csv

@@ -0,0 +1,101 @@
+plant,latitude,longitude,initial capacity,current capacity,year,operational?,input amount (tonne),stored amount (tonne),processed amount (tonne),opening cost ($),fixed operating cost ($),variable operating cost ($),expansion cost ($),storage cost ($)
+BoatFactory (Chicago),41.881832,-87.623177,0.0,0.0,1,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (Chicago),41.881832,-87.623177,0.0,0.0,2,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (Chicago),41.881832,-87.623177,0.0,0.0,3,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (Chicago),41.881832,-87.623177,0.0,0.0,4,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (Chicago),41.881832,-87.623177,0.0,0.0,5,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (New York City),40.712776,-74.005974,0.0,0.0,1,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (New York City),40.712776,-74.005974,0.0,0.0,2,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (New York City),40.712776,-74.005974,0.0,0.0,3,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (New York City),40.712776,-74.005974,0.0,0.0,4,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (New York City),40.712776,-74.005974,0.0,0.0,5,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (Los Angeles),34.052235,-118.243683,0.0,0.0,1,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (Los Angeles),34.052235,-118.243683,0.0,0.0,2,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (Los Angeles),34.052235,-118.243683,0.0,0.0,3,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (Los Angeles),34.052235,-118.243683,0.0,0.0,4,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (Los Angeles),34.052235,-118.243683,0.0,0.0,5,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (Houston),29.760427,-95.369804,0.0,0.0,1,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (Houston),29.760427,-95.369804,0.0,0.0,2,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (Houston),29.760427,-95.369804,0.0,0.0,3,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (Houston),29.760427,-95.369804,0.0,0.0,4,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (Houston),29.760427,-95.369804,0.0,0.0,5,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (Phoenix),33.448376,-112.074036,0.0,0.0,1,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (Phoenix),33.448376,-112.074036,0.0,0.0,2,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (Phoenix),33.448376,-112.074036,0.0,0.0,3,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (Phoenix),33.448376,-112.074036,0.0,0.0,4,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (Phoenix),33.448376,-112.074036,0.0,0.0,5,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (Philadelphia),39.952583,-75.165222,0.0,0.0,1,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (Philadelphia),39.952583,-75.165222,0.0,0.0,2,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (Philadelphia),39.952583,-75.165222,0.0,0.0,3,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (Philadelphia),39.952583,-75.165222,0.0,0.0,4,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (Philadelphia),39.952583,-75.165222,0.0,0.0,5,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (San Antonio),29.424122,-98.493629,0.0,0.0,1,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (San Antonio),29.424122,-98.493629,0.0,0.0,2,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (San Antonio),29.424122,-98.493629,0.0,0.0,3,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (San Antonio),29.424122,-98.493629,0.0,0.0,4,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (San Antonio),29.424122,-98.493629,0.0,0.0,5,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (San Diego),32.715736,-117.161087,0.0,0.0,1,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (San Diego),32.715736,-117.161087,0.0,0.0,2,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (San Diego),32.715736,-117.161087,0.0,0.0,3,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (San Diego),32.715736,-117.161087,0.0,0.0,4,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (San Diego),32.715736,-117.161087,0.0,0.0,5,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (Dallas),32.776664,-96.796988,0.0,500.0,1,true,63.15789,0.0,63.15789,100000.0,250000.0,315.78947,0.0,0.0
+BoatFactory (Dallas),32.776664,-96.796988,0.0,500.0,2,true,71.46814,0.0,71.46814,0.0,250000.0,357.34072,0.0,0.0
+BoatFactory (Dallas),32.776664,-96.796988,0.0,500.0,3,true,75.8857,0.0,75.8857,0.0,250000.0,379.42849,0.0,0.0
+BoatFactory (Dallas),32.776664,-96.796988,0.0,500.0,4,true,76.90434,0.0,76.90434,0.0,250000.0,384.52168,0.0,0.0
+BoatFactory (Dallas),32.776664,-96.796988,0.0,500.0,5,true,77.27087,0.0,77.27087,0.0,250000.0,386.35435,0.0,0.0
+BoatFactory (San Jose),37.338208,-121.886329,0.0,0.0,1,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (San Jose),37.338208,-121.886329,0.0,0.0,2,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+BoatFactory (San Jose),37.338208,-121.886329,0.0,0.0,3,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
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+RecyclingPlant (Chicago),41.881832,-87.623177,0.0,0.0,1,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
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+RecyclingPlant (Chicago),41.881832,-87.623177,0.0,0.0,3,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (Chicago),41.881832,-87.623177,0.0,0.0,4,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (Chicago),41.881832,-87.623177,0.0,0.0,5,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,0.0,0.0,1,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,0.0,0.0,2,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,0.0,0.0,3,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,0.0,0.0,4,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (New York City),40.712776,-74.005974,0.0,0.0,5,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,0.0,0.0,1,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,0.0,0.0,2,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,0.0,0.0,3,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,0.0,0.0,4,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (Los Angeles),34.052235,-118.243683,0.0,0.0,5,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,0.0,0.0,1,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,0.0,0.0,2,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,0.0,0.0,3,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,0.0,0.0,4,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (Houston),29.760427,-95.369804,0.0,0.0,5,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,0.0,0.0,1,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,0.0,0.0,2,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,0.0,0.0,3,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,0.0,0.0,4,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (Phoenix),33.448376,-112.074036,0.0,0.0,5,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,0.0,0.0,1,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,0.0,0.0,2,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,0.0,0.0,3,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,0.0,0.0,4,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (Philadelphia),39.952583,-75.165222,0.0,0.0,5,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,0.0,0.0,1,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,0.0,0.0,2,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,0.0,0.0,3,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,0.0,0.0,4,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (San Antonio),29.424122,-98.493629,0.0,0.0,5,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,0.0,0.0,1,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,0.0,0.0,2,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,0.0,0.0,3,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,0.0,0.0,4,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (San Diego),32.715736,-117.161087,0.0,0.0,5,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (Dallas),32.776664,-96.796988,0.0,500.0,1,true,6.31579,0.0,6.31579,500000.0,125000.0,15.78947,0.0,0.0
+RecyclingPlant (Dallas),32.776664,-96.796988,0.0,500.0,2,true,22.93629,0.0,22.93629,0.0,125000.0,57.34072,0.0,0.0
+RecyclingPlant (Dallas),32.776664,-96.796988,0.0,500.0,3,true,31.7714,0.0,31.7714,0.0,125000.0,79.42849,0.0,0.0
+RecyclingPlant (Dallas),32.776664,-96.796988,0.0,500.0,4,true,33.80867,0.0,33.80867,0.0,125000.0,84.52168,0.0,0.0
+RecyclingPlant (Dallas),32.776664,-96.796988,0.0,500.0,5,true,34.54174,0.0,34.54174,0.0,125000.0,86.35435,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,0.0,0.0,1,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,0.0,0.0,2,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,0.0,0.0,3,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,0.0,0.0,4,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0
+RecyclingPlant (San Jose),37.338208,-121.886329,0.0,0.0,5,false,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0

test/fixtures/boat_example/tr_emissions.csv

@@ -0,0 +1,81 @@
+source,destination,product,emission,year,amount sent (tonne),distance (km),emission factor (tonne/km/tonne),emission amount (tonne)
+RecyclingPlant (Dallas),BoatFactory (Dallas),Nail,CO2,1,0.15789,0.0,2.68,0.0
+RecyclingPlant (Dallas),BoatFactory (Dallas),Nail,NH4,1,0.15789,0.0,1.02,0.0
+RecyclingPlant (Dallas),BoatFactory (Dallas),Nail,CO2,2,0.57341,0.0,2.68,0.0
+RecyclingPlant (Dallas),BoatFactory (Dallas),Nail,NH4,2,0.57341,0.0,1.02,0.0
+RecyclingPlant (Dallas),BoatFactory (Dallas),Nail,CO2,3,0.79428,0.0,2.68,0.0
+RecyclingPlant (Dallas),BoatFactory (Dallas),Nail,NH4,3,0.79428,0.0,1.02,0.0
+RecyclingPlant (Dallas),BoatFactory (Dallas),Nail,CO2,4,0.84522,0.0,2.68,0.0
+RecyclingPlant (Dallas),BoatFactory (Dallas),Nail,NH4,4,0.84522,0.0,1.02,0.0
+RecyclingPlant (Dallas),BoatFactory (Dallas),Nail,CO2,5,0.86354,0.0,2.68,0.0
+RecyclingPlant (Dallas),BoatFactory (Dallas),Nail,NH4,5,0.86354,0.0,1.02,0.0
+NailFactory (Chicago),BoatFactory (Dallas),Nail,CO2,1,1.0,1293.093,2.68,3465.48924
+NailFactory (Chicago),BoatFactory (Dallas),Nail,NH4,1,1.0,1293.093,1.02,1318.95486
+NailFactory (Chicago),BoatFactory (Dallas),Nail,CO2,2,1.0,1293.093,2.68,3465.48924
+NailFactory (Chicago),BoatFactory (Dallas),Nail,NH4,2,1.0,1293.093,1.02,1318.95486
+NailFactory (Chicago),BoatFactory (Dallas),Nail,CO2,3,1.0,1293.093,2.68,3465.48924
+NailFactory (Chicago),BoatFactory (Dallas),Nail,NH4,3,1.0,1293.093,1.02,1318.95486
+NailFactory (Chicago),BoatFactory (Dallas),Nail,CO2,4,1.0,1293.093,2.68,3465.48924
+NailFactory (Chicago),BoatFactory (Dallas),Nail,NH4,4,1.0,1293.093,1.02,1318.95486
+NailFactory (Chicago),BoatFactory (Dallas),Nail,CO2,5,1.0,1293.093,2.68,3465.48924
+NailFactory (Chicago),BoatFactory (Dallas),Nail,NH4,5,1.0,1293.093,1.02,1318.95486
+NailFactory (Phoenix),BoatFactory (Dallas),Nail,CO2,1,1.0,1423.57,2.68,3815.1676
+NailFactory (Phoenix),BoatFactory (Dallas),Nail,NH4,1,1.0,1423.57,1.02,1452.0414
+NailFactory (Phoenix),BoatFactory (Dallas),Nail,CO2,2,1.0,1423.57,2.68,3815.1676
+NailFactory (Phoenix),BoatFactory (Dallas),Nail,NH4,2,1.0,1423.57,1.02,1452.0414
+NailFactory (Phoenix),BoatFactory (Dallas),Nail,CO2,3,1.0,1423.57,2.68,3815.1676
+NailFactory (Phoenix),BoatFactory (Dallas),Nail,NH4,3,1.0,1423.57,1.02,1452.0414
+NailFactory (Phoenix),BoatFactory (Dallas),Nail,CO2,4,1.0,1423.57,2.68,3815.1676
+NailFactory (Phoenix),BoatFactory (Dallas),Nail,NH4,4,1.0,1423.57,1.02,1452.0414
+NailFactory (Phoenix),BoatFactory (Dallas),Nail,CO2,5,1.0,1423.57,2.68,3815.1676
+NailFactory (Phoenix),BoatFactory (Dallas),Nail,NH4,5,1.0,1423.57,1.02,1452.0414
+NailFactory (Dallas),BoatFactory (Dallas),Nail,CO2,1,1.0,0.0,2.68,0.0
+NailFactory (Dallas),BoatFactory (Dallas),Nail,NH4,1,1.0,0.0,1.02,0.0
+NailFactory (Dallas),BoatFactory (Dallas),Nail,CO2,2,1.0,0.0,2.68,0.0
+NailFactory (Dallas),BoatFactory (Dallas),Nail,NH4,2,1.0,0.0,1.02,0.0
+NailFactory (Dallas),BoatFactory (Dallas),Nail,CO2,3,1.0,0.0,2.68,0.0
+NailFactory (Dallas),BoatFactory (Dallas),Nail,NH4,3,1.0,0.0,1.02,0.0
+NailFactory (Dallas),BoatFactory (Dallas),Nail,CO2,4,1.0,0.0,2.68,0.0
+NailFactory (Dallas),BoatFactory (Dallas),Nail,NH4,4,1.0,0.0,1.02,0.0
+NailFactory (Dallas),BoatFactory (Dallas),Nail,CO2,5,1.0,0.0,2.68,0.0
+NailFactory (Dallas),BoatFactory (Dallas),Nail,NH4,5,1.0,0.0,1.02,0.0
+RecyclingPlant (Dallas),BoatFactory (Dallas),Wood,CO2,1,3.0,0.0,2.68,0.0
+RecyclingPlant (Dallas),BoatFactory (Dallas),Wood,NH4,1,3.0,0.0,1.02,0.0
+RecyclingPlant (Dallas),BoatFactory (Dallas),Wood,CO2,2,10.89474,0.0,2.68,0.0
+RecyclingPlant (Dallas),BoatFactory (Dallas),Wood,NH4,2,10.89474,0.0,1.02,0.0
+RecyclingPlant (Dallas),BoatFactory (Dallas),Wood,CO2,3,15.09141,0.0,2.68,0.0
+RecyclingPlant (Dallas),BoatFactory (Dallas),Wood,NH4,3,15.09141,0.0,1.02,0.0
+RecyclingPlant (Dallas),BoatFactory (Dallas),Wood,CO2,4,16.05912,0.0,2.68,0.0
+RecyclingPlant (Dallas),BoatFactory (Dallas),Wood,NH4,4,16.05912,0.0,1.02,0.0
+RecyclingPlant (Dallas),BoatFactory (Dallas),Wood,CO2,5,16.40733,0.0,2.68,0.0
+RecyclingPlant (Dallas),BoatFactory (Dallas),Wood,NH4,5,16.40733,0.0,1.02,0.0
+Forest (Dallas),BoatFactory (Dallas),Wood,CO2,1,57.0,0.0,2.68,0.0
+Forest (Dallas),BoatFactory (Dallas),Wood,NH4,1,57.0,0.0,1.02,0.0
+Forest (Dallas),BoatFactory (Dallas),Wood,CO2,2,57.0,0.0,2.68,0.0
+Forest (Dallas),BoatFactory (Dallas),Wood,NH4,2,57.0,0.0,1.02,0.0
+Forest (Dallas),BoatFactory (Dallas),Wood,CO2,3,57.0,0.0,2.68,0.0
+Forest (Dallas),BoatFactory (Dallas),Wood,NH4,3,57.0,0.0,1.02,0.0
+Forest (Dallas),BoatFactory (Dallas),Wood,CO2,4,57.0,0.0,2.68,0.0
+Forest (Dallas),BoatFactory (Dallas),Wood,NH4,4,57.0,0.0,1.02,0.0
+Forest (Dallas),BoatFactory (Dallas),Wood,CO2,5,57.0,0.0,2.68,0.0
+Forest (Dallas),BoatFactory (Dallas),Wood,NH4,5,57.0,0.0,1.02,0.0
+BoatFactory (Dallas),Retail (Dallas),NewBoat,CO2,1,63.15789,0.0,2.68,0.0
+BoatFactory (Dallas),Retail (Dallas),NewBoat,NH4,1,63.15789,0.0,1.02,0.0
+BoatFactory (Dallas),Retail (Dallas),NewBoat,CO2,2,71.46814,0.0,2.68,0.0
+BoatFactory (Dallas),Retail (Dallas),NewBoat,NH4,2,71.46814,0.0,1.02,0.0
+BoatFactory (Dallas),Retail (Dallas),NewBoat,CO2,3,75.8857,0.0,2.68,0.0
+BoatFactory (Dallas),Retail (Dallas),NewBoat,NH4,3,75.8857,0.0,1.02,0.0
+BoatFactory (Dallas),Retail (Dallas),NewBoat,CO2,4,76.90434,0.0,2.68,0.0
+BoatFactory (Dallas),Retail (Dallas),NewBoat,NH4,4,76.90434,0.0,1.02,0.0
+BoatFactory (Dallas),Retail (Dallas),NewBoat,CO2,5,77.27087,0.0,2.68,0.0
+BoatFactory (Dallas),Retail (Dallas),NewBoat,NH4,5,77.27087,0.0,1.02,0.0
+Retail (Dallas),RecyclingPlant (Dallas),UsedBoat,CO2,1,6.31579,0.0,2.68,0.0
+Retail (Dallas),RecyclingPlant (Dallas),UsedBoat,NH4,1,6.31579,0.0,1.02,0.0
+Retail (Dallas),RecyclingPlant (Dallas),UsedBoat,CO2,2,22.93629,0.0,2.68,0.0
+Retail (Dallas),RecyclingPlant (Dallas),UsedBoat,NH4,2,22.93629,0.0,1.02,0.0
+Retail (Dallas),RecyclingPlant (Dallas),UsedBoat,CO2,3,31.7714,0.0,2.68,0.0
+Retail (Dallas),RecyclingPlant (Dallas),UsedBoat,NH4,3,31.7714,0.0,1.02,0.0
+Retail (Dallas),RecyclingPlant (Dallas),UsedBoat,CO2,4,33.80867,0.0,2.68,0.0
+Retail (Dallas),RecyclingPlant (Dallas),UsedBoat,NH4,4,33.80867,0.0,1.02,0.0
+Retail (Dallas),RecyclingPlant (Dallas),UsedBoat,CO2,5,34.54174,0.0,2.68,0.0
+Retail (Dallas),RecyclingPlant (Dallas),UsedBoat,NH4,5,34.54174,0.0,1.02,0.0

test/fixtures/boat_example/transportation.csv

@@ -0,0 +1,41 @@
+source,destination,product,year,amount sent (tonne),distance (km),transportation cost ($),center revenue ($),center collection cost ($)
+RecyclingPlant (Dallas),BoatFactory (Dallas),Nail,1,0.15789,0.0,0.0,0.0,0.0
+RecyclingPlant (Dallas),BoatFactory (Dallas),Nail,2,0.57341,0.0,0.0,0.0,0.0
+RecyclingPlant (Dallas),BoatFactory (Dallas),Nail,3,0.79428,0.0,0.0,0.0,0.0
+RecyclingPlant (Dallas),BoatFactory (Dallas),Nail,4,0.84522,0.0,0.0,0.0,0.0
+RecyclingPlant (Dallas),BoatFactory (Dallas),Nail,5,0.86354,0.0,0.0,0.0,0.0
+NailFactory (Chicago),BoatFactory (Dallas),Nail,1,1.0,1293.093,387.9279,0.0,1000.0
+NailFactory (Chicago),BoatFactory (Dallas),Nail,2,1.0,1293.093,387.9279,0.0,1000.0
+NailFactory (Chicago),BoatFactory (Dallas),Nail,3,1.0,1293.093,387.9279,0.0,1000.0
+NailFactory (Chicago),BoatFactory (Dallas),Nail,4,1.0,1293.093,387.9279,0.0,1000.0
+NailFactory (Chicago),BoatFactory (Dallas),Nail,5,1.0,1293.093,387.9279,0.0,1000.0
+NailFactory (Phoenix),BoatFactory (Dallas),Nail,1,1.0,1423.57,427.071,0.0,1000.0
+NailFactory (Phoenix),BoatFactory (Dallas),Nail,2,1.0,1423.57,427.071,0.0,1000.0
+NailFactory (Phoenix),BoatFactory (Dallas),Nail,3,1.0,1423.57,427.071,0.0,1000.0
+NailFactory (Phoenix),BoatFactory (Dallas),Nail,4,1.0,1423.57,427.071,0.0,1000.0
+NailFactory (Phoenix),BoatFactory (Dallas),Nail,5,1.0,1423.57,427.071,0.0,1000.0
+NailFactory (Dallas),BoatFactory (Dallas),Nail,1,1.0,0.0,0.0,0.0,1000.0
+NailFactory (Dallas),BoatFactory (Dallas),Nail,2,1.0,0.0,0.0,0.0,1000.0
+NailFactory (Dallas),BoatFactory (Dallas),Nail,3,1.0,0.0,0.0,0.0,1000.0
+NailFactory (Dallas),BoatFactory (Dallas),Nail,4,1.0,0.0,0.0,0.0,1000.0
+NailFactory (Dallas),BoatFactory (Dallas),Nail,5,1.0,0.0,0.0,0.0,1000.0
+RecyclingPlant (Dallas),BoatFactory (Dallas),Wood,1,3.0,0.0,0.0,0.0,0.0
+RecyclingPlant (Dallas),BoatFactory (Dallas),Wood,2,10.89474,0.0,0.0,0.0,0.0
+RecyclingPlant (Dallas),BoatFactory (Dallas),Wood,3,15.09141,0.0,0.0,0.0,0.0
+RecyclingPlant (Dallas),BoatFactory (Dallas),Wood,4,16.05912,0.0,0.0,0.0,0.0
+RecyclingPlant (Dallas),BoatFactory (Dallas),Wood,5,16.40733,0.0,0.0,0.0,0.0
+Forest (Dallas),BoatFactory (Dallas),Wood,1,57.0,0.0,0.0,0.0,14250.0
+Forest (Dallas),BoatFactory (Dallas),Wood,2,57.0,0.0,0.0,0.0,14250.0
+Forest (Dallas),BoatFactory (Dallas),Wood,3,57.0,0.0,0.0,0.0,14250.0
+Forest (Dallas),BoatFactory (Dallas),Wood,4,57.0,0.0,0.0,0.0,14250.0
+Forest (Dallas),BoatFactory (Dallas),Wood,5,57.0,0.0,0.0,0.0,14250.0
+BoatFactory (Dallas),Retail (Dallas),NewBoat,1,63.15789,0.0,0.0,757894.73684,0.0
+BoatFactory (Dallas),Retail (Dallas),NewBoat,2,71.46814,0.0,0.0,857617.72853,0.0
+BoatFactory (Dallas),Retail (Dallas),NewBoat,3,75.8857,0.0,0.0,910628.37148,0.0
+BoatFactory (Dallas),Retail (Dallas),NewBoat,4,76.90434,0.0,0.0,922852.03459,0.0
+BoatFactory (Dallas),Retail (Dallas),NewBoat,5,77.27087,0.0,0.0,927250.44516,0.0
+Retail (Dallas),RecyclingPlant (Dallas),UsedBoat,1,6.31579,0.0,0.0,0.0,631.57895
+Retail (Dallas),RecyclingPlant (Dallas),UsedBoat,2,22.93629,0.0,0.0,0.0,2293.62881
+Retail (Dallas),RecyclingPlant (Dallas),UsedBoat,3,31.7714,0.0,0.0,0.0,3177.13952
+Retail (Dallas),RecyclingPlant (Dallas),UsedBoat,4,33.80867,0.0,0.0,0.0,3380.86724
+Retail (Dallas),RecyclingPlant (Dallas),UsedBoat,5,34.54174,0.0,0.0,0.0,3454.17409

test/fixtures/s1-wrong-length.json

@@ -1,202 +0,0 @@
-{
-    "parameters": {
-        "time horizon (years)": 2
-    },
-    "products": {
-        "P1": {
-            "transportation cost ($/km/tonne)": [0.015, 0.015],
-            "transportation energy (J/km/tonne)": [0.12, 0.11],
-            "transportation emissions (tonne/km/tonne)": {
-                "CO2": [0.052],
-                "CH4": [0.003, 0.002]
-            },            
-            "initial amounts": {
-                "C1": {
-                    "latitude (deg)": 7.0,
-                    "longitude (deg)": 7.0,
-                    "amount (tonne)": [934.56, 934.56]
-                },
-                "C2": {
-                    "latitude (deg)": 7.0,
-                    "longitude (deg)": 19.0,
-                    "amount (tonne)": [198.95, 198.95]
-                },
-                "C3": {
-                    "latitude (deg)": 84.0,
-                    "longitude (deg)": 76.0,
-                    "amount (tonne)": [212.97, 212.97]
-                },
-                "C4": {
-                    "latitude (deg)": 21.0,
-                    "longitude (deg)": 16.0,
-                    "amount (tonne)": [352.19, 352.19]
-                },
-                "C5": {
-                    "latitude (deg)": 32.0,
-                    "longitude (deg)": 92.0,
-                    "amount (tonne)": [510.33, 510.33]
-                },
-                "C6": {
-                    "latitude (deg)": 14.0,
-                    "longitude (deg)": 62.0,
-                    "amount (tonne)": [471.66, 471.66]
-                },
-                "C7": {
-                    "latitude (deg)": 30.0,
-                    "longitude (deg)": 83.0,
-                    "amount (tonne)": [785.21, 785.21]
-                },
-                "C8": {
-                    "latitude (deg)": 35.0,
-                    "longitude (deg)": 40.0,
-                    "amount (tonne)": [706.17, 706.17]
-                },
-                "C9": {
-                    "latitude (deg)": 74.0,
-                    "longitude (deg)": 52.0,
-                    "amount (tonne)": [30.08, 30.08]
-                },
-                "C10": {
-                    "latitude (deg)": 22.0,
-                    "longitude (deg)": 54.0,
-                    "amount (tonne)": [536.52, 536.52]
-                }
-            }
-        },
-        "P2": {
-            "transportation cost ($/km/tonne)": [0.02, 0.02]
-        },
-        "P3": {
-            "transportation cost ($/km/tonne)": [0.0125, 0.0125]
-        },
-        "P4": {
-            "transportation cost ($/km/tonne)": [0.0175, 0.0175]
-        }
-    },
-    "plants": {
-        "F1": {
-            "input": "P1",
-            "outputs (tonne/tonne)": {
-                "P2": 0.2,
-                "P3": 0.5
-            },
-            "energy (GJ/tonne)": [0.12, 0.11],
-            "emissions (tonne/tonne)": {
-                "CO2": [0.052, 0.050],
-                "CH4": [0.003, 0.002]
-            },            
-            "locations": {
-                "L1": {
-                    "latitude (deg)": 0.0,
-                    "longitude (deg)": 0.0,
-                    "disposal": {
-                        "P2": {
-                            "cost ($/tonne)": [-10.0, -10.0],
-                            "limit (tonne)": [1.0, 1.0]
-                        },
-                        "P3": {
-                            "cost ($/tonne)": [-10.0, -10.0],
-                            "limit (tonne)": [1.0, 1.0]
-                        }
-                    },
-                    "capacities (tonne)": {
-                        "250.0": {
-                            "opening cost ($)": [500.0, 500.0],
-                            "fixed operating cost ($)": [30.0, 30.0],
-                            "variable operating cost ($/tonne)": [30.0, 30.0]
-                        },
-                        "1000.0": {
-                            "opening cost ($)": [1250.0, 1250.0],
-                            "fixed operating cost ($)": [30.0, 30.0],
-                            "variable operating cost ($/tonne)": [30.0, 30.0]
-                        }
-                    }
-                },
-                "L2": {
-                    "latitude (deg)": 0.5,
-                    "longitude (deg)": 0.5,
-                    "capacities (tonne)": {
-                        "0.0": {
-                            "opening cost ($)": [1000, 1000],
-                            "fixed operating cost ($)": [50.0, 50.0],
-                            "variable operating cost ($/tonne)": [50.0, 50.0]
-                        },
-                        "10000.0": {
-                            "opening cost ($)": [10000, 10000],
-                            "fixed operating cost ($)": [50.0, 50.0],
-                            "variable operating cost ($/tonne)": [50.0, 50.0]
-                        }
-                    }
-                }               
-            }
-        },
-        "F2": {
-            "input": "P2",
-            "outputs (tonne/tonne)": {
-                "P3": 0.05,
-                "P4": 0.80
-            },
-            "locations": {
-                "L3": {
-                    "latitude (deg)": 25.0,
-                    "longitude (deg)": 65.0,
-                    "disposal": {
-                        "P3": {
-                            "cost ($/tonne)": [100.0, 100.0]
-                        }
-                    },
-                    "capacities (tonne)": {
-                        "1000.0": {
-                            "opening cost ($)": [3000, 3000],
-                            "fixed operating cost ($)": [50.0, 50.0],
-                            "variable operating cost ($/tonne)": [50.0, 50.0]
-                        }
-                    }
-                },
-                "L4": {
-                    "latitude (deg)": 0.75,
-                    "longitude (deg)": 0.20,
-                    "capacities (tonne)": {
-                        "10000": {
-                            "opening cost ($)": [3000, 3000],
-                            "fixed operating cost ($)": [50.0, 50.0],
-                            "variable operating cost ($/tonne)": [50.0, 50.0]
-                        }
-                    }
-                }
-            }
-        },
-        "F3": {
-            "input": "P4",
-            "locations": {
-                "L5": {
-                    "latitude (deg)": 100.0,
-                    "longitude (deg)": 100.0,
-                    "capacities (tonne)": {
-                        "15000": {
-                            "opening cost ($)": [0.0, 0.0],
-                            "fixed operating cost ($)": [0.0, 0.0],
-                            "variable operating cost ($/tonne)": [-15.0, -15.0]
-                        }
-                    }
-                }           
-            }
-        },
-        "F4": {
-            "input": "P3",
-            "locations": {
-                "L6": {
-                    "latitude (deg)": 50.0,
-                    "longitude (deg)": 50.0,
-                    "capacities (tonne)": {
-                        "10000": {
-                            "opening cost ($)": [0.0, 0.0],
-                            "fixed operating cost ($)": [0.0, 0.0],
-                            "variable operating cost ($/tonne)": [-15.0, -15.0]
-                        }
-                    }
-                }           
-            }
-        }
-    }
-}

test/fixtures/simple.json

@@ -0,0 +1,169 @@
+{
+  "parameters": {
+    "time horizon (years)": 4,
+    "building period (years)": [1],
+    "distance metric": "euclidean"
+  },
+  "products": {
+    "P1": {
+      "transportation cost ($/km/tonne)": 0.015,
+      "transportation energy (J/km/tonne)": 0.12,
+      "transportation emissions (tonne/km/tonne)": {
+        "CO2": 0.052,
+        "CH4": [0.003, 0.003, 0.003, 0.003]
+      },
+      "disposal limit (tonne)": 1.0
+    },
+    "P2": {
+      "transportation cost ($/km/tonne)": [0.015, 0.015, 0.015, 0.015],
+      "transportation energy (J/km/tonne)": [0.12, 0.12, 0.12, 0.12],
+      "transportation emissions (tonne/km/tonne)": {
+        "CO2": [0.052, 0.052, 0.052, 0.052],
+        "CH4": [0.003, 0.003, 0.003, 0.003]
+      },
+      "disposal limit (tonne)": 2.0
+    },
+    "P3": {
+      "transportation cost ($/km/tonne)": [0.015, 0.015, 0.015, 0.015],
+      "transportation energy (J/km/tonne)": [0.12, 0.12, 0.12, 0.12],
+      "transportation emissions (tonne/km/tonne)": {
+        "CO2": [0.052, 0.052, 0.052, 0.052],
+        "CH4": [0.003, 0.003, 0.003, 0.003]
+      },
+      "disposal limit (tonne)": 5.0
+    },
+    "P4": {
+      "transportation cost ($/km/tonne)": [0.015, 0.015, 0.015, 0.015],
+      "transportation energy (J/km/tonne)": [0.12, 0.12, 0.12, 0.12],
+      "transportation emissions (tonne/km/tonne)": {
+        "CO2": [0.052, 0.052, 0.052, 0.052],
+        "CH4": [0.003, 0.003, 0.003, 0.003]
+      },
+      "disposal limit (tonne)": null
+    }
+  },
+  "centers": {
+    "C1": {
+      "latitude (deg)": 41.881,
+      "longitude (deg)": -87.623,
+      "input": "P1",
+      "outputs": ["P2", "P3"],
+      "fixed output (tonne)": {
+        "P2": [100, 50, 0, 0],
+        "P3": [20, 10, 0, 0]
+      },
+      "variable output (tonne/tonne)": {
+        "P2": [0.20, 0.25, 0.12],
+        "P3": [0.25, 0.25, 0.25]
+      },
+      "revenue ($/tonne)": 12.0,
+      "collection cost ($/tonne)": {
+        "P2": [0.25, 0.25, 0.25, 0.25],
+        "P3": [0.37, 0.37, 0.37, 0.37]
+      },
+      "operating cost ($)": [150.0, 150.0, 150.0, 150.0],
+      "disposal limit (tonne)": {
+        "P2": [0, 0, 0, 0],
+        "P3": [null, null, null, null]
+      },
+      "disposal cost ($/tonne)": {
+        "P2": [0.23, 0.23, 0.23, 0.23],
+        "P3": [1.0, 1.0, 1.0, 1.0]
+      }
+    },
+    "C2": {
+      "latitude (deg)": 42.881,
+      "longitude (deg)": -87.623,
+      "input": null,
+      "outputs": ["P1"],
+      "variable output (tonne/tonne)": {
+        "P1": 0
+      },
+      "fixed output (tonne)": {
+        "P1": [50, 60, 70, 80]
+      },
+      "revenue ($/tonne)": null,
+      "collection cost ($/tonne)": {
+        "P1": 0.25
+      },
+      "operating cost ($)": [150.0, 150.0, 150.0, 150.0],
+      "disposal limit (tonne)": {
+        "P1": null
+      },
+      "disposal cost ($/tonne)": {
+        "P1": 0
+      }
+    },
+    "C3": {
+      "latitude (deg)": 43.881,
+      "longitude (deg)": -87.623,
+      "input": "P4",
+      "outputs": [],
+      "variable output (tonne/tonne)": {},
+      "constant output (tonne)": {},
+      "revenue ($/tonne)": [12.0, 12.0, 12.0, 12.0],
+      "collection cost ($/tonne)": {},
+      "operating cost ($)": 150.0,
+      "disposal limit (tonne)": {},
+      "disposal cost ($/tonne)": {}
+    }
+  },
+  "plants": {
+    "L1": {
+      "latitude (deg)": 44.881,
+      "longitude (deg)": -87.623,
+      "input mix (%)": {
+        "P1": 95.3,
+        "P2": 4.7
+      },
+      "output (tonne)": {
+        "P3": 0.25,
+        "P4": 0.12
+      },
+      "processing emissions (tonne)": {
+        "CO2": 0.1
+      },
+      "storage cost ($/tonne)": {
+        "P1": 0.1,
+        "P2": 0.1
+      },
+      "storage limit (tonne)": {
+        "P1": 100,
+        "P2": null
+      },
+      "disposal cost ($/tonne)": {
+        "P3": 0,
+        "P4": 0.86
+      },
+      "disposal limit (tonne)": {
+        "P3": null,
+        "P4": 1000.0
+      },
+      "capacities": [
+        {
+          "size (tonne)": 100,
+          "opening cost ($)": [300, 400, 450, 475],
+          "fixed operating cost ($)": 300,
+          "variable operating cost ($/tonne)": 5.0
+        },
+        {
+          "size (tonne)": 500,
+          "opening cost ($)": 1000.0,
+          "fixed operating cost ($)": 400.0,
+          "variable operating cost ($/tonne)": 5.0
+        }
+      ],
+      "initial capacity (tonne)": 250
+    }
+  },
+  "emissions": {
+    "CO2": {
+      "limit (tonne)": [1000.0, 1100.0, 1200.0, 1300.0],
+      "penalty ($/tonne)": [50.0, 55.0, 60.0, 65.0]
+    },
+    "CH4": {
+      "limit (tonne)": null,
+      "penalty ($/tonne)": 1200.0
+    }
+  }
+}

test/fixtures/storage.json

@@ -1,39 +0,0 @@
-{
-    "parameters": {
-        "time horizon (years)": 3
-    },
-    "products": {
-        "battery": {
-            "initial amounts": {
-                "Chicago": {
-                    "latitude (deg)": 0.0,
-                    "longitude (deg)": 0.0,
-                    "amount (tonne)": [100.0, 0.0, 0.0]
-                }
-            },
-            "transportation cost ($/km/tonne)": [0.01, 0.01, 0.01]
-        }
-    },
-    "plants": {
-        "mega plant": {
-            "input": "battery",
-            "locations": {
-                "Chicago": {
-                    "latitude (deg)": 0.0,
-                    "longitude (deg)": 0.0,
-                    "storage": {
-                        "cost ($/tonne)": [2.0, 1.5, 1.0],
-                        "limit (tonne)": 50.0
-                    },
-                    "capacities (tonne)": {
-                        "100": {
-                            "opening cost ($)": [0.0, 0.0, 0],
-                            "fixed operating cost ($)": [0.0, 0.0, 0.0],
-                            "variable operating cost ($/tonne)": [10.0, 5.0, 2.0]
-                        }
-                    }
-                }
-            }
-        }
-    }
-}

test/graph/build_test.jl

@@ -1,39 +0,0 @@
-# Copyright (C) 2020 Argonne National Laboratory
-# Written by Alinson Santos Xavier <axavier@anl.gov>
-
-using RELOG
-
-@testset "build_graph" begin
-    basedir = dirname(@__FILE__)
-    instance = RELOG.parsefile("$basedir/../../instances/s1.json")
-    graph = RELOG.build_graph(instance)
-    process_node_by_location_name =
-        Dict(n.location.location_name => n for n in graph.process_nodes)
-
-    @test length(graph.plant_shipping_nodes) == 8
-    @test length(graph.collection_shipping_nodes) == 10
-    @test length(graph.process_nodes) == 6
-
-    node = graph.collection_shipping_nodes[1]
-    @test node.location.name == "C1"
-    @test length(node.incoming_arcs) == 0
-    @test length(node.outgoing_arcs) == 2
-    @test node.outgoing_arcs[1].source.location.name == "C1"
-    @test node.outgoing_arcs[1].dest.location.plant_name == "F1"
-    @test node.outgoing_arcs[1].dest.location.location_name == "L1"
-    @test node.outgoing_arcs[1].values["distance"] == 1095.62
-
-    node = process_node_by_location_name["L1"]
-    @test node.location.plant_name == "F1"
-    @test node.location.location_name == "L1"
-    @test length(node.incoming_arcs) == 10
-    @test length(node.outgoing_arcs) == 2
-
-    node = process_node_by_location_name["L3"]
-    @test node.location.plant_name == "F2"
-    @test node.location.location_name == "L3"
-    @test length(node.incoming_arcs) == 2
-    @test length(node.outgoing_arcs) == 2
-
-    @test length(graph.arcs) == 38
-end

test/instance/compress_test.jl

@@ -1,53 +0,0 @@
-# Copyright (C) 2020 Argonne National Laboratory
-# Written by Alinson Santos Xavier <axavier@anl.gov>
-
-using RELOG
-
-@testset "compress" begin
-    basedir = dirname(@__FILE__)
-    instance = RELOG.parsefile("$basedir/../../instances/s1.json")
-    compressed = RELOG._compress(instance)
-
-    product_name_to_product = Dict(p.name => p for p in compressed.products)
-    location_name_to_facility = Dict()
-    for p in compressed.plants
-        location_name_to_facility[p.location_name] = p
-    end
-    for c in compressed.collection_centers
-        location_name_to_facility[c.name] = c
-    end
-
-    p1 = product_name_to_product["P1"]
-    p2 = product_name_to_product["P2"]
-    p3 = product_name_to_product["P3"]
-    c1 = location_name_to_facility["C1"]
-    l1 = location_name_to_facility["L1"]
-
-    @test compressed.time == 1
-    @test compressed.building_period == [1]
-
-    @test p1.name == "P1"
-    @test p1.transportation_cost ≈ [0.015]
-    @test p1.transportation_energy ≈ [0.115]
-    @test p1.transportation_emissions["CO2"] ≈ [0.051]
-    @test p1.transportation_emissions["CH4"] ≈ [0.0025]
-
-    @test c1.name == "C1"
-    @test c1.amount ≈ [1869.12]
-
-    @test l1.plant_name == "F1"
-    @test l1.location_name == "L1"
-    @test l1.energy ≈ [0.115]
-    @test l1.emissions["CO2"] ≈ [0.051]
-    @test l1.emissions["CH4"] ≈ [0.0025]
-    @test l1.sizes[1].opening_cost ≈ [500]
-    @test l1.sizes[2].opening_cost ≈ [1250]
-    @test l1.sizes[1].fixed_operating_cost ≈ [60]
-    @test l1.sizes[2].fixed_operating_cost ≈ [60]
-    @test l1.sizes[1].variable_operating_cost ≈ [30]
-    @test l1.sizes[2].variable_operating_cost ≈ [30]
-    @test l1.disposal_limit[p2] ≈ [2.0]
-    @test l1.disposal_limit[p3] ≈ [2.0]
-    @test l1.disposal_cost[p2] ≈ [-10.0]
-    @test l1.disposal_cost[p3] ≈ [-10.0]
-end

test/instance/geodb_test.jl

@@ -1,25 +0,0 @@
-# RELOG: Reverse Logistics Optimization
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-using RELOG
-
-@testset "geodb_query (2018-us-county)" begin
-    region = RELOG.geodb_query("2018-us-county:17043")
-    @test region.centroid.lat == 41.83956
-    @test region.centroid.lon == -88.08857
-    @test region.population == 922_921
-end
-
-# @testset "geodb_query (2018-us-zcta)" begin
-#     region = RELOG.geodb_query("2018-us-zcta:60439")
-#     @test region.centroid.lat == 41.68241
-#     @test region.centroid.lon == -87.98954
-# end
-
-@testset "geodb_query (us-state)" begin
-    region = RELOG.geodb_query("us-state:IL")
-    @test region.centroid.lat == 39.73939
-    @test region.centroid.lon == -89.50414
-    @test region.population == 12_671_821
-end

test/instance/parse_test.jl

@@ -1,86 +0,0 @@
-# Copyright (C) 2020 Argonne National Laboratory
-# Written by Alinson Santos Xavier <axavier@anl.gov>
-
-using RELOG
-
-@testset "parse" begin
-    basedir = dirname(@__FILE__)
-    instance = RELOG.parsefile("$basedir/../../instances/s1.json")
-
-    centers = instance.collection_centers
-    plants = instance.plants
-    products = instance.products
-    location_name_to_plant = Dict(p.location_name => p for p in plants)
-    product_name_to_product = Dict(p.name => p for p in products)
-
-    @test length(centers) == 10
-    @test centers[1].name == "C1"
-    @test centers[1].latitude == 7
-    @test centers[1].latitude == 7
-    @test centers[1].longitude == 7
-    @test centers[1].amount == [934.56, 934.56]
-    @test centers[1].product.name == "P1"
-
-    @test length(plants) == 6
-
-    plant = location_name_to_plant["L1"]
-    @test plant.plant_name == "F1"
-    @test plant.location_name == "L1"
-    @test plant.input.name == "P1"
-    @test plant.latitude == 0
-    @test plant.longitude == 0
-
-    @test length(plant.sizes) == 2
-    @test plant.sizes[1].capacity == 250
-    @test plant.sizes[1].opening_cost == [500, 500]
-    @test plant.sizes[1].fixed_operating_cost == [30, 30]
-    @test plant.sizes[1].variable_operating_cost == [30, 30]
-    @test plant.sizes[2].capacity == 1000
-    @test plant.sizes[2].opening_cost == [1250, 1250]
-    @test plant.sizes[2].fixed_operating_cost == [30, 30]
-    @test plant.sizes[2].variable_operating_cost == [30, 30]
-
-    p2 = product_name_to_product["P2"]
-    p3 = product_name_to_product["P3"]
-    @test length(plant.output) == 2
-    @test plant.output[p2] == 0.2
-    @test plant.output[p3] == 0.5
-    @test plant.disposal_limit[p2] == [1, 1]
-    @test plant.disposal_limit[p3] == [1, 1]
-    @test plant.disposal_cost[p2] == [-10, -10]
-    @test plant.disposal_cost[p3] == [-10, -10]
-
-    plant = location_name_to_plant["L3"]
-    @test plant.location_name == "L3"
-    @test plant.input.name == "P2"
-    @test plant.latitude == 25
-    @test plant.longitude == 65
-
-    @test length(plant.sizes) == 2
-    @test plant.sizes[1].capacity == 1000.0
-    @test plant.sizes[1].opening_cost == [3000, 3000]
-    @test plant.sizes[1].fixed_operating_cost == [50, 50]
-    @test plant.sizes[1].variable_operating_cost == [50, 50]
-    @test plant.sizes[1] == plant.sizes[2]
-
-    p4 = product_name_to_product["P4"]
-    @test plant.output[p3] == 0.05
-    @test plant.output[p4] == 0.8
-    @test plant.disposal_limit[p3] == [1e8, 1e8]
-    @test plant.disposal_limit[p4] == [0, 0]
-end
-
-@testset "parse (geodb)" begin
-    basedir = dirname(@__FILE__)
-    instance = RELOG.parsefile("$basedir/../../instances/s2.json")
-
-    centers = instance.collection_centers
-    @test centers[1].name == "C1"
-    @test centers[1].latitude == 41.83956
-    @test centers[1].longitude == -88.08857
-end
-
-# @testset "parse (invalid)" begin
-#     basedir = dirname(@__FILE__)
-#     @test_throws ErrorException RELOG.parsefile("$basedir/../fixtures/s1-wrong-length.json")
-# end

test/model/build_test.jl

@@ -1,38 +0,0 @@
-# Copyright (C) 2020 Argonne National Laboratory
-# Written by Alinson Santos Xavier <axavier@anl.gov>
-
-using RELOG, Cbc, JuMP, Printf, JSON, MathOptInterface.FileFormats
-
-@testset "build" begin
-    basedir = dirname(@__FILE__)
-    instance = RELOG.parsefile("$basedir/../../instances/s1.json")
-    graph = RELOG.build_graph(instance)
-    model = RELOG.build_model(instance, graph, Cbc.Optimizer)
-    set_optimizer_attribute(model, "logLevel", 0)
-
-    process_node_by_location_name =
-        Dict(n.location.location_name => n for n in graph.process_nodes)
-
-    shipping_node_by_loc_and_prod_names = Dict(
-        (n.location.location_name, n.product.name) => n for n in graph.plant_shipping_nodes
-    )
-
-    @test length(model[:flow]) == 76
-    @test length(model[:dispose]) == 16
-    @test length(model[:open_plant]) == 12
-    @test length(model[:capacity]) == 12
-    @test length(model[:expansion]) == 12
-
-    l1 = process_node_by_location_name["L1"]
-    v = model[:capacity][l1, 1]
-    @test lower_bound(v) == 0.0
-    @test upper_bound(v) == 1000.0
-
-    v = model[:expansion][l1, 1]
-    @test lower_bound(v) == 0.0
-    @test upper_bound(v) == 750.0
-
-    v = model[:dispose][shipping_node_by_loc_and_prod_names["L1", "P2"], 1]
-    @test lower_bound(v) == 0.0
-    @test upper_bound(v) == 1.0
-end

test/model/solve_test.jl

@@ -1,61 +0,0 @@
-# Copyright (C) 2020 Argonne National Laboratory
-# Written by Alinson Santos Xavier <axavier@anl.gov>
-
-using RELOG, Cbc, JuMP, Printf, JSON, MathOptInterface.FileFormats
-
-basedir = dirname(@__FILE__)
-
-@testset "solve (exact)" begin
-    solution_filename_a = tempname()
-    solution_filename_b = tempname()
-    solution = RELOG.solve("$basedir/../../instances/s1.json", output = solution_filename_a)
-
-    @test isfile(solution_filename_a)
-
-    RELOG.write(solution, solution_filename_b)
-    @test isfile(solution_filename_b)
-
-    @test "Costs" in keys(solution)
-    @test "Fixed operating (\$)" in keys(solution["Costs"])
-    @test "Transportation (\$)" in keys(solution["Costs"])
-    @test "Variable operating (\$)" in keys(solution["Costs"])
-    @test "Total (\$)" in keys(solution["Costs"])
-
-    @test "Plants" in keys(solution)
-    @test "F1" in keys(solution["Plants"])
-    @test "F2" in keys(solution["Plants"])
-    @test "F3" in keys(solution["Plants"])
-    @test "F4" in keys(solution["Plants"])
-end
-
-@testset "solve (heuristic)" begin
-    # Should not crash
-    solution = RELOG.solve("$basedir/../../instances/s1.json", heuristic = true)
-end
-
-@testset "solve (infeasible)" begin
-    json = JSON.parsefile("$basedir/../../instances/s1.json")
-    for (location_name, location_dict) in json["products"]["P1"]["initial amounts"]
-        location_dict["amount (tonne)"] *= 1000
-    end
-    RELOG.solve(RELOG.parse(json))
-end
-
-@testset "solve (with storage)" begin
-    basedir = dirname(@__FILE__)
-    filename = "$basedir/../fixtures/storage.json"
-    instance = RELOG.parsefile(filename)
-    @test instance.plants[1].storage_limit == 50.0
-    @test instance.plants[1].storage_cost == [2.0, 1.5, 1.0]
-
-    solution = RELOG.solve(filename)
-    plant_dict = solution["Plants"]["mega plant"]["Chicago"]
-    @test plant_dict["Variable operating cost (\$)"] == [500.0, 0.0, 100.0]
-    @test plant_dict["Process (tonne)"] == [50.0, 0.0, 50.0]
-    @test plant_dict["Storage (tonne)"] == [50.0, 50.0, 0.0]
-    @test plant_dict["Storage cost (\$)"] == [100.0, 75.0, 0.0]
-
-    @test solution["Costs"]["Variable operating (\$)"] == [500.0, 0.0, 100.0]
-    @test solution["Costs"]["Storage (\$)"] == [100.0, 75.0, 0.0]
-    @test solution["Costs"]["Total (\$)"] == [600.0, 75.0, 100.0]
-end

test/reports_test.jl

@@ -1,18 +0,0 @@
-# RELOG: Reverse Logistics Optimization
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-using RELOG, JSON, GZip
-
-@testset "Reports" begin
-    @testset "from solve" begin
-        solution = RELOG.solve("$(pwd())/../instances/s1.json")
-        tmp_filename = tempname()
-        # The following should not crash
-        RELOG.write_plants_report(solution, tmp_filename)
-        RELOG.write_plant_outputs_report(solution, tmp_filename)
-        RELOG.write_plant_emissions_report(solution, tmp_filename)
-        RELOG.write_transportation_report(solution, tmp_filename)
-        RELOG.write_transportation_emissions_report(solution, tmp_filename)
-    end
-end

test/runtests.jl

@@ -1,20 +0,0 @@
-# Copyright (C) 2020 Argonne National Laboratory
-# Written by Alinson Santos Xavier <axavier@anl.gov>
-
-using Test
-
-@testset "RELOG" begin
-    @testset "Instance" begin
-        include("instance/compress_test.jl")
-        include("instance/geodb_test.jl")
-        include("instance/parse_test.jl")
-    end
-    @testset "Graph" begin
-        include("graph/build_test.jl")
-    end
-    @testset "Model" begin
-        include("model/build_test.jl")
-        include("model/solve_test.jl")
-    end
-    include("reports_test.jl")
-end

test/src/RELOGT.jl

@@ -0,0 +1,38 @@
+module RELOGT
+
+using Test
+using RELOG
+using JuliaFormatter
+
+include("instance/parse_test.jl")
+include("model/build_test.jl")
+include("model/dist_test.jl")
+include("model/jumpext_test.jl")
+include("reports_test.jl")
+include("../fixtures/boat_example.jl")
+
+basedir = dirname(@__FILE__)
+
+function fixture(path::String)::String
+    return "$basedir/../fixtures/$path"
+end
+
+function runtests()
+    @testset "RELOG" begin
+        instance_parse_test_1()
+        instance_parse_test_2()
+        model_build_test()
+        model_dist_test()
+        report_tests()
+        jumpext_test()
+    end
+    return
+end
+
+function format()
+    JuliaFormatter.format(basedir, verbose = true)
+    JuliaFormatter.format("$basedir/../../src", verbose = true)
+    JuliaFormatter.format("$basedir/../fixtures", verbose = true)
+    return
+end
+end # module RELOGT

test/src/instance/parse_test.jl

@@ -0,0 +1,90 @@
+using RELOG
+using Test
+using OrderedCollections
+
+function instance_parse_test_1()
+    instance = RELOG.parsefile(fixture("simple.json"))
+
+    # Parameters
+    @test instance.time_horizon == 4
+    @test instance.building_period == [1]
+    @test instance.distance_metric isa RELOG.EuclideanDistance
+
+    # Products
+    @test length(instance.products) == 4
+    p1 = instance.products[1]
+    @test p1.name == "P1"
+    @test p1.tr_cost == [0.015, 0.015, 0.015, 0.015]
+    @test p1.tr_energy == [0.12, 0.12, 0.12, 0.12]
+    @test p1.tr_emissions ==
+          Dict("CO2" => [0.052, 0.052, 0.052, 0.052], "CH4" => [0.003, 0.003, 0.003, 0.003])
+    @test p1.disposal_limit == [1.0, 1.0, 1.0, 1.0]
+    @test instance.products_by_name["P1"] === p1
+    p2 = instance.products[2]
+    p3 = instance.products[3]
+    p4 = instance.products[4]
+
+    # Centers
+    @test length(instance.centers) == 3
+    c1 = instance.centers[1]
+    @test c1.latitude == 41.881
+    @test c1.longitude == -87.623
+    @test c1.input === p1
+    @test c1.outputs == [p2, p3]
+    @test c1.fixed_output == Dict(p2 => [100, 50, 0, 0], p3 => [20, 10, 0, 0])
+    @test c1.var_output == Dict(p2 => [0.2, 0.25, 0.12], p3 => [0.25, 0.25, 0.25])
+    @test c1.revenue == [12.0, 12.0, 12.0, 12.0]
+    @test c1.operating_cost == [150.0, 150.0, 150.0, 150.0]
+    @test c1.disposal_limit == Dict(p2 => [0, 0, 0, 0], p3 => [Inf, Inf, Inf, Inf])
+    @test c1.disposal_cost ==
+          Dict(p2 => [0.23, 0.23, 0.23, 0.23], p3 => [1.0, 1.0, 1.0, 1.0])
+    c2 = instance.centers[2]
+    @test c2.input === nothing
+    @test c2.revenue == [0, 0, 0, 0]
+
+    # Plants
+    @test length(instance.plants) == 1
+    l1 = instance.plants[1]
+    @test l1.latitude == 44.881
+    @test l1.longitude == -87.623
+    @test l1.input_mix ==
+          Dict(p1 => [0.953, 0.953, 0.953, 0.953], p2 => [0.047, 0.047, 0.047, 0.047])
+    @test l1.output == Dict(p3 => [0.25, 0.25, 0.25, 0.25], p4 => [0.12, 0.12, 0.12, 0.12])
+    @test l1.emissions == Dict("CO2" => [0.1, 0.1, 0.1, 0.1])
+    @test l1.storage_cost == Dict(p1 => [0.1, 0.1, 0.1, 0.1], p2 => [0.1, 0.1, 0.1, 0.1])
+    @test l1.storage_limit == Dict(p1 => [100, 100, 100, 100], p2 => [Inf, Inf, Inf, Inf])
+    @test l1.disposal_cost == Dict(p3 => [0, 0, 0, 0], p4 => [0.86, 0.86, 0.86, 0.86])
+    @test l1.disposal_limit ==
+          Dict(p3 => [Inf, Inf, Inf, Inf], p4 => [1000.0, 1000.0, 1000.0, 1000.0])
+    @test l1.initial_capacity == 250
+    @test length(l1.capacities) == 2
+    c1 = l1.capacities[1]
+    @test c1.size == 100
+    @test c1.opening_cost == [300, 400, 450, 475]
+    @test c1.fix_operating_cost == [300, 300, 300, 300]
+    @test c1.var_operating_cost == [5, 5, 5, 5]
+    c2 = l1.capacities[2]
+    @test c2.size == 500
+    @test c2.opening_cost == [1000, 1000, 1000, 1000]
+    @test c2.fix_operating_cost == [400, 400, 400, 400]
+    @test c2.var_operating_cost == [5, 5, 5, 5]
+
+    # Emissions
+    @test length(instance.emissions) == 2
+    co2 = instance.emissions[1]
+    @test co2.name == "CO2"
+    @test co2.limit == [1000.0, 1100.0, 1200.0, 1300.0]
+    @test co2.penalty == [50.0, 55.0, 60.0, 65.0]
+    @test instance.emissions_by_name["CO2"] === co2
+    ch4 = instance.emissions[2]
+    @test ch4.name == "CH4"
+    @test ch4.limit == [Inf, Inf, Inf, Inf]
+    @test ch4.penalty == [1200.0, 1200.0, 1200.0, 1200.0]
+    @test instance.emissions_by_name["CH4"] === ch4
+end
+
+
+function instance_parse_test_2()
+    # Should not crash
+    RELOG.parsefile(fixture("boat_example.json"))
+end

test/src/model/build_test.jl

@@ -0,0 +1,222 @@
+using RELOG
+using Test
+using HiGHS
+using JuMP
+
+function model_build_test()
+    instance = RELOG.parsefile(fixture("simple.json"))
+    model = RELOG.build_model(instance, optimizer = HiGHS.Optimizer, variable_names = true)
+    y = model[:y]
+    z_disp = model[:z_disp]
+    z_input = model[:z_input]
+    z_process = model[:z_process]
+    z_storage = model[:z_storage]
+    z_em_tr = model[:z_em_tr]
+    z_em_plant = model[:z_em_plant]
+    z_exp = model[:z_exp]
+    x = model[:x]
+    obj = objective_function(model)
+    # print(model)
+
+    @test obj.terms[y["L1", "C3", "P4", 1]] == (
+        111.118 * 0.015 # transportation
+        - 12.0 # revenue
+    )
+    @test obj.terms[y["C1", "L1", "P2", 4]] == (
+        333.262 * 0.015 +  # transportation
+        0.25 + # center collection cost
+        5.0 # plant operating cost
+    )
+    @test obj.terms[z_disp["C1", "P2", 1]] == 0.23
+    @test obj.constant == (
+        150 * 4 * 3 # center operating cost
+        - 300 # initial opening cost
+        - 150 * 1.75 # initial expansion
+    )
+    @test obj.terms[z_disp["L1", "P4", 2]] == 0.86
+    @test obj.terms[x["L1", 1]] == (
+        -100.0 + # opening cost
+        300 # fixed operating cost
+    )
+    @test obj.terms[x["L1", 2]] == (
+        -50.0 + # opening cost
+        300 # fixed operating cost
+    )
+    @test obj.terms[x["L1", 3]] == (
+        -25.0 + # opening cost
+        300 # fixed operating cost
+    )
+    @test obj.terms[x["L1", 4]] == (
+        475.0 + # opening cost
+        300 # fixed operating cost
+    )
+
+    # Test expansion variables exist and have correct initial values
+    @test z_exp["L1", 0] == 150.0  # initial_capacity (250) - min_capacity (100)
+    @test haskey(z_exp, ("L1", 1))
+    @test haskey(z_exp, ("L1", 2))
+    @test haskey(z_exp, ("L1", 3))
+    @test haskey(z_exp, ("L1", 4))
+
+    # Test expansion costs in objective function
+    # R_expand[1] = (1000 - 300) / (500 - 100) = 1.75
+    # R_expand[2] = (1000 - 400) / (500 - 100) = 1.5
+    # R_fix_exp[1] = (400 - 300) / (500 - 100) = 0.25
+    @test obj.terms[z_exp["L1", 1]] == (
+        +1.75  # expansion cost[1]
+        - 1.5  # expansion cost[2]
+        + 0.25   # fixed operating cost[1]
+    )
+
+    # Test storage cost in objective function
+    @test obj.terms[z_storage["L1", "P1", 1]] == 0.1  # P1 storage cost
+    @test obj.terms[z_storage["L1", "P2", 1]] == 0.1  # P2 storage cost
+
+    # Variables: Transportation emissions
+    @test haskey(z_em_tr, ("CO2", "L1", "C3", "P4", 1))
+    @test haskey(z_em_tr, ("CH4", "L1", "C3", "P4", 1))
+    @test haskey(z_em_tr, ("CO2", "C2", "L1", "P1", 1))
+    @test haskey(z_em_tr, ("CH4", "C2", "L1", "P1", 1))
+
+    # Variables: Plant emissions
+    @test haskey(z_em_plant, ("CO2", "L1", 1))
+    @test haskey(z_em_plant, ("CO2", "L1", 2))
+    @test haskey(z_em_plant, ("CO2", "L1", 3))
+    @test haskey(z_em_plant, ("CO2", "L1", 4))
+
+    # Plants: Definition of total plant input
+    @test repr(model[:eq_z_input]["L1", 1]) ==
+          "eq_z_input[L1,1] : -y[C2,L1,P1,1] - y[C1,L1,P2,1] + z_input[L1,1] = 0"
+
+    # Plants: Definition of total processing amount
+    @test repr(model[:eq_z_process]["L1", 1]) ==
+          "eq_z_process[L1,1] : -z_input[L1,1] + z_storage[L1,P1,1] + z_storage[L1,P2,1] + z_process[L1,1] = 0"
+
+    # Plants: Processing mix must have correct proportion
+    @test repr(model[:eq_process_mix]["L1", "P1", 1]) ==
+          "eq_process_mix[L1,P1,1] : y[C2,L1,P1,1] - z_storage[L1,P1,1] - 0.953 z_process[L1,1] = 0"
+    @test repr(model[:eq_process_mix]["L1", "P2", 1]) ==
+          "eq_process_mix[L1,P2,1] : y[C1,L1,P2,1] - z_storage[L1,P2,1] - 0.047 z_process[L1,1] = 0"
+
+    # Plants: Calculate amount produced
+    @test repr(model[:eq_z_prod]["L1", "P3", 1]) ==
+          "eq_z_prod[L1,P3,1] : z_prod[L1,P3,1] - 0.25 z_process[L1,1] = 0"
+    @test repr(model[:eq_z_prod]["L1", "P4", 1]) ==
+          "eq_z_prod[L1,P4,1] : z_prod[L1,P4,1] - 0.12 z_process[L1,1] = 0"
+
+    # Plants: Produced material must be sent or disposed
+    @test repr(model[:eq_balance]["L1", "P3", 1]) ==
+          "eq_balance[L1,P3,1] : z_prod[L1,P3,1] - z_disp[L1,P3,1] = 0"
+    @test repr(model[:eq_balance]["L1", "P4", 1]) ==
+          "eq_balance[L1,P4,1] : -y[L1,C3,P4,1] + z_prod[L1,P4,1] - z_disp[L1,P4,1] = 0"
+
+    # Plants: Processing limit (capacity constraint)
+    @test repr(model[:eq_process_limit]["L1", 1]) ==
+          "eq_process_limit[L1,1] : -100 x[L1,1] - z_exp[L1,1] + z_process[L1,1] ≤ 0"
+
+    # Plants: Expansion upper bound
+    @test repr(model[:eq_exp_ub]["L1", 1]) ==
+          "eq_exp_ub[L1,1] : -400 x[L1,1] + z_exp[L1,1] ≤ 0"
+
+    # Plants: Disposal limit
+    @test repr(model[:eq_disposal_limit]["L1", "P4", 1]) ==
+          "eq_disposal_limit[L1,P4,1] : z_disp[L1,P4,1] ≤ 1000"
+    @test ("L1", "P3", 1) ∉ keys(model[:eq_disposal_limit])
+
+    # Plants: Plant remains open
+    @test repr(model[:eq_keep_open]["L1", 4]) ==
+          "eq_keep_open[L1,4] : -x[L1,3] + x[L1,4] ≥ 0"
+    @test repr(model[:eq_keep_open]["L1", 1]) == "eq_keep_open[L1,1] : x[L1,1] ≥ 1"
+
+    # Plants: Capacity cannot decrease over time
+    @test repr(model[:eq_capacity_nondecreasing]["L1", 4]) ==
+          "eq_capacity_nondecreasing[L1,4] : -z_exp[L1,3] + z_exp[L1,4] ≥ 0"
+    @test repr(model[:eq_capacity_nondecreasing]["L1", 1]) ==
+          "eq_capacity_nondecreasing[L1,1] : z_exp[L1,1] ≥ 150"
+
+    # Plants: Building period
+    @test ("L1", 1) ∉ keys(model[:eq_building_period])
+    @test repr(model[:eq_building_period]["L1", 2]) ==
+          "eq_building_period[L1,2] : -x[L1,1] + x[L1,2] ≤ 0"
+
+    # Centers: Definition of total center input
+    @test repr(model[:eq_z_input]["C1", 1]) ==
+          "eq_z_input[C1,1] : -y[C2,C1,P1,1] + z_input[C1,1] = 0"
+
+    # Centers: Calculate amount collected
+    @test repr(model[:eq_z_collected]["C1", "P2", 1]) ==
+          "eq_z_collected[C1,P2,1] : -0.2 z_input[C1,1] + z_collected[C1,P2,1] = 100"
+    @test repr(model[:eq_z_collected]["C1", "P2", 2]) ==
+          "eq_z_collected[C1,P2,2] : -0.25 z_input[C1,1] - 0.2 z_input[C1,2] + z_collected[C1,P2,2] = 50"
+    @test repr(model[:eq_z_collected]["C1", "P2", 3]) ==
+          "eq_z_collected[C1,P2,3] : -0.12 z_input[C1,1] - 0.25 z_input[C1,2] - 0.2 z_input[C1,3] + z_collected[C1,P2,3] = 0"
+    @test repr(model[:eq_z_collected]["C1", "P2", 4]) ==
+          "eq_z_collected[C1,P2,4] : -0.12 z_input[C1,2] - 0.25 z_input[C1,3] - 0.2 z_input[C1,4] + z_collected[C1,P2,4] = 0"
+
+    # Centers: Collected products must be disposed or sent
+    @test repr(model[:eq_balance]["C1", "P2", 1]) ==
+          "eq_balance[C1,P2,1] : -y[C1,L1,P2,1] - z_disp[C1,P2,1] + z_collected[C1,P2,1] = 0"
+    @test repr(model[:eq_balance]["C1", "P3", 1]) ==
+          "eq_balance[C1,P3,1] : -z_disp[C1,P3,1] + z_collected[C1,P3,1] = 0"
+
+    # Centers: Disposal limit
+    @test repr(model[:eq_disposal_limit]["C1", "P2", 1]) ==
+          "eq_disposal_limit[C1,P2,1] : z_disp[C1,P2,1] ≤ 0"
+    @test ("C1", "P3", 1) ∉ keys(model[:eq_disposal_limit])
+
+    # Global disposal limit
+    @test repr(model[:eq_disposal_limit]["P1", 1]) ==
+          "eq_disposal_limit[P1,1] : z_disp[C2,P1,1] ≤ 1"
+    @test repr(model[:eq_disposal_limit]["P2", 1]) ==
+          "eq_disposal_limit[P2,1] : z_disp[C1,P2,1] ≤ 2"
+    @test repr(model[:eq_disposal_limit]["P3", 1]) ==
+          "eq_disposal_limit[P3,1] : z_disp[L1,P3,1] + z_disp[C1,P3,1] ≤ 5"
+    @test ("P4", 1) ∉ keys(model[:eq_disposal_limit])
+
+    # Products: Transportation emissions
+    @test repr(model[:eq_emission_tr]["CH4", "L1", "C3", "P4", 1]) ==
+          "eq_emission_tr[CH4,L1,C3,P4,1] : -0.333354 y[L1,C3,P4,1] + z_em_tr[CH4,L1,C3,P4,1] = 0"
+
+    # Plants: Plant emissions (updated to use z_process)
+    @test repr(model[:eq_emission_plant]["CO2", "L1", 1]) ==
+          "eq_emission_plant[CO2,L1,1] : -0.1 z_process[L1,1] + z_em_plant[CO2,L1,1] = 0"
+
+    # Objective function: Emissions penalty costs
+    @test obj.terms[z_em_plant["CO2", "L1", 1]] == 50.0  # CO2 penalty at time 1
+    @test obj.terms[z_em_plant["CO2", "L1", 2]] == 55.0  # CO2 penalty at time 2
+    @test obj.terms[z_em_plant["CO2", "L1", 3]] == 60.0  # CO2 penalty at time 3
+    @test obj.terms[z_em_plant["CO2", "L1", 4]] == 65.0  # CO2 penalty at time 4
+    @test obj.terms[z_em_tr["CO2", "L1", "C3", "P4", 1]] == 50.0  # CO2 transportation penalty at time 1
+    @test obj.terms[z_em_tr["CH4", "L1", "C3", "P4", 1]] == 1200.0  # CH4 transportation penalty at time 1
+
+    # Global emissions limit constraints
+    @test repr(model[:eq_emission_limit]["CO2", 1]) ==
+          "eq_emission_limit[CO2,1] : z_em_tr[CO2,C2,L1,P1,1] + z_em_tr[CO2,C2,C1,P1,1] + z_em_tr[CO2,C1,L1,P2,1] + z_em_tr[CO2,L1,C3,P4,1] + z_em_plant[CO2,L1,1] ≤ 1000"
+    @test ("CH4", 1) ∉ keys(model[:eq_emission_limit])
+
+    # Test storage variables exist
+    @test haskey(z_storage, ("L1", "P1", 1))
+    @test haskey(z_storage, ("L1", "P2", 1))
+    @test haskey(z_process, ("L1", 1))
+    @test haskey(z_process, ("L1", 2))
+    @test haskey(z_process, ("L1", 3))
+    @test haskey(z_process, ("L1", 4))
+
+    # Test initial storage values
+    @test z_storage["L1", "P1", 0] == 0
+    @test z_storage["L1", "P2", 0] == 0
+
+    # Test storage limit constraints (P1 has limit of 100, P2 has no limit)
+    @test haskey(model[:eq_storage_limit], ("L1", "P1", 1))
+    @test repr(model[:eq_storage_limit]["L1", "P1", 1]) ==
+          "eq_storage_limit[L1,P1,1] : z_storage[L1,P1,1] ≤ 100"
+    @test ("L1", "P2", 1) ∉ keys(model[:eq_storage_limit])  # P2 has no storage limit
+
+    # Test final storage constraints exist
+    @test haskey(model[:eq_storage_final], ("L1", "P1"))
+    @test haskey(model[:eq_storage_final], ("L1", "P2"))
+    @test repr(model[:eq_storage_final]["L1", "P1"]) ==
+          "eq_storage_final[L1,P1] : z_storage[L1,P1,4] = 0"
+    @test repr(model[:eq_storage_final]["L1", "P2"]) ==
+          "eq_storage_final[L1,P2] : z_storage[L1,P2,4] = 0"
+end

test/src/model/dist_test.jl

@@ -0,0 +1,25 @@
+# RELOG: Reverse Logistics Optimization
+# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+# Released under the modified BSD license. See COPYING.md for more details.
+
+using RELOG
+
+function model_dist_test()
+    # Euclidean distance between Chicago and Indianapolis
+    @test RELOG._calculate_distance(
+        41.866,
+        -87.656,
+        39.764,
+        -86.148,
+        RELOG.EuclideanDistance(),
+    ) == 265.818
+
+    # Driving distance between Chicago and Indianapolis
+    @test RELOG._calculate_distance(
+        41.866,
+        -87.656,
+        39.764,
+        -86.148,
+        RELOG.KnnDrivingDistance(),
+    ) == 316.43
+end

test/src/model/jumpext_test.jl

@@ -0,0 +1,144 @@
+# RELOG: Reverse Logistics Optimization
+# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+# Released under the modified BSD license. See COPYING.md for more details.
+
+using RELOG
+using JuMP
+using HiGHS
+using Test
+
+function jumpext_test()
+    jumpext_pwl_single_point()
+    jumpext_pwl_two_points()
+    jumpext_pwl_multiple_points()
+    jumpext_pwl_input_validation()
+    return
+end
+
+function jumpext_pwl_single_point()
+    model = Model(HiGHS.Optimizer)
+    set_silent(model)
+    @variable(model, x)
+    @variable(model, y1)
+    @variable(model, y2)
+    xpts = [5.0]
+    ypts = [10.0 20.0]
+    RELOG._add_pwl_constraints(model, x, [y1, y2], xpts, ypts)
+    optimize!(model)
+    @test is_solved_and_feasible(model)
+    @test value(x) ≈ 5.0 atol = 1e-6
+    @test value(y1) ≈ 10.0 atol = 1e-6
+    @test value(y2) ≈ 20.0 atol = 1e-6
+    return
+end
+
+function jumpext_pwl_two_points()
+    model = Model(HiGHS.Optimizer)
+    set_silent(model)
+    @variable(model, x)
+    @variable(model, y1)
+    @variable(model, y2)
+    xpts = [0.0, 2.0]
+    ypts = [0.0 10.0; 4.0 6.0]
+    RELOG._add_pwl_constraints(model, x, [y1, y2], xpts, ypts)
+
+    # Test at x = 1
+    JuMP.fix(x, 1.0)
+    optimize!(model)
+    @test is_solved_and_feasible(model)
+    @test value(y1) ≈ 2.0 atol = 1e-6
+    @test value(y2) ≈ 8.0 atol = 1e-6
+
+    # Test at x = 2
+    JuMP.fix(x, 2.0)
+    optimize!(model)
+    @test is_solved_and_feasible(model)
+    @test value(y1) ≈ 4.0 atol = 1e-6
+    @test value(y2) ≈ 6.0 atol = 1e-6
+    return
+end
+
+function jumpext_pwl_multiple_points()
+    model = Model(HiGHS.Optimizer)
+    set_silent(model)
+    @variable(model, x)
+    @variable(model, y1)
+    @variable(model, y2)
+    xpts = [0.0, 1.0, 2.0]
+    ypts = [0.0 5.0; 2.0 3.0; 1.0 4.0]
+    RELOG._add_pwl_constraints(model, x, [y1, y2], xpts, ypts)
+
+    # Test at x = 0.5
+    JuMP.fix(x, 0.5)
+    optimize!(model)
+    @test is_solved_and_feasible(model)
+    @test value(y1) ≈ 1.0 atol = 1e-6
+    @test value(y2) ≈ 4.0 atol = 1e-6
+
+    # Test at x = 1
+    JuMP.fix(x, 1.0)
+    optimize!(model)
+    @test is_solved_and_feasible(model)
+    @test value(y1) ≈ 2.0 atol = 1e-6
+    @test value(y2) ≈ 3.0 atol = 1e-6
+
+    # Test at x = 1.5
+    JuMP.fix(x, 1.5)
+    optimize!(model)
+    @test is_solved_and_feasible(model)
+    @test value(y1) ≈ 1.5 atol = 1e-6
+    @test value(y2) ≈ 3.5 atol = 1e-6
+    return
+end
+
+function jumpext_pwl_input_validation()
+    model = Model(HiGHS.Optimizer)
+    @variable(model, x)
+    @variable(model, y)
+
+    # Test non-matrix ypts
+    @test_throws ArgumentError RELOG._add_pwl_constraints(model, x, [y], [1.0], [1.0])
+
+    # Test mismatched dimensions
+    @test_throws ArgumentError RELOG._add_pwl_constraints(
+        model,
+        x,
+        [y],
+        [1.0, 2.0],
+        [1.0 2.0],
+    )
+    @test_throws ArgumentError RELOG._add_pwl_constraints(
+        model,
+        x,
+        [y],
+        [1.0],
+        [1.0 2.0; 3.0 4.0],
+    )
+
+    # Test empty breakpoints
+    @test_throws ArgumentError RELOG._add_pwl_constraints(
+        model,
+        x,
+        [y],
+        Float64[],
+        Matrix{Float64}(undef, 0, 1),
+    )
+
+    # Test non-increasing x points
+    @test_throws ArgumentError RELOG._add_pwl_constraints(
+        model,
+        x,
+        [y],
+        [2.0, 1.0],
+        [1.0; 2.0],
+    )
+    @test_throws ArgumentError RELOG._add_pwl_constraints(
+        model,
+        x,
+        [y],
+        [1.0, 1.0],
+        [1.0; 2.0],
+    )
+
+    return
+end

test/src/reports_test.jl

@@ -0,0 +1,14 @@
+function report_tests()
+    # Load and solve the boat example
+    instance = RELOG.parsefile(fixture("boat_example.json"))
+    model = RELOG.build_model(instance, optimizer = HiGHS.Optimizer, variable_names = true)
+    optimize!(model)
+    mkpath("tmp")
+    write_to_file(model, "tmp/model.lp")
+    RELOG.write_plants_report(model, "tmp/plants.csv")
+    RELOG.write_plant_inputs_report(model, "tmp/plant_inputs.csv")
+    RELOG.write_plant_outputs_report(model, "tmp/plant_outputs.csv")
+    RELOG.write_centers_report(model, "tmp/centers.csv")
+    RELOG.write_center_outputs_report(model, "tmp/center_outputs.csv")
+    RELOG.write_transportation_report(model, "tmp/transportation.csv")
+end

web/.env

@@ -0,0 +1 @@
+FAST_REFRESH=false

web/.gitignore

@@ -0,0 +1,25 @@
+# See https://help.github.com/articles/ignoring-files/ for more about ignoring files.
+
+# dependencies
+/node_modules
+/.pnp
+.pnp.js
+
+# testing
+/coverage
+
+# production
+/build
+
+# misc
+.DS_Store
+.env.local
+.env.development.local
+.env.test.local
+.env.production.local
+
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+
+assets

web/.prettierrc.json

@@ -0,0 +1 @@
+{}

web/package.json

@@ -0,0 +1,65 @@
+{
+  "name": "web",
+  "version": "0.1.0",
+  "private": true,
+  "dependencies": {
+    "@fortawesome/fontawesome-svg-core": "^6.7.2",
+    "@fortawesome/free-regular-svg-icons": "^6.7.2",
+    "@fortawesome/free-solid-svg-icons": "^6.7.2",
+    "@fortawesome/react-fontawesome": "^0.2.2",
+    "@testing-library/dom": "^10.4.0",
+    "@testing-library/jest-dom": "^6.6.3",
+    "@testing-library/react": "^16.3.0",
+    "@testing-library/user-event": "^13.5.0",
+    "@types/jest": "^27.5.2",
+    "@types/node": "^16.18.126",
+    "@types/pako": "^2.0.3",
+    "@types/papaparse": "^5.3.16",
+    "@types/react": "^19.1.3",
+    "@types/react-dom": "^19.1.3",
+    "ajv": "^8.17.1",
+    "eslint": "^8.57.1",
+    "pako": "^2.1.0",
+    "papaparse": "^5.5.2",
+    "react": "^19.1.0",
+    "react-dom": "^19.1.0",
+    "react-scripts": "^5.0.1",
+    "tabulator-tables": "^6.3.1",
+    "typescript": "^4.9.5",
+    "web-vitals": "^2.1.4"
+  },
+  "scripts": {
+    "start": "react-scripts start",
+    "build": "react-scripts build",
+    "test": "react-scripts test",
+    "eject": "react-scripts eject"
+  },
+  "eslintConfig": {
+    "extends": [
+      "react-app",
+      "react-app/jest"
+    ],
+    "rules": {
+      "semi": [
+        "error",
+        "always"
+      ]
+    }
+  },
+  "browserslist": {
+    "production": [
+      ">0.2%",
+      "not dead",
+      "not op_mini all"
+    ],
+    "development": [
+      "last 1 chrome version",
+      "last 1 firefox version",
+      "last 1 safari version"
+    ]
+  },
+  "devDependencies": {
+    "@types/tabulator-tables": "^6.2.6",
+    "prettier": "3.5.3"
+  }
+}

web/public/index.html

@@ -0,0 +1,49 @@
+<!--
+  ~ RELOG: Supply Chain Analysis and Optimization
+  ~ Copyright (C) 2020-2025, UChicago Argonne, LLC. All rights reserved.
+  ~ Released under the modified BSD license. See COPYING.md for more details.
+  -->
+
+<!doctype html>
+<html lang="en">
+  <head>
+    <meta charset="utf-8" />
+    <link rel="icon" href="%PUBLIC_URL%/favicon.ico" />
+    <meta name="viewport" content="width=device-width, initial-scale=1" />
+    <meta name="theme-color" content="#000000" />
+    <meta name="description" content="RELOG Case Builder" />
+    <link rel="apple-touch-icon" href="%PUBLIC_URL%/logo192.png" />
+    <link rel="manifest" href="%PUBLIC_URL%/manifest.json" />
+    <title>Case Builder - RELOG</title>
+    <style>
+      :root {
+        --site-max-width: 1500px;
+        --site-min-width: 900px;
+        --box-border: 1px solid rgba(0, 0, 0, 0.2);
+        --box-shadow: 0px 2px 4px -3px rgba(0, 0, 0, 0.2);
+        --border-radius: 4px;
+        --primary: #0d6efd;
+        --contrast-100: #202020;
+        --contrast-80: #606060;
+        --contrast-60: #909090;
+        --contrast-20: #d6d6d6;
+        --contrast-10: #f6f6f6;
+        --contrast-0: #fefefe;
+      }
+      body {
+        margin: 0;
+        padding: 0;
+        font-family: Arial, sans-serif;
+        background-color: #333;
+      }
+      .content {
+        background-color: var(--contrast-10);
+        padding-bottom: 36px;
+      }
+    </style>
+  </head>
+  <body>
+    <noscript>You need to enable JavaScript to run this app.</noscript>
+    <div id="root"></div>
+  </body>
+</html>

web/public/manifest.json

@@ -0,0 +1,25 @@
+{
+  "short_name": "React App",
+  "name": "Create React App Sample",
+  "icons": [
+    {
+      "src": "favicon.ico",
+      "sizes": "64x64 32x32 24x24 16x16",
+      "type": "image/x-icon"
+    },
+    {
+      "src": "logo192.png",
+      "type": "image/png",
+      "sizes": "192x192"
+    },
+    {
+      "src": "logo512.png",
+      "type": "image/png",
+      "sizes": "512x512"
+    }
+  ],
+  "start_url": ".",
+  "display": "standalone",
+  "theme_color": "#000000",
+  "background_color": "#ffffff"
+}

web/public/robots.txt

@@ -0,0 +1,3 @@
+# https://www.robotstxt.org/robotstxt.html
+User-agent: *
+Disallow:

web/src/components/CaseBuilder/CaseBuilder.tsx

@@ -0,0 +1,27 @@
+/*
+ * RELOG: Supply Chain Analysis and Optimization
+ * Copyright (C) 2020-2025, UChicago Argonne, LLC. All rights reserved.
+ * Released under the modified BSD license. See COPYING.md for more details.
+ */
+
+import Header from "./Header";
+
+import "tabulator-tables/dist/css/tabulator.min.css";
+import "../Common/Forms/Tables.css";
+import Footer from "./Footer";
+
+const CaseBuilder = () => {
+  const onClear = () => {};
+  const onSave = () => {};
+  const onLoad = () => {};
+
+  return (
+    <div>
+      <Header onClear={onClear} onSave={onSave} onLoad={onLoad} />
+      <div className="content"></div>
+      <Footer />
+    </div>
+  );
+};
+
+export default CaseBuilder;

web/src/components/CaseBuilder/Footer.module.css

@@ -0,0 +1,14 @@
+/*
+ * RELOG: Supply Chain Analysis and Optimization
+ * Copyright (C) 2020-2025, UChicago Argonne, LLC. All rights reserved.
+ * Released under the modified BSD license. See COPYING.md for more details.
+ */
+
+.Footer {
+  background-color: #333;
+  text-align: center;
+  color: #aaa;
+  font-size: 14px;
+  padding: 16px;
+  line-height: 24px;
+}