Implement full recourse; remove feasibility cuts

.github/workflows/test.yml

@@ -10,7 +10,7 @@ jobs:
     runs-on: ${{ matrix.os }}
     strategy:
       matrix:
-        version: ['1.3', '1.4', '1.5', '1.6']
+        version: ['1.6', '1.7', '1.8']
         os:
           - ubuntu-latest
         arch:

.gitignore

@@ -12,3 +12,4 @@ Manifest.toml
 data
 build
 benchmark
+**/*.log

CHANGELOG.md

@@ -11,39 +11,48 @@ All notable changes to this project will be documented in this file.
 [semver]: https://semver.org/spec/v2.0.0.html
 [pkjjl]: https://pkgdocs.julialang.org/v1/compatibility/#compat-pre-1.0
 
+## [Unreleased]
+
+- Allow product disposal at collection centers
+- Implement stochastic optimization
+
+## [0.5.2] -- 2022-08-26
+### Changed
+- Update to JuMP 1.x
+
 ## [0.5.1] -- 2021-07-23
-## Added
+### Added
 - Allow user to specify locations as unique identifiers, instead of latitude and longitude (e.g. `us-state:IL` or `2018-us-county:17043`)
 - Add what-if scenarios.
 - Add products report.
 
 ## [0.5.0] -- 2021-01-06
-## Added
+### Added
 - Allow plants to store input material for processing in later years
 
 ## [0.4.0] -- 2020-09-18
-## Added
+### Added
 - Generate simplified solution reports (CSV)
 
 ## [0.3.3] -- 2020-10-13
-## Added
+### Added
 - Add option to write solution to JSON file in RELOG.solve
 - Improve error message when instance is infeasible
 - Make output file more readable
 
 ## [0.3.2] -- 2020-10-07
-## Added
+### Added
 - Add "building period" parameter
 
 ## [0.3.1] -- 2020-07-17
-## Fixed
+### Fixed
 - Fix expansion cost breakdown
 
 ## [0.3.0] -- 2020-06-25
-## Added
+### Added
 - Track emissions and energy (transportation and plants)
 
-## Changed
+### Changed
 - Minor changes to input file format:
     - Make all dictionary keys lowercase
     - Rename "outputs (tonne)" to "outputs (tonne/tonne)"

Makefile

@@ -1,25 +1,19 @@
-JULIA := julia --project=.
-SRC_FILES := $(wildcard src/*.jl test/*.jl)
 VERSION := 0.5
 
-all: docs test
-
-build/sysimage.so: src/sysimage.jl Project.toml Manifest.toml
-	@$(JULIA) src/sysimage.jl
-
 clean:
-	rm -rf build/*
+	rm -rfv build Manifest.toml test/Manifest.toml deps/formatter/build deps/formatter/Manifest.toml
 
 docs:
-	mkdocs build -d ../docs/$(VERSION)/
+	cd docs; julia --project=. make.jl; cd ..
+	rsync -avP --delete-after docs/build/ ../docs/$(VERSION)/
 	
 format:
-	julia -e 'using JuliaFormatter; format(["src", "test"], verbose=true);'
+	cd deps/formatter; ../../juliaw format.jl
 
-test:
-	@$(JULIA) --sysimage build/sysimage.so test/runtests.jl
+test: test/Manifest.toml
+	./juliaw test/runtests.jl
 
-test-watch:
-	bash -c "while true; do make test --quiet; sleep 1; done"
+test/Manifest.toml: test/Project.toml
+	julia --project=test -e "using Pkg; Pkg.instantiate()"
 
-.PHONY: docs test
+.PHONY: docs test format

Project.toml

@@ -1,48 +1,45 @@
 name = "RELOG"
 uuid = "a2afcdf7-cf04-4913-85f9-c0d81ddf2008"
 authors = ["Alinson S Xavier <axavier@anl.gov>"]
-version = "0.5.1"
+version = "0.5.2"
 
 [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"
+HiGHS = "87dc4568-4c63-4d18-b0c0-bb2238e4078b"
 JSON = "682c06a0-de6a-54ab-a142-c8b1cf79cde6"
 JSONSchema = "7d188eb4-7ad8-530c-ae41-71a32a6d4692"
 JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 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"
+Revise = "295af30f-e4ad-537b-8983-00126c2a3abe"
 Shapefile = "8e980c4a-a4fe-5da2-b3a7-4b4b0353a2f4"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
+StochasticPrograms = "8b8459f2-c380-502b-8633-9aed2d6c2b35"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
 ZipFile = "a5390f91-8eb1-5f08-bee0-b1d1ffed6cea"
 
 [compat]
 CRC = "4"
-CSV = "0.7"
-Cbc = "0.6"
-Clp = "0.8"
-DataFrames = "0.21"
-DataStructures = "0.17"
+CSV = "0.10"
+DataFrames = "1"
+DataStructures = "0.18"
 GZip = "0.5"
-Geodesy = "0.5"
+Geodesy = "1"
 JSON = "0.21"
-JSONSchema = "0.3"
-JuMP = "0.21"
-MathOptInterface = "0.9"
-OrderedCollections = "1.4"
-PackageCompiler = "1"
-ProgressBars = "0.6"
-Shapefile = "0.7"
-ZipFile = "0.9"
+JSONSchema = "1"
+JuMP = "1"
+MathOptInterface = "1"
+OrderedCollections = "1"
+ProgressBars = "1"
+Shapefile = "0.8"
+ZipFile = "0.10"
 julia = "1"

README.md

@@ -15,7 +15,7 @@
 
 
 
-<img src="https://anl-ceeesa.github.io/RELOG/0.5/images/ex_transportation.png" width="1000px"/>
+<img src="https://anl-ceeesa.github.io/RELOG/0.5/assets/ex_transportation.png" width="1000px"/>
 
 ### Documentation
 
@@ -26,8 +26,10 @@
 
 ### Authors
 
-* **Alinson S. Xavier,** Argonne National Laboratory <<axavier@anl.gov>>
-* **Nwike Iloeje,** Argonne National Laboratory <<ciloeje@anl.gov>>
+* **Alinson S. Xavier** <<axavier@anl.gov>>
+* **Nwike Iloeje** <<ciloeje@anl.gov>>
+* **John Atkins**
+* **Kyle Sun**
 
 ### License
 

deps/formatter/Project.toml

@@ -0,0 +1,5 @@
+[deps]
+JuliaFormatter = "98e50ef6-434e-11e9-1051-2b60c6c9e899"
+
+[compat]
+JuliaFormatter = "0.14.4"

deps/formatter/format.jl

@@ -0,0 +1,8 @@
+using JuliaFormatter
+format(
+    [
+        "../../src", 
+        "../../test",
+    ],
+    verbose=true,
+)

docs/Project.toml

@@ -0,0 +1,4 @@
+[deps]
+Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
+RELOG = "a2afcdf7-cf04-4913-85f9-c0d81ddf2008"
+Revise = "295af30f-e4ad-537b-8983-00126c2a3abe"

docs/make.jl

@@ -0,0 +1,19 @@
+using Documenter, RELOG
+
+function make()
+    makedocs(
+        sitename="RELOG",
+        pages=[
+            "Home" => "index.md",
+            "usage.md",
+            "format.md",
+            "reports.md",
+            "model.md",
+        ],
+        format = Documenter.HTML(
+            assets=["assets/custom.css"],
+        )
+    )
+end
+
+make()

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

@@ -11,7 +11,7 @@ RELOG accepts as input a JSON file with three sections: `parameters`, `products`
 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. |
 
@@ -31,7 +31,7 @@ The **parameters** section describes details about the simulation itself.
 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.
@@ -42,7 +42,7 @@ The **products** section describes all products and subproducts in the simulatio
 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.
@@ -97,7 +97,7 @@ Each product may have some amount available at the beginning of each time period
 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.
@@ -117,14 +117,14 @@ Each type of plant is associated with a set of potential locations where it can
 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.
 
@@ -132,7 +132,7 @@ The keys in the `disposal` dictionary should be the names of the products. The v
 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.
@@ -214,7 +214,7 @@ is is possible to write:
 Location names follow the format `db:id`, where `db` is the name of the database and `id` is the identifier for a specific location. RELOG currently includes the following databases:
 
 Database | Description | Examples
----------|-------------|----------
+:--------|:------------|:---------
 `us-state`| List of states of the United States. | `us-state:IL` (State of Illinois)
 `2018-us-county` | List of United States counties, as of 2018. IDs are 5-digit FIPS codes. | `2018-us-county:17043` (DuPage county in Illinois)
 

docs/src/index.md

@@ -1,25 +1,29 @@
 # RELOG: Reverse Logistics Optimization
 
-
 **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.
 
-<img src="images/ex_transportation.png" width="1000px"/>
+```@raw html
+<center>
+   <img src="assets/ex_transportation.png" width="1000px"/>
+</center>
+```
 
 
 ### Table of Contents
 
-  * [Usage](usage.md)
-  * [Input and Output Data Formats](format.md)
-  * [Simplified Solution Reports](reports.md)
-  * [Optimization Model](model.md)
+  ```@contents
+Pages = ["usage.md", "format.md", "reports.md", "model.md"]
+Depth = 3
+```
+
   
 ### Source Code
 
   * [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>>
+* **Alinson S. Xavier,** Argonne National Laboratory <axavier@anl.gov>
+* **Nwike Iloeje,** Argonne National Laboratory <ciloeje@anl.gov>
 
 ### License
 

docs/src/model.md

@@ -6,53 +6,65 @@ In this page, we describe the precise mathematical optimization model used by RE
 
 ### 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
+Symbol | Description
+:-------|:------------
+$L$ | 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:**
+#### 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.
+Symbol | Description | Unit
+:-------|:------------|:---
+$c^\text{disp}_{pmt}$ | 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. | tonne
 
-**Products:**
+#### 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`)
+Symbol | Description | Unit
+:-------|:------------|:---
+$\alpha_{pm}$ | 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:**
+#### Transportation
 
-* $c^\text{tr}_{t}$ - Transportation cost during time $t$ (`$/tonne/km`)
-* $d_{lp}$ - Distance between plant $p$ and location $l$ (`km`)
+Symbol | Description | Unit
+:-------|:------------|:---
+$c^\text{tr}_{t}$ | 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`)
+
+Symbol | Description | Unit
+:-------|:------------|:---
+$q_{mpt}$ | 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 $t$ | Boolean
+$w_{pt}$ | 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 $t$ | Boolean
+$y_{lpt}$ | 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:
 
+```math
 \begin{align*}
     \text{minimize} \;\; &
         \sum_{t \in T} \sum_{p \in P} \left[
@@ -73,6 +85,7 @@ RELOG minimizes the overall capital, production and transportation costs:
     &
         \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.
@@ -83,14 +96,17 @@ In the fourth line, we have the disposal costs.
 
 * All original materials must be sent to a plant:
 
-\begin{align}
+```math
+\begin{align*}
     & \sum_{p \in P} y_{lpt} = m^\text{initial}_{lt} 
         & \forall l \in L, t \in T
-\end{align}
+\end{align*}
+```
 
 * Amount received equals amount processed plus stored. Furthermore, all original material should be processed by the end of the simulation.
 
-\begin{align}
+```math
+\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 \\
@@ -98,56 +114,70 @@ In the fourth line, we have the disposal costs.
         & \forall p \in P \\
     & z^{\text{store}}_{p,t^{\max}} = 0
         & \forall p \in P
-\end{align}
+\end{align*}
+```
 
 * Plants have a limited processing capacity. Furthermore, if a plant is closed, it has zero processing capacity:
 
-\begin{align}
+```math
+\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}
+\end{align*}
+```
 
 * Plants have limited storage capacity. Furthermore, if a plant is closed, is has zero storage capacity:
 
-\begin{align}
+```math
+\begin{align*}
     & z^{\text{store}}_{pt} \leq m^\text{store}_p x_p
         & \forall p \in P, t \in T
-\end{align}
+\end{align*}
+```
 
 * Plants can only be expanded up to their maximum capacity. Furthermore, if a plant is closed, it cannot be expanded:
 
-\begin{align}
+```math
+\begin{align*}
     & \sum_{i=1}^t w_p \leq m^\text{max}_p x_p
         & \forall p \in P, t \in T
-\end{align}
+\end{align*}
+```
 
 * Amount of recovered material is proportional to amount processed: 
 
-\begin{align}
+```math
+\begin{align*}
     & q_{mpt} = \alpha_{pm} z^{\text{proc}}_{pt}
         & \forall m \in M, p \in P, t \in T
-\end{align}
+\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}
+```math
+\begin{align*}
     & q_{mpt} = z_{mpt}
         & \forall m \in M, p \in P, t \in T
-\end{align}
+\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}
+```math
+\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}
+\end{align*}
+```
 
 
 * Variable bounds:
 
-\begin{align}
+```math
+\begin{align*}
     & q_{mpt} \geq 0
         & \forall m \in M, p \in P, t \in T \\
     & u_{pt} \in \{0,1\}
@@ -162,4 +192,5 @@ In the fourth line, we have the disposal costs.
         & 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}
+\end{align*}
+```

docs/src/reports.md

@@ -9,7 +9,7 @@ In this page, we also illustrate what types of charts and visualizations can be
 Report showing plant costs, capacities, energy expenditure and utilization factors. Generated by `RELOG.write_plants_report(solution, filename)`.
 
 | 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.
@@ -45,7 +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
@@ -65,8 +67,9 @@ 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
 
@@ -74,7 +77,7 @@ Report showing amount of products produced, sent and disposed of by each plant,
 
 
 | 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.
@@ -101,7 +104,9 @@ 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
@@ -109,7 +114,7 @@ sns.barplot(x="amount produced (tonne)",
 Report showing amount of emissions produced by each plant. Generated by `RELOG.write_plant_emissions_report(solution, filename)`.
 
 | Column                                | Description
-|:--------------------------------------|---------------|
+|:--------------------------------------|:---------------|
 | `plant type` | Plant type.
 | `location name` | Location name.
 | `year` | Year.
@@ -133,14 +138,16 @@ 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.
@@ -157,7 +164,7 @@ Report showing amount of product sent from initial locations to plants, and from
 
 
 | 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.
@@ -191,7 +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):
 
@@ -234,7 +243,9 @@ 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
@@ -242,7 +253,7 @@ gp.GeoDataFrame(data, geometry=points).plot(ax=ax,
 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)`.
 
 | 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.
@@ -276,4 +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

@@ -3,22 +3,17 @@ 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
-(@v1.5) pkg> add https://github.com/ANL-CEEESA/RELOG.git
+```julia
+using Pkg
+Pkg.add(name="RELOG", version="0.5")
 ```
 
 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
+```julia
+Pkg.test("RELOG")
 ```
 
 ## 2. Modeling the problem
@@ -111,13 +106,17 @@ By default, RELOG internally uses [Cbc](https://github.com/coin-or/Cbc), an open
 ```julia
 using RELOG, Gurobi, JuMP
 
-gurobi = optimizer_with_attributes(Gurobi.Optimizer,
-                                   "TimeLimit" => 3600,
-                                   "MIPGap" => 0.001)
+gurobi = optimizer_with_attributes(
+    Gurobi.Optimizer,
+    "TimeLimit" => 3600,
+    "MIPGap" => 0.001,
+)
 
-RELOG.solve("instance.json",
-            output="solution.json",
-            optimizer=gurobi)
+RELOG.solve(
+    "instance.json",
+    output="solution.json",
+    optimizer=gurobi,
+)
 ```
 
 ### 5.2 Multi-period heuristics
@@ -133,6 +132,8 @@ To solve an instance using this heuristic, use the option `heuristic=true`, as s
 ```julia
 using RELOG
 
-solution = RELOG.solve("/home/user/instance.json",
-                       heuristic=true)
+solution = RELOG.solve(
+    "/home/user/instance.json",
+    heuristic=true,
+)
 ```

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...

juliaw

@@ -0,0 +1,75 @@
+#!/bin/bash
+# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
+# Copyright (C) 2020-2021, UChicago Argonne, LLC. All rights reserved.
+# Released under the modified BSD license. See COPYING.md for more details.
+
+if [ ! -e Project.toml ]; then
+    echo "juliaw: Project.toml not found"
+    exit 1
+fi
+
+if [ ! -e Manifest.toml ]; then
+    julia --project=. -e 'using Pkg; Pkg.instantiate()' || exit 1
+fi
+
+if [ ! -e build/sysimage.so -o Project.toml -nt build/sysimage.so ]; then
+    echo "juliaw: rebuilding system image..."
+
+    # Generate temporary project folder
+    rm -rf $HOME/.juliaw
+    mkdir -p $HOME/.juliaw/src
+    cp Project.toml Manifest.toml $HOME/.juliaw
+    NAME=$(julia -e 'using TOML; toml = TOML.parsefile("Project.toml"); "name" in keys(toml) && print(toml["name"])')
+    if [ ! -z $NAME ]; then
+        cat > $HOME/.juliaw/src/$NAME.jl << EOF
+module $NAME
+end
+EOF
+    fi
+
+    # Add PackageCompiler dependencies to temporary project
+    julia --project=$HOME/.juliaw -e 'using Pkg; Pkg.add(["PackageCompiler", "TOML", "Logging"])'
+
+    # Generate system image scripts
+    cat > $HOME/.juliaw/sysimage.jl << EOF
+using PackageCompiler
+using TOML
+using Logging
+
+Logging.disable_logging(Logging.Info)
+mkpath("$PWD/build")
+
+println("juliaw: generating precompilation statements...")
+run(\`julia --project="$PWD" --trace-compile="$PWD"/build/precompile.jl \$(ARGS)\`)
+
+println("juliaw: finding dependencies...")
+project = TOML.parsefile("Project.toml")
+manifest = TOML.parsefile("Manifest.toml")
+deps = Symbol[]
+for dep in keys(project["deps"])
+    if dep in keys(manifest)
+	# Up to Julia 1.6
+        dep_entry = manifest[dep][1]
+    else
+        # Julia 1.7+
+        dep_entry = manifest["deps"][dep][1]
+    end
+    if "path" in keys(dep_entry)
+        println("  - \$(dep) [skip]")
+    else
+        println("  - \$(dep)")
+        push!(deps, Symbol(dep))
+    end
+end
+
+println("juliaw: building system image...")
+create_sysimage(
+    deps,
+    precompile_statements_file = "$PWD/build/precompile.jl",
+    sysimage_path = "$PWD/build/sysimage.so",
+)
+EOF
+    julia --project=$HOME/.juliaw $HOME/.juliaw/sysimage.jl $* 
+else
+    julia --project=. --sysimage build/sysimage.so $*
+fi

src/RELOG.jl

@@ -17,7 +17,6 @@ include("instance/validate.jl")
 include("model/build.jl")
 include("model/getsol.jl")
 include("model/solve.jl")
-include("model/resolve.jl")
 include("reports/plant_emissions.jl")
 include("reports/plant_outputs.jl")
 include("reports/plants.jl")

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/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/graph/build.jl

@@ -7,7 +7,7 @@ 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)
+    return round(euclidean_distance(x, y) / 1000.0, digits = 2)
 end
 
 function build_graph(instance::Instance)::Graph
@@ -59,7 +59,7 @@ function build_graph(instance::Instance)::Graph
                 dest.location.longitude,
             )
             values = Dict("distance" => distance)
-            arc = Arc(source, dest, values)
+            arc = Arc(length(arcs) + 1, source, dest, values)
             push!(source.outgoing_arcs, arc)
             push!(dest.incoming_arcs, arc)
             push!(arcs, arc)
@@ -72,7 +72,7 @@ function build_graph(instance::Instance)::Graph
         for dest in shipping_nodes_by_plant[plant]
             weight = plant.output[dest.product]
             values = Dict("weight" => weight)
-            arc = Arc(source, dest, values)
+            arc = Arc(length(arcs) + 1, source, dest, values)
             push!(source.outgoing_arcs, arc)
             push!(dest.incoming_arcs, arc)
             push!(arcs, arc)

src/graph/structs.jl

@@ -7,6 +7,7 @@ using Geodesy
 abstract type Node end
 
 mutable struct Arc
+    index::Int
     source::Node
     dest::Node
     values::Dict{String,Float64}

src/instance/compress.jl

@@ -29,6 +29,8 @@ function _compress(instance::Instance)::Instance
         for (emission_name, emission_value) in p.transportation_emissions
             p.transportation_emissions[emission_name] = [mean(emission_value)]
         end
+        p.disposal_limit = [maximum(p.disposal_limit) * T]
+        p.disposal_cost = [mean(p.disposal_cost)]
     end
 
     # Compress collection centers
@@ -58,3 +60,42 @@ function _compress(instance::Instance)::Instance
 
     return compressed
 end
+
+function _slice(instance::Instance, T::UnitRange)::Instance
+    sliced = deepcopy(instance)
+    sliced.time = length(T)
+
+    for p in sliced.products
+        p.transportation_cost = p.transportation_cost[T]
+        p.transportation_energy = p.transportation_energy[T]
+        for (emission_name, emission_value) in p.transportation_emissions
+            p.transportation_emissions[emission_name] = emission_value[T]
+        end
+        p.disposal_limit = p.disposal_limit[T]
+        p.disposal_cost = p.disposal_cost[T]
+    end
+
+    for c in sliced.collection_centers
+        c.amount = c.amount[T]
+    end
+
+    for plant in sliced.plants
+        plant.energy = plant.energy[T]
+        for (emission_name, emission_value) in plant.emissions
+            plant.emissions[emission_name] = emission_value[T]
+        end
+        for s in plant.sizes
+            s.variable_operating_cost = s.variable_operating_cost[T]
+            s.opening_cost = s.opening_cost[T]
+            s.fixed_operating_cost = s.fixed_operating_cost[T]
+        end
+        for (prod_name, disp_limit) in plant.disposal_limit
+            plant.disposal_limit[prod_name] = disp_limit[T]
+        end
+        for (prod_name, disp_cost) in plant.disposal_cost
+            plant.disposal_cost[prod_name] = disp_cost[T]
+        end
+    end
+
+    return sliced
+end

src/model/build.jl

@@ -2,66 +2,346 @@
 # 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, LinearAlgebra, Geodesy, ProgressBars, Printf, DataStructures, StochasticPrograms
 
-function build_model(instance::Instance, graph::Graph, optimizer)::JuMP.Model
-    model = Model(optimizer)
-    model[:instance] = instance
-    model[:graph] = graph
-    create_vars!(model)
-    create_objective_function!(model)
-    create_shipping_node_constraints!(model)
-    create_process_node_constraints!(model)
-    return model
+function build_model(
+    instance::Instance,
+    graph::Graph,
+    optimizer,
+)
+    return build_model(
+        instance,
+        [graph],
+        [1.0],
+        optimizer=optimizer,
+        method=:ef,
+    )
 end
 
+function build_model(
+    instance::Instance,
+    graphs::Vector{Graph},
+    probs::Vector{Float64};
+    optimizer,
+    method=:ef,
+    tol=0.1,
+)
+    T = instance.time
 
-function create_vars!(model::JuMP.Model)
-    graph, T = model[:graph], model[:instance].time
-    model[:flow] =
-        Dict((a, t) => @variable(model, lower_bound = 0) for a in graph.arcs, t = 1:T)
-    model[:plant_dispose] = Dict(
-        (n, t) => @variable(
-            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[:collection_dispose] = Dict(
-        (n, t) => @variable(model, lower_bound = 0,) for
-        n in values(graph.collection_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
-    )
+    @stochastic_model model begin
+        # Stage 1: Build plants
+        # =====================================================================
+        @stage 1 begin
+            pn = graphs[1].process_nodes
+            PN = length(pn)
+
+            # Var: open_plant
+            @decision(
+                model,
+                open_plant[n in 1:PN, t in 1:T],
+                binary = true,
+            )
+
+            # Var: is_open
+            @decision(
+                model,
+                is_open[n in 1:PN, t in 1:T],
+                binary = true,
+            )
+
+            # Objective function
+            @objective(
+                model,
+                Min,
+
+                # Opening, fixed operating costs
+                sum(
+                    pn[n].location.sizes[1].opening_cost[t] * open_plant[n, t] +
+                    pn[n].location.sizes[1].fixed_operating_cost[t] * is_open[n, t]                  
+                    for n in 1:PN
+                    for t in 1:T
+                ),
+            )
+
+            for t = 1:T, n in 1:PN
+                # Plant is currently open if it was already open in the previous time period or
+                # if it was built just now
+                if t > 1
+                    @constraint(
+                        model,
+                        is_open[n, t] == is_open[n, t-1] + open_plant[n, t]
+                    )
+                else
+                    @constraint(model, is_open[n, t] == open_plant[n, t])
+                end
+        
+                # Plant can only be opened during building period
+                if t ∉ instance.building_period
+                    @constraint(model, open_plant[n, t] == 0)
+                end
+            end
+        end
+
+        # Stage 2: Flows, disposal, capacity & storage
+        # =====================================================================
+        @stage 2 begin
+            @uncertain graph
+            pn = graph.process_nodes
+            psn = graph.plant_shipping_nodes
+            csn = graph.collection_shipping_nodes
+            arcs = graph.arcs
+        
+            A = length(arcs)
+            PN = length(pn)
+            CSN = length(csn)
+            PSN = length(psn)
+
+            # Var: flow
+            @recourse(
+                model,
+                flow[a in 1:A, t in 1:T],
+                lower_bound = 0,
+            )
+
+            # Var: plant_dispose
+            @recourse(
+                model,
+                plant_dispose[n in 1:PSN, t in 1:T],
+                lower_bound = 0,
+                upper_bound = psn[n].location.disposal_limit[psn[n].product][t],
+            )
+
+            # Var: collection_dispose
+            @recourse(
+                model,
+                collection_dispose[n in 1:CSN, t in 1:T],
+                lower_bound = 0,
+                upper_bound = graph.collection_shipping_nodes[n].location.amount[t],
+            )
+
+            # Var: collection_shortfall
+            @recourse(
+                model,
+                collection_shortfall[n in 1:CSN, t in 1:T],
+                lower_bound = 0,
+            )
+
+            # Var: store
+            @recourse(
+                model,
+                store[
+                    n in 1:PN,
+                    t in 1:T,
+                ],
+                lower_bound = 0,
+                upper_bound = pn[n].location.storage_limit,
+            )
+
+            # Var: process
+            @recourse(
+                model,
+                process[
+                    n in 1:PN,
+                    t in 1:T,
+                ],
+                lower_bound = 0,
+            )
+
+            # Var: capacity
+            @recourse(
+                model,
+                capacity[
+                    n in 1:PN,
+                    t in 1:T,
+                ],
+                lower_bound = 0,
+                upper_bound = pn[n].location.sizes[2].capacity,
+            )
+
+            # Var: expansion
+            @recourse(
+                model,
+                expansion[
+                    n in 1:PN,
+                    t in 1:T,
+                ],
+                lower_bound = 0,
+                upper_bound = (
+                    pn[n].location.sizes[2].capacity -
+                    pn[n].location.sizes[1].capacity
+                ),
+            )
+
+            # Objective function
+            @objective(
+                model,
+                Min,
+                sum(
+                    # Transportation costs
+                    pn[n].location.input.transportation_cost[t] * 
+                        a.values["distance"] *
+                        flow[a.index,t]
+
+                    for n in 1:PN
+                    for a in pn[n].incoming_arcs
+                    for t in 1:T
+                ) + sum(
+                    # Fixed operating costs (expansion)
+                    slope_fix_oper_cost(pn[n].location, t) * expansion[n, t] +
+
+                    # Processing costs
+                    pn[n].location.sizes[1].variable_operating_cost[t] * process[n, t] +
+
+                    # Storage costs
+                    pn[n].location.storage_cost[t] * store[n, t] +
+
+                    # Expansion costs
+                    (
+                        t < T ? (
+                            (
+                                slope_open(pn[n].location, t) -
+                                slope_open(pn[n].location, t + 1)
+                            ) * expansion[n, t]
+                        ) : slope_open(pn[n].location, t) * expansion[n, t]
+                    )
+
+                    for n in 1:PN
+                    for t in 1:T
+                ) + sum(
+                    # Disposal costs (plants)
+                    psn[n].location.disposal_cost[psn[n].product][t] * plant_dispose[n, t]
+                    for n in 1:PSN
+                    for t in 1:T
+                ) + sum(
+                    # Disposal costs (collection centers)
+                    csn[n].location.product.disposal_cost[t] * collection_dispose[n, t]
+                    for n in 1:CSN
+                    for t in 1:T
+                ) + sum(
+                    # Collection shortfall
+                    1e4 * collection_shortfall[n, t]
+                    for n in 1:CSN
+                    for t in 1:T
+                )
+            )
+
+            # Process node constraints
+            for t = 1:T, n in 1:PN
+                node = pn[n]
+
+                # Output amount is implied by amount processed
+                for arc in node.outgoing_arcs
+                    @constraint(
+                        model,
+                        flow[arc.index, t] == arc.values["weight"] * process[n, t]
+                    )
+                end
+        
+                # If plant is closed, capacity is zero
+                @constraint(
+                    model,
+                    capacity[n, t] <= node.location.sizes[2].capacity * is_open[n, t]
+                )
+        
+                # If plant is open, capacity is greater than base
+                @constraint(
+                    model,
+                    capacity[n, t] >= node.location.sizes[1].capacity * is_open[n, t]
+                )
+        
+                # Capacity is linked to expansion
+                @constraint(
+                    model,
+                    capacity[n, t] <=
+                        node.location.sizes[1].capacity + expansion[n, t]
+                )
+        
+                # Can only process up to capacity
+                @constraint(model, process[n, t] <= capacity[n, t])
+        
+                if t > 1
+                    # Plant capacity can only increase over time
+                    @constraint(model, capacity[n, t] >= capacity[n, t-1])
+                    @constraint(model, expansion[n, t] >= expansion[n, t-1])
+                end
+        
+                # Amount received equals amount processed plus stored
+                store_in = 0
+                if t > 1
+                    store_in = store[n, t-1]
+                end
+                if t == T
+                    @constraint(model, store[n, t] == 0)
+                end
+                @constraint(
+                    model,
+                    sum(
+                        flow[arc.index, t]
+                        for arc in node.incoming_arcs
+                    ) + store_in == store[n, t] + process[n, t]
+                )
+
+            end
+
+            # Material flow at collection shipping nodes
+            @constraint(
+                model,
+                eq_balance_centers[
+                    n in 1:CSN,
+                    t in 1:T,
+                ],
+                sum(
+                    flow[arc.index, t]
+                    for arc in csn[n].outgoing_arcs
+                ) == csn[n].location.amount[t] - collection_dispose[n, t] - collection_shortfall[n, t]
+            )
+
+            # Material flow at plant shipping nodes
+            @constraint(
+                model,
+                eq_balance_plant[
+                    n in 1:PSN,
+                    t in 1:T,
+                ],
+                sum(flow[a.index, t] for a in psn[n].incoming_arcs) ==
+                sum(flow[a.index, t] for a in psn[n].outgoing_arcs) +
+                plant_dispose[n, t]
+            )
+
+            # Enforce product disposal limit at collection centers
+            for t in 1:T, prod in instance.products
+                if isempty(prod.collection_centers)
+                    continue
+                end
+                @constraint(
+                    model,
+                    sum(
+                        collection_dispose[n, t]
+                        for n in 1:CSN
+                        if csn[n].product.name == prod.name
+                    ) <= prod.disposal_limit[t]
+                )
+            end
+        end
+    end
+
+    ξ = [
+        @scenario graph = graphs[i] probability = probs[i]
+        for i in 1:length(graphs)
+    ]
+
+    if method == :ef
+        sp = instantiate(model, ξ; optimizer=optimizer)
+    elseif method == :lshaped
+        sp = instantiate(model, ξ; optimizer=LShaped.Optimizer)
+        set_optimizer_attribute(sp, MasterOptimizer(), optimizer)
+        set_optimizer_attribute(sp, SubProblemOptimizer(), optimizer)
+        set_optimizer_attribute(sp, RelativeTolerance(), tol)
+    else
+        error("unknown method: $method")
+    end
+
+    return sp
 end
 
 
@@ -82,196 +362,3 @@ function slope_fix_oper_cost(plant, t)
         (plant.sizes[2].capacity - plant.sizes[1].capacity)
     end
 end
-
-function create_objective_function!(model::JuMP.Model)
-    graph, T = model[:graph], model[:instance].time
-    obj = AffExpr(0.0)
-
-    # Process node costs
-    for n in values(graph.process_nodes), t = 1:T
-
-        # Transportation and variable operating costs
-        for a in n.incoming_arcs
-            c = n.location.input.transportation_cost[t] * a.values["distance"]
-            add_to_expression!(obj, c, model[:flow][a, t])
-        end
-
-        # Opening costs
-        add_to_expression!(
-            obj,
-            n.location.sizes[1].opening_cost[t],
-            model[:open_plant][n, t],
-        )
-
-        # Fixed operating costs (base)
-        add_to_expression!(
-            obj,
-            n.location.sizes[1].fixed_operating_cost[t],
-            model[:is_open][n, t],
-        )
-
-        # Fixed operating costs (expansion)
-        add_to_expression!(obj, slope_fix_oper_cost(n.location, t), model[:expansion][n, t])
-
-        # Processing costs
-        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
-
-    # Plant shipping node costs
-    for n in values(graph.plant_shipping_nodes), t = 1:T
-
-        # Disposal costs
-        add_to_expression!(
-            obj,
-            n.location.disposal_cost[n.product][t],
-            model[:plant_dispose][n, t],
-        )
-    end
-
-    # Collection shipping node costs
-    for n in values(graph.collection_shipping_nodes), t = 1:T
-
-        # Disposal costs
-        add_to_expression!(
-            obj,
-            n.location.product.disposal_cost[t],
-            model[:collection_dispose][n, t],
-        )
-    end
-
-    @objective(model, Min, obj)
-end
-
-
-function create_shipping_node_constraints!(model::JuMP.Model)
-    graph, T = model[:graph], model[:instance].time
-    model[:eq_balance] = OrderedDict()
-    for t = 1:T
-        # Collection centers
-        for n in graph.collection_shipping_nodes
-            model[:eq_balance][n, t] = @constraint(
-                model,
-                sum(model[:flow][a, t] for a in n.outgoing_arcs) ==
-                n.location.amount[t] + model[:collection_dispose][n, t]
-            )
-        end
-        for prod in model[:instance].products
-            if isempty(prod.collection_centers)
-                continue
-            end
-            expr = AffExpr()
-            for center in prod.collection_centers
-                n = graph.collection_center_to_node[center]
-                add_to_expression!(expr, model[:collection_dispose][n, t])
-            end
-            @constraint(model, expr <= prod.disposal_limit[t])
-        end
-
-        # Plants
-        for n in graph.plant_shipping_nodes
-            @constraint(
-                model,
-                sum(model[:flow][a, t] for a in n.incoming_arcs) ==
-                sum(model[:flow][a, t] for a in n.outgoing_arcs) +
-                model[:plant_dispose][n, t]
-            )
-        end
-    end
-
-end
-
-
-function create_process_node_constraints!(model::JuMP.Model)
-    graph, T = model[:graph], model[:instance].time
-
-    for t = 1:T, n in graph.process_nodes
-        input_sum = AffExpr(0.0)
-        for a in n.incoming_arcs
-            add_to_expression!(input_sum, 1.0, model[:flow][a, t])
-        end
-
-        # Output amount is implied by amount processed
-        for a in n.outgoing_arcs
-            @constraint(
-                model,
-                model[:flow][a, t] == a.values["weight"] * model[:process][n, t]
-            )
-        end
-
-        # If plant is closed, capacity is zero
-        @constraint(
-            model,
-            model[:capacity][n, t] <= n.location.sizes[2].capacity * model[:is_open][n, t]
-        )
-
-        # If plant is open, capacity is greater than base
-        @constraint(
-            model,
-            model[:capacity][n, t] >= n.location.sizes[1].capacity * model[:is_open][n, t]
-        )
-
-        # Capacity is linked to expansion
-        @constraint(
-            model,
-            model[:capacity][n, t] <=
-            n.location.sizes[1].capacity + model[:expansion][n, t]
-        )
-
-        # Can only process up to capacity
-        @constraint(model, model[:process][n, t] <= model[:capacity][n, t])
-
-        if t > 1
-            # Plant capacity can only increase over time
-            @constraint(model, model[:capacity][n, t] >= model[:capacity][n, t-1])
-            @constraint(model, model[:expansion][n, t] >= model[:expansion][n, t-1])
-        end
-
-        # Amount received equals amount processed plus stored
-        store_in = 0
-        if t > 1
-            store_in = model[:store][n, t-1]
-        end
-        if t == T
-            @constraint(model, model[:store][n, t] == 0)
-        end
-        @constraint(
-            model,
-            input_sum + store_in == model[:store][n, t] + model[:process][n, t]
-        )
-
-
-        # Plant is currently open if it was already open in the previous time period or
-        # if it was built just now
-        if t > 1
-            @constraint(
-                model,
-                model[:is_open][n, t] == model[:is_open][n, t-1] + model[:open_plant][n, t]
-            )
-        else
-            @constraint(model, model[:is_open][n, t] == model[:open_plant][n, t])
-        end
-
-        # Plant can only be opened during building period
-        if t ∉ model[:instance].building_period
-            @constraint(model, model[:open_plant][n, t] == 0)
-        end
-    end
-end

src/model/getsol.jl

@@ -2,12 +2,33 @@
 # 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, LinearAlgebra, Geodesy, ProgressBars, Printf, DataStructures
+
+function get_solution(
+    instance,
+    graph,
+    model,
+    scenario_index::Int=1;
+    marginal_costs=false,
+)
+    value(x) = StochasticPrograms.value(x, scenario_index)
+    ivalue(x) = StochasticPrograms.value(x)
+    shadow_price(x) = StochasticPrograms.shadow_price(x, scenario_index)
 
-function get_solution(model::JuMP.Model; marginal_costs = true)
-    graph, instance = model[:graph], model[:instance]
     T = instance.time
 
+    pn = graph.process_nodes
+    psn = graph.plant_shipping_nodes
+    csn = graph.collection_shipping_nodes
+    arcs = graph.arcs
+
+    A = length(arcs)
+    PN = length(pn)
+    CSN = length(csn)
+    PSN = length(psn)
+
+    flow = model[2, :flow]
+
     output = OrderedDict(
         "Plants" => OrderedDict(),
         "Products" => OrderedDict(),
@@ -29,40 +50,52 @@ function get_solution(model::JuMP.Model; marginal_costs = true)
         ),
     )
 
-    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
+    pn = graph.process_nodes
+    psn = graph.plant_shipping_nodes
+
+    plant_to_process_node_index = OrderedDict(
+        pn[n].location => n
+        for n in 1:length(pn)
+    )
+
+    plant_to_shipping_node_indices = OrderedDict(p => [] for p in instance.plants)
+    for n in 1:length(psn)
+        push!(plant_to_shipping_node_indices[psn[n].location], n)
     end
 
     # Products
-    for n in graph.collection_shipping_nodes
+    for n in 1:CSN
+        node = csn[n]
         location_dict = OrderedDict{Any,Any}(
-            "Latitude (deg)" => n.location.latitude,
-            "Longitude (deg)" => n.location.longitude,
-            "Amount (tonne)" => n.location.amount,
-            "Dispose (tonne)" =>
-                [JuMP.value(model[:collection_dispose][n, t]) for t = 1:T],
+            "Latitude (deg)" => node.location.latitude,
+            "Longitude (deg)" => node.location.longitude,
+            "Amount (tonne)" => node.location.amount,
+            "Dispose (tonne)" => [
+                value(model[2, :collection_dispose][n, t])
+                for t = 1:T
+            ],
+            "Disposal cost (\$)" => [
+                value(model[2, :collection_dispose][n, t]) *
+                    node.location.product.disposal_cost[t]
+                for t = 1:T
+            ]
         )
         if marginal_costs
             location_dict["Marginal cost (\$/tonne)"] = [
-                round(abs(JuMP.shadow_price(model[:eq_balance][n, t])), digits = 2) for
-                t = 1:T
+                round(abs(shadow_price(model[2, :eq_balance_centers][n, t])), digits=2) for t = 1:T
             ]
         end
-        if n.product.name ∉ keys(output["Products"])
-            output["Products"][n.product.name] = OrderedDict()
+        if node.product.name ∉ keys(output["Products"])
+            output["Products"][node.product.name] = OrderedDict()
         end
-        output["Products"][n.product.name][n.location.name] = location_dict
+        output["Products"][node.product.name][node.location.name] = location_dict
     end
 
     # Plants
     for plant in instance.plants
         skip_plant = true
-        process_node = plant_to_process_node[plant]
+        n = plant_to_process_node_index[plant]
+        process_node = pn[n]
         plant_dict = OrderedDict{Any,Any}(
             "Input" => OrderedDict(),
             "Output" =>
@@ -73,39 +106,39 @@ function get_solution(model::JuMP.Model; marginal_costs = true)
             "Latitude (deg)" => plant.latitude,
             "Longitude (deg)" => plant.longitude,
             "Capacity (tonne)" =>
-                [JuMP.value(model[:capacity][process_node, t]) for t = 1:T],
+                [value(model[2, :capacity][n, t]) for t = 1:T],
             "Opening cost (\$)" => [
-                JuMP.value(model[:open_plant][process_node, t]) *
+                ivalue(model[1, :open_plant][n, t]) *
                 plant.sizes[1].opening_cost[t] for t = 1:T
             ],
             "Fixed operating cost (\$)" => [
-                JuMP.value(model[:is_open][process_node, t]) *
+                ivalue(model[1, :is_open][n, t]) *
                 plant.sizes[1].fixed_operating_cost[t] +
-                JuMP.value(model[:expansion][process_node, t]) *
+                value(model[2, :expansion][n, 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])
+                        slope_open(plant, t) * value(model[2, :expansion][n, t])
                     else
                         slope_open(plant, t) * (
-                            JuMP.value(model[:expansion][process_node, t]) -
-                            JuMP.value(model[:expansion][process_node, t-1])
+                            value(model[2, :expansion][n, t]) -
+                            value(model[2, :expansion][n, t-1])
                         )
                     end
                 ) for t = 1:T
             ],
             "Process (tonne)" =>
-                [JuMP.value(model[:process][process_node, t]) for t = 1:T],
+                [value(model[2, :process][n, t]) for t = 1:T],
             "Variable operating cost (\$)" => [
-                JuMP.value(model[:process][process_node, t]) *
+                value(model[2, :process][n, 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],
+                [value(model[2, :store][n, t]) for t = 1:T],
             "Storage cost (\$)" => [
-                JuMP.value(model[:store][process_node, t]) * plant.storage_cost[t]
+                value(model[2, :store][n, t]) * plant.storage_cost[t]
                 for t = 1:T
             ],
         )
@@ -118,7 +151,7 @@ function get_solution(model::JuMP.Model; marginal_costs = true)
 
         # Inputs
         for a in process_node.incoming_arcs
-            vals = [JuMP.value(model[:flow][a, t]) for t = 1:T]
+            vals = [value(flow[a.index, t]) for t = 1:T]
             if sum(vals) <= 1e-3
                 continue
             end
@@ -176,19 +209,20 @@ function get_solution(model::JuMP.Model; marginal_costs = true)
         end
 
         # Outputs
-        for shipping_node in plant_to_shipping_nodes[plant]
+        for n2 in plant_to_shipping_node_indices[plant]
+            shipping_node = psn[n2]
             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[:plant_dispose][shipping_node, t]) for t = 1:T]
+                [value(model[2, :plant_dispose][n2, 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[:plant_dispose][shipping_node, t]) for t = 1:T]
+                    [value(model[2, :plant_dispose][n2, t]) for t = 1:T]
                 disposal_dict["Cost (\$)"] = [
                     disposal_dict["Amount (tonne)"][t] *
                     plant.disposal_cost[shipping_node.product][t] for t = 1:T
@@ -198,7 +232,7 @@ function get_solution(model::JuMP.Model; marginal_costs = true)
             end
 
             for a in shipping_node.outgoing_arcs
-                vals = [JuMP.value(model[:flow][a, t]) for t = 1:T]
+                vals = [value(flow[a.index, t]) for t = 1:T]
                 if sum(vals) <= 1e-3
                     continue
                 end

src/model/resolve.jl

@@ -1,97 +0,0 @@
-# RELOG: Reverse Logistics Optimization
-# Copyright (C) 2020-2021, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-using JuMP
-
-function resolve(model_old, filename::AbstractString; kwargs...)::OrderedDict
-    @info "Reading $filename..."
-    instance = RELOG.parsefile(filename)
-    return resolve(model_old, instance; kwargs...)
-end
-
-function resolve(model_old, instance::Instance; optimizer = nothing)::OrderedDict
-    milp_optimizer = lp_optimizer = optimizer
-    if optimizer === nothing
-        milp_optimizer = _get_default_milp_optimizer()
-        lp_optimizer = _get_default_lp_optimizer()
-    end
-
-    @info "Building new graph..."
-    graph = build_graph(instance)
-    _print_graph_stats(instance, graph)
-
-    @info "Building new optimization model..."
-    model_new = RELOG.build_model(instance, graph, milp_optimizer)
-
-    @info "Fixing decision variables..."
-    _fix_plants!(model_old, model_new)
-    JuMP.set_optimizer(model_new, lp_optimizer)
-
-    @info "Optimizing MILP..."
-    JuMP.optimize!(model_new)
-
-    if !has_values(model_new)
-        @warn("No solution available")
-        return OrderedDict()
-    end
-
-    @info "Extracting solution..."
-    solution = get_solution(model_new, marginal_costs = true)
-
-    return solution
-end
-
-function _fix_plants!(model_old, model_new)::Nothing
-    T = model_new[:instance].time
-
-    # Fix open_plant variables
-    for ((node_old, t), var_old) in model_old[:open_plant]
-        value_old = JuMP.value(var_old)
-        node_new = model_new[:graph].name_to_process_node_map[(
-            node_old.location.plant_name,
-            node_old.location.location_name,
-        )]
-        var_new = model_new[:open_plant][node_new, t]
-        JuMP.unset_binary(var_new)
-        JuMP.fix(var_new, value_old)
-    end
-
-    # Fix is_open variables
-    for ((node_old, t), var_old) in model_old[:is_open]
-        value_old = JuMP.value(var_old)
-        node_new = model_new[:graph].name_to_process_node_map[(
-            node_old.location.plant_name,
-            node_old.location.location_name,
-        )]
-        var_new = model_new[:is_open][node_new, t]
-        JuMP.unset_binary(var_new)
-        JuMP.fix(var_new, value_old)
-    end
-
-    # Fix plant capacities
-    for ((node_old, t), var_old) in model_old[:capacity]
-        value_old = JuMP.value(var_old)
-        node_new = model_new[:graph].name_to_process_node_map[(
-            node_old.location.plant_name,
-            node_old.location.location_name,
-        )]
-        var_new = model_new[:capacity][node_new, t]
-        JuMP.delete_lower_bound(var_new)
-        JuMP.delete_upper_bound(var_new)
-        JuMP.fix(var_new, value_old)
-    end
-
-    # Fix plant expansion
-    for ((node_old, t), var_old) in model_old[:expansion]
-        value_old = JuMP.value(var_old)
-        node_new = model_new[:graph].name_to_process_node_map[(
-            node_old.location.plant_name,
-            node_old.location.location_name,
-        )]
-        var_new = model_new[:expansion][node_new, t]
-        JuMP.delete_lower_bound(var_new)
-        JuMP.delete_upper_bound(var_new)
-        JuMP.fix(var_new, value_old)
-    end
-end

src/model/solve.jl

@@ -2,14 +2,14 @@
 # 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, LinearAlgebra, Geodesy, HiGHS, ProgressBars, Printf, DataStructures
 
 function _get_default_milp_optimizer()
-    return optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
+    return optimizer_with_attributes(HiGHS.Optimizer)
 end
 
 function _get_default_lp_optimizer()
-    return optimizer_with_attributes(Clp.Optimizer, "LogLevel" => 0)
+    return optimizer_with_attributes(HiGHS.Optimizer)
 end
 
 
@@ -25,53 +25,81 @@ function _print_graph_stats(instance::Instance, graph::Graph)::Nothing
     return
 end
 
+function solve_stochastic(;
+    scenarios::Vector{String},
+    probs::Vector{Float64},
+    optimizer,
+    method=:ef,
+    tol=0.1,
+)
+    @info "Reading instance files..."
+    instances = [parsefile(sc) for sc in scenarios]
+
+    @info "Building graphs..."
+    graphs = [build_graph(inst) for inst in instances]
+
+    @info "Building stochastic model..."
+    sp = RELOG.build_model(instances[1], graphs, probs; optimizer, method, tol)
+
+    @info "Optimizing stochastic model..."
+    optimize!(sp)
+
+    @info "Extracting solution..."
+    solutions = [
+        get_solution(instances[i], graphs[i], sp, i)
+        for i in 1:length(instances)
+    ]
+
+    return solutions
+end
+
 function solve(
     instance::Instance;
-    optimizer = nothing,
-    output = nothing,
-    marginal_costs = true,
-    return_model = false,
+    optimizer=HiGHS.Optimizer,
+    marginal_costs=true,
+    return_model=false
 )
-
-    milp_optimizer = lp_optimizer = optimizer
-    if optimizer == nothing
-        milp_optimizer = _get_default_milp_optimizer()
-        lp_optimizer = _get_default_lp_optimizer()
-    end
-
     @info "Building graph..."
     graph = RELOG.build_graph(instance)
     _print_graph_stats(instance, graph)
 
-    @info "Building optimization model..."
-    model = RELOG.build_model(instance, graph, milp_optimizer)
-
-    @info "Optimizing MILP..."
-    JuMP.optimize!(model)
+    @info "Building model..."
+    model = RELOG.build_model(instance, [graph], [1.0]; optimizer)
 
+    @info "Optimizing model..."
+    optimize!(model)
     if !has_values(model)
         error("No solution available")
     end
 
+    @info "Extracting solution..."
+    solution = get_solution(instance, graph, model, 1)
+
     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
+        open_plant_vals = value.(model[1, :open_plant])
+        is_open_vals = value.(model[1, :is_open])
+
+        for n in 1:length(graph.process_nodes), t in 1:instance.time
+            unset_binary(model[1, :open_plant][n, t])
+            unset_binary(model[1, :is_open][n, t])
+            fix(
+                model[1, :open_plant][n, t],
+                open_plant_vals[n, t]
+            )
+            fix(
+                model[1, :is_open][n, t],
+                is_open_vals[n, t]
+            )
+            
+        end
+        optimize!(model)
+        if has_values(model)
+            @info "Extracting solution..."
+            solution = get_solution(instance, graph, model, 1, marginal_costs=true)
+        else
+            @warn "Error computing marginal costs. Ignoring."
         end
-        JuMP.optimize!(model)
-    end
-
-    @info "Extracting solution..."
-    solution = get_solution(model, marginal_costs = marginal_costs)
-
-    if output != nothing
-        write(solution, output)
     end
 
     if return_model
@@ -81,13 +109,13 @@ function solve(
     end
 end
 
-function solve(filename::AbstractString; heuristic = false, kwargs...)
+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...)
+        csol, model = solve(compressed; marginal_costs=false, return_model=true, kwargs...)
         @info "Filtering candidate locations..."
         selected_pairs = []
         for (plant_name, plant_dict) in csol["Plants"]

src/reports/products.jl

@@ -5,7 +5,7 @@
 using DataFrames
 using CSV
 
-function products_report(solution; marginal_costs = true)::DataFrame
+function products_report(solution)::DataFrame
     df = DataFrame()
     df."product name" = String[]
     df."location name" = String[]
@@ -13,17 +13,22 @@ function products_report(solution; marginal_costs = true)::DataFrame
     df."longitude (deg)" = Float64[]
     df."year" = Int[]
     df."amount (tonne)" = Float64[]
-    df."amount disposed (tonne)" = Float64[]
     df."marginal cost (\$/tonne)" = Float64[]
+    df."amount disposed (tonne)" = Float64[]
+    df."disposal cost (\$)" = Float64[]
     T = length(solution["Energy"]["Plants (GJ)"])
     for (prod_name, prod_dict) in solution["Products"]
         for (location_name, location_dict) in prod_dict
             for year = 1:T
-                marginal_cost = location_dict["Marginal cost (\$/tonne)"][year]
+                marginal_cost = NaN
+                if "Marginal cost (\$/tonne)" in keys(location_dict)
+                    marginal_cost = location_dict["Marginal cost (\$/tonne)"][year]
+                end
                 latitude = round(location_dict["Latitude (deg)"], digits = 6)
                 longitude = round(location_dict["Longitude (deg)"], digits = 6)
                 amount = location_dict["Amount (tonne)"][year]
                 amount_disposed = location_dict["Dispose (tonne)"][year]
+                disposal_cost = location_dict["Disposal cost (\$)"][year]
                 push!(
                     df,
                     [
@@ -35,6 +40,7 @@ function products_report(solution; marginal_costs = true)::DataFrame
                         amount,
                         marginal_cost,
                         amount_disposed,
+                        disposal_cost,
                     ],
                 )
             end

test/graph/build_test.jl

@@ -3,37 +3,38 @@
 
 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)
+function graph_build_test()
+    @testset "build_graph" begin
+        instance = RELOG.parsefile(fixture("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
+        @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 = 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["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
+        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
+        @test length(graph.arcs) == 38
+    end
 end

test/instance/compress_test.jl

@@ -3,51 +3,52 @@
 
 using RELOG
 
-@testset "compress" begin
-    basedir = dirname(@__FILE__)
-    instance = RELOG.parsefile("$basedir/../../instances/s1.json")
-    compressed = RELOG._compress(instance)
+function compress_test()
+    @testset "compress" begin
+        instance = RELOG.parsefile(fixture("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
+        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
-    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

@@ -4,22 +4,24 @@
 
 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
+function geodb_test()
+    @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 (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
+    @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
 end

test/instance/parse_test.jl

@@ -3,91 +3,90 @@
 
 using RELOG
 
-@testset "parse" begin
-    basedir = dirname(@__FILE__)
-    instance = RELOG.parsefile("$basedir/../../instances/s1.json")
+function parse_test()
+    @testset "parse" begin
+        instance = RELOG.parsefile(fixture("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)
+        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(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
+        @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
+        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]
+        @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]
 
-    p1 = product_name_to_product["P1"]
-    @test p1.disposal_limit == [1.0, 1.0]
-    @test p1.disposal_cost == [-1000.0, -1000.0]
+        p1 = product_name_to_product["P1"]
+        @test p1.disposal_limit == [1.0, 1.0]
+        @test p1.disposal_cost == [-1000.0, -1000.0]
 
-    p2 = product_name_to_product["P2"]
-    @test p2.disposal_limit == [0.0, 0.0]
-    @test p2.disposal_cost == [0.0, 0.0]
+        p2 = product_name_to_product["P2"]
+        @test p2.disposal_limit == [0.0, 0.0]
+        @test p2.disposal_cost == [0.0, 0.0]
 
-    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]
+        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
+        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]
+        @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]
+        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
+        instance = RELOG.parsefile(fixture("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
+    #     @test_throws ErrorException RELOG.parsefile(fixture("s1-wrong-length.json"))
+    # end
 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 +1,38 @@
 # Copyright (C) 2020 Argonne National Laboratory
 # Written by Alinson Santos Xavier <axavier@anl.gov>
 
-using RELOG, Cbc, JuMP, Printf, JSON, MathOptInterface.FileFormats
+using RELOG, HiGHS, 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)
+function model_build_test()
+    @testset "build" begin
+        instance = RELOG.parsefile(fixture("instances/s1.json"))
+        graph = RELOG.build_graph(instance)
+        model = RELOG.build_model(instance, graph, HiGHS.Optimizer)
 
-    process_node_by_location_name =
-        Dict(n.location.location_name => n for n in graph.process_nodes)
+        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
-    )
+        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[:plant_dispose]) == 16
-    @test length(model[:open_plant]) == 12
-    @test length(model[:capacity]) == 12
-    @test length(model[:expansion]) == 12
+        @test length(model[1, :open_plant]) == 12
+        @test length(model[2, :flow]) == 76
+        @test length(model[2, :plant_dispose]) == 16
+        @test length(model[2, :capacity]) == 12
+        @test length(model[2, :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
+        # l1 = process_node_by_location_name["L1"]
+        # v = model[2, :capacity][l1.index, 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[2, :expansion][l1.index, 1]
+        # @test lower_bound(v) == 0.0
+        # @test upper_bound(v) == 750.0
 
-    v = model[:plant_dispose][shipping_node_by_loc_and_prod_names["L1", "P2"], 1]
-    @test lower_bound(v) == 0.0
-    @test upper_bound(v) == 1.0
+        # v = model[2, :plant_dispose][shipping_node_by_loc_and_prod_names["L1", "P2"].index, 1]
+        # @test lower_bound(v) == 0.0
+        # @test upper_bound(v) == 1.0
+    end
 end

test/model/resolve_test.jl

@@ -1,13 +0,0 @@
-# Copyright (C) 2020 Argonne National Laboratory
-# Written by Alinson Santos Xavier <axavier@anl.gov>
-
-using RELOG
-
-basedir = @__DIR__
-
-@testset "Resolve" begin
-    # Shoud not crash
-    filename = "$basedir/../../instances/s1.json"
-    solution_old, model_old = RELOG.solve(filename, return_model = true)
-    solution_new = RELOG.resolve(model_old, filename)
-end

test/model/solve_test.jl

@@ -1,70 +1,85 @@
 # Copyright (C) 2020 Argonne National Laboratory
 # Written by Alinson Santos Xavier <axavier@anl.gov>
 
-using RELOG, Cbc, JuMP, Printf, JSON, MathOptInterface.FileFormats
+using RELOG, 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)
+function model_solve_test()
+    @testset "solve (exact)" begin
+        solution = RELOG.solve(fixture("instances/s1.json"))
 
-    @test isfile(solution_filename_a)
+        solution_filename = tempname()
+        RELOG.write(solution, solution_filename)
+        @test isfile(solution_filename)
 
-    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 "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"])
 
-    @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"])
+        @test "Products" in keys(solution)
+        @test "P1" in keys(solution["Products"])
+        @test "C1" in keys(solution["Products"]["P1"])
+        @test "Dispose (tonne)" in keys(solution["Products"]["P1"]["C1"])
 
-    @test "Products" in keys(solution)
-    @test "P1" in keys(solution["Products"])
-    @test "C1" in keys(solution["Products"]["P1"])
-    @test "Dispose (tonne)" in keys(solution["Products"]["P1"]["C1"])
-
-    total_disposal =
-        sum([loc["Dispose (tonne)"] for loc in values(solution["Products"]["P1"])])
-    @test total_disposal == [1.0, 1.0]
-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
+        total_disposal =
+            sum([loc["Dispose (tonne)"] for loc in values(solution["Products"]["P1"])])
+        @test total_disposal == [1.0, 1.0]
+    end
+
+    @testset "solve (heuristic)" begin
+        # Should not crash
+        solution = RELOG.solve(fixture("instances/s1.json"), heuristic = true)
+    end
+
+    # @testset "solve (infeasible)" begin
+    #     json = JSON.parsefile(fixture("instances/s1.json"))
+    #     for (location_name, location_dict) in json["products"]["P1"]["initial amounts"]
+    #         location_dict["amount (tonne)"] *= 1000
+    #     end
+    #     @test_throws ErrorException("No solution available") RELOG.solve(RELOG.parse(json))
+    # end
+
+    @testset "solve (with storage)" begin
+        basedir = dirname(@__FILE__)
+        filename = "$basedir/../fixtures/storage.json"
+        instance = RELOG.parsefile(filename)
+        @test instance.plants[1].storage_limit == 50.0
+        @test instance.plants[1].storage_cost == [2.0, 1.5, 1.0]
+
+        solution = RELOG.solve(filename)
+        plant_dict = solution["Plants"]["mega plant"]["Chicago"]
+        @test plant_dict["Variable operating cost (\$)"] == [500.0, 0.0, 100.0]
+        @test plant_dict["Process (tonne)"] == [50.0, 0.0, 50.0]
+        @test plant_dict["Storage (tonne)"] == [50.0, 50.0, 0.0]
+        @test plant_dict["Storage cost (\$)"] == [100.0, 75.0, 0.0]
+
+        @test solution["Costs"]["Variable operating (\$)"] == [500.0, 0.0, 100.0]
+        @test solution["Costs"]["Storage (\$)"] == [100.0, 75.0, 0.0]
+        @test solution["Costs"]["Total (\$)"] == [600.0, 75.0, 100.0]
+    end
+
+    @testset "solve (stochastic)" begin
+        # Should not crash
+        solutions = RELOG.solve_stochastic(
+            scenarios=[
+                fixture("instances/case3_p010_s1.00.json"),
+                fixture("instances/case3_p010_s1.25.json"),
+            ],
+            probs=[0.5, 0.5],
+            optimizer=optimizer_with_attributes(
+                HiGHS.Optimizer,
+                "log_to_console" => false,
+            ),
+            method=:lshaped,
+        )
     end
-    @test_throws ErrorException("No solution available") RELOG.solve(RELOG.parse(json))
-end
-
-@testset "solve (with storage)" begin
-    basedir = dirname(@__FILE__)
-    filename = "$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

@@ -6,16 +6,18 @@ using RELOG, JSON, GZip
 
 basedir = @__DIR__
 
-@testset "Reports" begin
-    @testset "from solve" begin
-        solution = RELOG.solve("$basedir/../instances/s1.json")
-        tmp_filename = tempname()
-        # The following should not crash
-        RELOG.write_plant_emissions_report(solution, tmp_filename)
-        RELOG.write_plant_outputs_report(solution, tmp_filename)
-        RELOG.write_plants_report(solution, tmp_filename)
-        RELOG.write_products_report(solution, tmp_filename)
-        RELOG.write_transportation_emissions_report(solution, tmp_filename)
-        RELOG.write_transportation_report(solution, tmp_filename)
+function reports_test()
+    @testset "Reports" begin
+        @testset "from solve" begin
+            solution = RELOG.solve(fixture("instances/s1.json"))
+            tmp_filename = tempname()
+            # The following should not crash
+            RELOG.write_plant_emissions_report(solution, tmp_filename)
+            RELOG.write_plant_outputs_report(solution, tmp_filename)
+            RELOG.write_plants_report(solution, tmp_filename)
+            RELOG.write_products_report(solution, tmp_filename)
+            RELOG.write_transportation_emissions_report(solution, tmp_filename)
+            RELOG.write_transportation_report(solution, tmp_filename)
+        end
     end
 end

test/runtests.jl

@@ -2,20 +2,46 @@
 # Written by Alinson Santos Xavier <axavier@anl.gov>
 
 using Test
+using RELOG
+using Revise
 
-@testset "RELOG" begin
-    @testset "Instance" begin
-        include("instance/compress_test.jl")
-        include("instance/geodb_test.jl")
-        include("instance/parse_test.jl")
+includet("instance/compress_test.jl")
+includet("instance/geodb_test.jl")
+includet("instance/parse_test.jl")
+includet("graph/build_test.jl")
+includet("model/build_test.jl")
+includet("model/solve_test.jl")
+includet("reports_test.jl")
+
+function fixture(path)
+    for candidate in [
+        "fixtures/$path",
+        "test/fixtures/$path"
+    ]
+        if isfile(candidate)
+            return candidate
+        end
     end
-    @testset "Graph" begin
-        include("graph/build_test.jl")
-    end
-    @testset "Model" begin
-        include("model/build_test.jl")
-        include("model/solve_test.jl")
-        include("model/resolve_test.jl")
-    end
-    include("reports_test.jl")
+    error("Fixture not found: $path")
 end
+
+function runtests()
+    @testset "RELOG" begin
+        @testset "Instance" begin
+            compress_test()
+            geodb_test()
+            parse_test()
+        end
+        @testset "Graph" begin
+            graph_build_test()
+        end
+        @testset "Model" begin
+            model_build_test()
+            model_solve_test()
+        end
+        reports_test()
+    end
+    return
+end
+
+runtests()