Update CHANGELOG

Fix OrderedCollections version
Implement resolve
2025-12-06 07:48:50 -06:00 · 2021-07-23 17:42:48 -05:00 · 2021-07-23 17:42:29 -05:00 · 2021-07-21 14:53:49 -05:00 · 2021-07-21 14:18:10 -05:00 · 2021-07-21 14:11:01 -05:00
56 changed files with 2674 additions and 9339 deletions
--- a/.github/workflows/lint.yml
+++ b/.github/workflows/lint.yml
@@ -0,0 +1,27 @@
+name: Lint
+on:
+  push:
+  pull_request:
+jobs:
+  build:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: julia-actions/setup-julia@latest
+        with:
+          version: '1'
+      - uses: actions/checkout@v1
+      - name: Format check
+        shell: julia --color=yes {0}
+        run: |
+          using Pkg
+          Pkg.add(PackageSpec(name="JuliaFormatter", version="0.14.4"))
+          using JuliaFormatter
+          format("src", verbose=true)
+          format("test", verbose=true)
+          out = String(read(Cmd(`git diff`)))
+          if isempty(out)
+              exit(0)
+          end
+          @error "Some files have not been formatted !!!"
+          write(stdout, out)
+          exit(1)
--- a/.github/workflows/tagbot.yml
+++ b/.github/workflows/tagbot.yml
@@ -0,0 +1,15 @@
+name: TagBot
+on:
+  issue_comment:
+    types:
+      - created
+  workflow_dispatch:
+jobs:
+  TagBot:
+    if: github.event_name == 'workflow_dispatch' || github.actor == 'JuliaTagBot'
+    runs-on: ubuntu-latest
+    steps:
+      - uses: JuliaRegistries/TagBot@v1
+        with:
+          token: ${{ secrets.GITHUB_TOKEN }}
+          ssh: ${{ secrets.DOCUMENTER_KEY }}
--- a/.github/workflows/test.yml
+++ b/.github/workflows/test.yml
@@ -1,14 +1,16 @@
 name: Build & Test
 on:
-  - push
-  - pull_request
+  push:
+  pull_request:
+  schedule:
+    - cron: '45 10 * * *'
 jobs:
  test:
    name: Julia ${{ matrix.version }} - ${{ matrix.os }} - ${{ matrix.arch }}
    runs-on: ${{ matrix.os }}
    strategy:
      matrix:
-        version: ['1.3', '1.4', '1.5', 'nightly']
+        version: ['1.3', '1.4', '1.5', '1.6']
        os:
          - ubuntu-latest
        arch:
--- a/.gitignore
+++ b/.gitignore
@@ -8,3 +8,7 @@ instances/*.py
 notebooks
 .idea
 *.lp
+Manifest.toml
+data
+build
+benchmark
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,28 +1,49 @@
-# Version 0.5.0 (TBD)
+# Changelog

+All notable changes to this project will be documented in this file.
+
+- The format is based on [Keep a Changelog][changelog].
+- This project adheres to [Semantic Versioning][semver].
+- For versions before 1.0, we follow the [Pkg.jl convention][pkjjl]
+  that `0.a.b` is compatible with `0.a.c`.
+
+[changelog]: https://keepachangelog.com/en/1.0.0/
+[semver]: https://semver.org/spec/v2.0.0.html
+[pkjjl]: https://pkgdocs.julialang.org/v1/compatibility/#compat-pre-1.0
+
+## [0.5.1] -- 2021-07-23
+## 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
 - Allow plants to store input material for processing in later years

-# Version 0.4.0 (Sep 18, 2020)
-
+## [0.4.0] -- 2020-09-18
+## Added
 - Generate simplified solution reports (CSV)

-# Version 0.3.3 (Aug 13, 2020)
-
+## [0.3.3] -- 2020-10-13
+## Added
 - Add option to write solution to JSON file in RELOG.solve
 - Improve error message when instance is infeasible
 - Make output file more readable

-# Version 0.3.2 (Aug 7, 2020)
-
+## [0.3.2] -- 2020-10-07
+## Added
 - Add "building period" parameter

-# Version 0.3.1 (July 17, 2020)
-
+## [0.3.1] -- 2020-07-17
+## Fixed
 - Fix expansion cost breakdown

-# Version 0.3.0 (June 25, 2020)
-
+## [0.3.0] -- 2020-06-25
+## Added
 - Track emissions and energy (transportation and plants)
+
+## Changed
 - Minor changes to input file format:
    - Make all dictionary keys lowercase
    - Rename "outputs (tonne)" to "outputs (tonne/tonne)"
--- a/3
+++ b/3
@@ -17,6 +17,9 @@ clean:
 docs:
 	mkdocs build -d ../docs/$(VERSION)/

+format:
+	julia -e 'using JuliaFormatter; format(["src", "test"], verbose=true);'
+
 test: build/test.log

 test-watch:
--- a/Manifest.toml
+++ b/Manifest.toml
@@ -1,441 +0,0 @@
-# This file is machine-generated - editing it directly is not advised
-
-[[Base64]]
-uuid = "2a0f44e3-6c83-55bd-87e4-b1978d98bd5f"
-
-[[BenchmarkTools]]
-deps = ["JSON", "Logging", "Printf", "Statistics", "UUIDs"]
-git-tree-sha1 = "9e62e66db34540a0c919d72172cc2f642ac71260"
-uuid = "6e4b80f9-dd63-53aa-95a3-0cdb28fa8baf"
-version = "0.5.0"
-
-[[BinaryProvider]]
-deps = ["Libdl", "Logging", "SHA"]
-git-tree-sha1 = "ecdec412a9abc8db54c0efc5548c64dfce072058"
-uuid = "b99e7846-7c00-51b0-8f62-c81ae34c0232"
-version = "0.5.10"
-
-[[Bzip2_jll]]
-deps = ["Libdl", "Pkg"]
-git-tree-sha1 = "03a44490020826950c68005cafb336e5ba08b7e8"
-uuid = "6e34b625-4abd-537c-b88f-471c36dfa7a0"
-version = "1.0.6+4"
-
-[[CEnum]]
-git-tree-sha1 = "215a9aa4a1f23fbd05b92769fdd62559488d70e9"
-uuid = "fa961155-64e5-5f13-b03f-caf6b980ea82"
-version = "0.4.1"
-
-[[CSV]]
-deps = ["CategoricalArrays", "DataFrames", "Dates", "Mmap", "Parsers", "PooledArrays", "SentinelArrays", "Tables", "Unicode"]
-git-tree-sha1 = "a390152e6850405a48ca51bd7ca33d11a21d6230"
-uuid = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
-version = "0.7.7"
-
-[[Calculus]]
-deps = ["LinearAlgebra"]
-git-tree-sha1 = "f641eb0a4f00c343bbc32346e1217b86f3ce9dad"
-uuid = "49dc2e85-a5d0-5ad3-a950-438e2897f1b9"
-version = "0.5.1"
-
-[[CategoricalArrays]]
-deps = ["DataAPI", "Future", "JSON", "Missings", "Printf", "Statistics", "StructTypes", "Unicode"]
-git-tree-sha1 = "2ac27f59196a68070e132b25713f9a5bbc5fa0d2"
-uuid = "324d7699-5711-5eae-9e2f-1d82baa6b597"
-version = "0.8.3"
-
-[[Cbc]]
-deps = ["BinaryProvider", "Libdl", "MathOptInterface", "MathProgBase", "SparseArrays", "Test"]
-git-tree-sha1 = "62d80f448b5d77b3f0a59cecf6197aad2a3aa280"
-uuid = "9961bab8-2fa3-5c5a-9d89-47fab24efd76"
-version = "0.6.7"
-
-[[Clp]]
-deps = ["BinaryProvider", "CEnum", "Clp_jll", "Libdl", "MathOptInterface", "SparseArrays"]
-git-tree-sha1 = "581763750759c1e38df2a35a0b3bdee496a062c7"
-uuid = "e2554f3b-3117-50c0-817c-e040a3ddf72d"
-version = "0.8.1"
-
-[[Clp_jll]]
-deps = ["CoinUtils_jll", "CompilerSupportLibraries_jll", "Libdl", "OpenBLAS32_jll", "Osi_jll", "Pkg"]
-git-tree-sha1 = "79263d9383ca89b35f31c33ab5b880536a8413a4"
-uuid = "06985876-5285-5a41-9fcb-8948a742cc53"
-version = "1.17.6+6"
-
-[[CodecBzip2]]
-deps = ["Bzip2_jll", "Libdl", "TranscodingStreams"]
-git-tree-sha1 = "2e62a725210ce3c3c2e1a3080190e7ca491f18d7"
-uuid = "523fee87-0ab8-5b00-afb7-3ecf72e48cfd"
-version = "0.7.2"
-
-[[CodecZlib]]
-deps = ["TranscodingStreams", "Zlib_jll"]
-git-tree-sha1 = "ded953804d019afa9a3f98981d99b33e3db7b6da"
-uuid = "944b1d66-785c-5afd-91f1-9de20f533193"
-version = "0.7.0"
-
-[[CoinUtils_jll]]
-deps = ["CompilerSupportLibraries_jll", "Libdl", "OpenBLAS32_jll", "Pkg"]
-git-tree-sha1 = "ee1f06ab89337b7f194c29377ab174e752cdf60d"
-uuid = "be027038-0da8-5614-b30d-e42594cb92df"
-version = "2.11.3+3"
-
-[[CommonSubexpressions]]
-deps = ["MacroTools", "Test"]
-git-tree-sha1 = "7b8a93dba8af7e3b42fecabf646260105ac373f7"
-uuid = "bbf7d656-a473-5ed7-a52c-81e309532950"
-version = "0.3.0"
-
-[[Compat]]
-deps = ["Base64", "Dates", "DelimitedFiles", "Distributed", "InteractiveUtils", "LibGit2", "Libdl", "LinearAlgebra", "Markdown", "Mmap", "Pkg", "Printf", "REPL", "Random", "SHA", "Serialization", "SharedArrays", "Sockets", "SparseArrays", "Statistics", "Test", "UUIDs", "Unicode"]
-git-tree-sha1 = "7c7f4cda0d58ec999189d70f5ee500348c4b4df1"
-uuid = "34da2185-b29b-5c13-b0c7-acf172513d20"
-version = "3.16.0"
-
-[[CompilerSupportLibraries_jll]]
-deps = ["Libdl", "Pkg"]
-git-tree-sha1 = "7c4f882c41faa72118841185afc58a2eb00ef612"
-uuid = "e66e0078-7015-5450-92f7-15fbd957f2ae"
-version = "0.3.3+0"
-
-[[CoordinateTransformations]]
-deps = ["LinearAlgebra", "StaticArrays"]
-git-tree-sha1 = "c230b1d94db9fdd073168830437e64b9db627fcb"
-uuid = "150eb455-5306-5404-9cee-2592286d6298"
-version = "0.6.0"
-
-[[DataAPI]]
-git-tree-sha1 = "176e23402d80e7743fc26c19c681bfb11246af32"
-uuid = "9a962f9c-6df0-11e9-0e5d-c546b8b5ee8a"
-version = "1.3.0"
-
-[[DataFrames]]
-deps = ["CategoricalArrays", "Compat", "DataAPI", "Future", "InvertedIndices", "IteratorInterfaceExtensions", "Missings", "PooledArrays", "Printf", "REPL", "Reexport", "SortingAlgorithms", "Statistics", "TableTraits", "Tables", "Unicode"]
-git-tree-sha1 = "a7c1c9a6e47a92321bbc9d500dab9b04cc4a6a39"
-uuid = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
-version = "0.21.7"
-
-[[DataStructures]]
-deps = ["InteractiveUtils", "OrderedCollections"]
-git-tree-sha1 = "88d48e133e6d3dd68183309877eac74393daa7eb"
-uuid = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
-version = "0.17.20"
-
-[[DataValueInterfaces]]
-git-tree-sha1 = "bfc1187b79289637fa0ef6d4436ebdfe6905cbd6"
-uuid = "e2d170a0-9d28-54be-80f0-106bbe20a464"
-version = "1.0.0"
-
-[[Dates]]
-deps = ["Printf"]
-uuid = "ade2ca70-3891-5945-98fb-dc099432e06a"
-
-[[DelimitedFiles]]
-deps = ["Mmap"]
-uuid = "8bb1440f-4735-579b-a4ab-409b98df4dab"
-
-[[DiffResults]]
-deps = ["StaticArrays"]
-git-tree-sha1 = "da24935df8e0c6cf28de340b958f6aac88eaa0cc"
-uuid = "163ba53b-c6d8-5494-b064-1a9d43ac40c5"
-version = "1.0.2"
-
-[[DiffRules]]
-deps = ["NaNMath", "Random", "SpecialFunctions"]
-git-tree-sha1 = "eb0c34204c8410888844ada5359ac8b96292cfd1"
-uuid = "b552c78f-8df3-52c6-915a-8e097449b14b"
-version = "1.0.1"
-
-[[Distributed]]
-deps = ["Random", "Serialization", "Sockets"]
-uuid = "8ba89e20-285c-5b6f-9357-94700520ee1b"
-
-[[ForwardDiff]]
-deps = ["CommonSubexpressions", "DiffResults", "DiffRules", "NaNMath", "Random", "SpecialFunctions", "StaticArrays"]
-git-tree-sha1 = "1d090099fb82223abc48f7ce176d3f7696ede36d"
-uuid = "f6369f11-7733-5829-9624-2563aa707210"
-version = "0.10.12"
-
-[[Future]]
-deps = ["Random"]
-uuid = "9fa8497b-333b-5362-9e8d-4d0656e87820"
-
-[[GZip]]
-deps = ["Libdl"]
-git-tree-sha1 = "039be665faf0b8ae36e089cd694233f5dee3f7d6"
-uuid = "92fee26a-97fe-5a0c-ad85-20a5f3185b63"
-version = "0.5.1"
-
-[[Geodesy]]
-deps = ["CoordinateTransformations", "Dates", "LinearAlgebra", "StaticArrays", "Test"]
-git-tree-sha1 = "f80ea86cb88db337a1906e245e495592f0b5cc25"
-uuid = "0ef565a4-170c-5f04-8de2-149903a85f3d"
-version = "0.5.0"
-
-[[HTTP]]
-deps = ["Base64", "Dates", "IniFile", "MbedTLS", "Sockets"]
-git-tree-sha1 = "c7ec02c4c6a039a98a15f955462cd7aea5df4508"
-uuid = "cd3eb016-35fb-5094-929b-558a96fad6f3"
-version = "0.8.19"
-
-[[IniFile]]
-deps = ["Test"]
-git-tree-sha1 = "098e4d2c533924c921f9f9847274f2ad89e018b8"
-uuid = "83e8ac13-25f8-5344-8a64-a9f2b223428f"
-version = "0.5.0"
-
-[[InteractiveUtils]]
-deps = ["Markdown"]
-uuid = "b77e0a4c-d291-57a0-90e8-8db25a27a240"
-
-[[InvertedIndices]]
-deps = ["Test"]
-git-tree-sha1 = "15732c475062348b0165684ffe28e85ea8396afc"
-uuid = "41ab1584-1d38-5bbf-9106-f11c6c58b48f"
-version = "1.0.0"
-
-[[IteratorInterfaceExtensions]]
-git-tree-sha1 = "a3f24677c21f5bbe9d2a714f95dcd58337fb2856"
-uuid = "82899510-4779-5014-852e-03e436cf321d"
-version = "1.0.0"
-
-[[JSON]]
-deps = ["Dates", "Mmap", "Parsers", "Unicode"]
-git-tree-sha1 = "81690084b6198a2e1da36fcfda16eeca9f9f24e4"
-uuid = "682c06a0-de6a-54ab-a142-c8b1cf79cde6"
-version = "0.21.1"
-
-[[JSONSchema]]
-deps = ["BinaryProvider", "HTTP", "JSON"]
-git-tree-sha1 = "b0a7f9328967df5213691d318a03cf70ea8c76b1"
-uuid = "7d188eb4-7ad8-530c-ae41-71a32a6d4692"
-version = "0.2.0"
-
-[[JuMP]]
-deps = ["Calculus", "DataStructures", "ForwardDiff", "LinearAlgebra", "MathOptInterface", "MutableArithmetics", "NaNMath", "Random", "SparseArrays", "Statistics"]
-git-tree-sha1 = "cbab42e2e912109d27046aa88f02a283a9abac7c"
-uuid = "4076af6c-e467-56ae-b986-b466b2749572"
-version = "0.21.3"
-
-[[LibGit2]]
-deps = ["Printf"]
-uuid = "76f85450-5226-5b5a-8eaa-529ad045b433"
-
-[[Libdl]]
-uuid = "8f399da3-3557-5675-b5ff-fb832c97cbdb"
-
-[[LinearAlgebra]]
-deps = ["Libdl"]
-uuid = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
-
-[[Logging]]
-uuid = "56ddb016-857b-54e1-b83d-db4d58db5568"
-
-[[MacroTools]]
-deps = ["Markdown", "Random"]
-git-tree-sha1 = "f7d2e3f654af75f01ec49be82c231c382214223a"
-uuid = "1914dd2f-81c6-5fcd-8719-6d5c9610ff09"
-version = "0.5.5"
-
-[[Markdown]]
-deps = ["Base64"]
-uuid = "d6f4376e-aef5-505a-96c1-9c027394607a"
-
-[[MathOptInterface]]
-deps = ["BenchmarkTools", "CodecBzip2", "CodecZlib", "JSON", "JSONSchema", "LinearAlgebra", "MutableArithmetics", "OrderedCollections", "SparseArrays", "Test", "Unicode"]
-git-tree-sha1 = "27f2ef85879b8f1d144266ab44f076ba0dfbd8a1"
-uuid = "b8f27783-ece8-5eb3-8dc8-9495eed66fee"
-version = "0.9.13"
-
-[[MathProgBase]]
-deps = ["LinearAlgebra", "SparseArrays"]
-git-tree-sha1 = "9abbe463a1e9fc507f12a69e7f29346c2cdc472c"
-uuid = "fdba3010-5040-5b88-9595-932c9decdf73"
-version = "0.7.8"
-
-[[MbedTLS]]
-deps = ["Dates", "MbedTLS_jll", "Random", "Sockets"]
-git-tree-sha1 = "426a6978b03a97ceb7ead77775a1da066343ec6e"
-uuid = "739be429-bea8-5141-9913-cc70e7f3736d"
-version = "1.0.2"
-
-[[MbedTLS_jll]]
-deps = ["Libdl", "Pkg"]
-git-tree-sha1 = "c0b1286883cac4e2b617539de41111e0776d02e8"
-uuid = "c8ffd9c3-330d-5841-b78e-0817d7145fa1"
-version = "2.16.8+0"
-
-[[Missings]]
-deps = ["DataAPI"]
-git-tree-sha1 = "ed61674a0864832495ffe0a7e889c0da76b0f4c8"
-uuid = "e1d29d7a-bbdc-5cf2-9ac0-f12de2c33e28"
-version = "0.4.4"
-
-[[Mmap]]
-uuid = "a63ad114-7e13-5084-954f-fe012c677804"
-
-[[MutableArithmetics]]
-deps = ["LinearAlgebra", "SparseArrays", "Test"]
-git-tree-sha1 = "6cf09794783b9de2e662c4e8b60d743021e338d0"
-uuid = "d8a4904e-b15c-11e9-3269-09a3773c0cb0"
-version = "0.2.10"
-
-[[NaNMath]]
-git-tree-sha1 = "c84c576296d0e2fbb3fc134d3e09086b3ea617cd"
-uuid = "77ba4419-2d1f-58cd-9bb1-8ffee604a2e3"
-version = "0.3.4"
-
-[[OpenBLAS32_jll]]
-deps = ["CompilerSupportLibraries_jll", "Libdl", "Pkg"]
-git-tree-sha1 = "793b33911239d2651c356c823492b58d6490d36a"
-uuid = "656ef2d0-ae68-5445-9ca0-591084a874a2"
-version = "0.3.9+4"
-
-[[OpenSpecFun_jll]]
-deps = ["CompilerSupportLibraries_jll", "Libdl", "Pkg"]
-git-tree-sha1 = "d51c416559217d974a1113522d5919235ae67a87"
-uuid = "efe28fd5-8261-553b-a9e1-b2916fc3738e"
-version = "0.5.3+3"
-
-[[OrderedCollections]]
-git-tree-sha1 = "16c08bf5dba06609fe45e30860092d6fa41fde7b"
-uuid = "bac558e1-5e72-5ebc-8fee-abe8a469f55d"
-version = "1.3.1"
-
-[[Osi_jll]]
-deps = ["CoinUtils_jll", "CompilerSupportLibraries_jll", "Libdl", "OpenBLAS32_jll", "Pkg"]
-git-tree-sha1 = "bd436a97280df40938e66ae8d18e57aceb072856"
-uuid = "7da25872-d9ce-5375-a4d3-7a845f58efdd"
-version = "0.108.5+3"
-
-[[PackageCompiler]]
-deps = ["Libdl", "Pkg", "UUIDs"]
-git-tree-sha1 = "98aa9c653e1dc3473bb5050caf8501293db9eee1"
-uuid = "9b87118b-4619-50d2-8e1e-99f35a4d4d9d"
-version = "1.2.1"
-
-[[Parsers]]
-deps = ["Dates", "Test"]
-git-tree-sha1 = "8077624b3c450b15c087944363606a6ba12f925e"
-uuid = "69de0a69-1ddd-5017-9359-2bf0b02dc9f0"
-version = "1.0.10"
-
-[[Pkg]]
-deps = ["Dates", "LibGit2", "Libdl", "Logging", "Markdown", "Printf", "REPL", "Random", "SHA", "UUIDs"]
-uuid = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
-
-[[PooledArrays]]
-deps = ["DataAPI"]
-git-tree-sha1 = "b1333d4eced1826e15adbdf01a4ecaccca9d353c"
-uuid = "2dfb63ee-cc39-5dd5-95bd-886bf059d720"
-version = "0.5.3"
-
-[[Printf]]
-deps = ["Unicode"]
-uuid = "de0858da-6303-5e67-8744-51eddeeeb8d7"
-
-[[ProgressBars]]
-deps = ["Printf"]
-git-tree-sha1 = "e66732bbdaad368cfc642cef1f639df5812dc818"
-uuid = "49802e3a-d2f1-5c88-81d8-b72133a6f568"
-version = "0.6.0"
-
-[[REPL]]
-deps = ["InteractiveUtils", "Markdown", "Sockets"]
-uuid = "3fa0cd96-eef1-5676-8a61-b3b8758bbffb"
-
-[[Random]]
-deps = ["Serialization"]
-uuid = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
-
-[[Reexport]]
-deps = ["Pkg"]
-git-tree-sha1 = "7b1d07f411bc8ddb7977ec7f377b97b158514fe0"
-uuid = "189a3867-3050-52da-a836-e630ba90ab69"
-version = "0.2.0"
-
-[[SHA]]
-uuid = "ea8e919c-243c-51af-8825-aaa63cd721ce"
-
-[[SentinelArrays]]
-deps = ["Dates", "Random"]
-git-tree-sha1 = "7a74946ace3b34fbb6c10e61b6e250b33d7e758c"
-uuid = "91c51154-3ec4-41a3-a24f-3f23e20d615c"
-version = "1.2.15"
-
-[[Serialization]]
-uuid = "9e88b42a-f829-5b0c-bbe9-9e923198166b"
-
-[[SharedArrays]]
-deps = ["Distributed", "Mmap", "Random", "Serialization"]
-uuid = "1a1011a3-84de-559e-8e89-a11a2f7dc383"
-
-[[Sockets]]
-uuid = "6462fe0b-24de-5631-8697-dd941f90decc"
-
-[[SortingAlgorithms]]
-deps = ["DataStructures", "Random", "Test"]
-git-tree-sha1 = "03f5898c9959f8115e30bc7226ada7d0df554ddd"
-uuid = "a2af1166-a08f-5f64-846c-94a0d3cef48c"
-version = "0.3.1"
-
-[[SparseArrays]]
-deps = ["LinearAlgebra", "Random"]
-uuid = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
-
-[[SpecialFunctions]]
-deps = ["OpenSpecFun_jll"]
-git-tree-sha1 = "d8d8b8a9f4119829410ecd706da4cc8594a1e020"
-uuid = "276daf66-3868-5448-9aa4-cd146d93841b"
-version = "0.10.3"
-
-[[StaticArrays]]
-deps = ["LinearAlgebra", "Random", "Statistics"]
-git-tree-sha1 = "016d1e1a00fabc556473b07161da3d39726ded35"
-uuid = "90137ffa-7385-5640-81b9-e52037218182"
-version = "0.12.4"
-
-[[Statistics]]
-deps = ["LinearAlgebra", "SparseArrays"]
-uuid = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
-
-[[StructTypes]]
-deps = ["Dates", "UUIDs"]
-git-tree-sha1 = "1ed04f622a39d2e5a6747c3a70be040c00333933"
-uuid = "856f2bd8-1eba-4b0a-8007-ebc267875bd4"
-version = "1.1.0"
-
-[[TableTraits]]
-deps = ["IteratorInterfaceExtensions"]
-git-tree-sha1 = "b1ad568ba658d8cbb3b892ed5380a6f3e781a81e"
-uuid = "3783bdb8-4a98-5b6b-af9a-565f29a5fe9c"
-version = "1.0.0"
-
-[[Tables]]
-deps = ["DataAPI", "DataValueInterfaces", "IteratorInterfaceExtensions", "LinearAlgebra", "TableTraits", "Test"]
-git-tree-sha1 = "b7f762e9820b7fab47544c36f26f54ac59cf8abf"
-uuid = "bd369af6-aec1-5ad0-b16a-f7cc5008161c"
-version = "1.0.5"
-
-[[Test]]
-deps = ["Distributed", "InteractiveUtils", "Logging", "Random"]
-uuid = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
-
-[[TranscodingStreams]]
-deps = ["Random", "Test"]
-git-tree-sha1 = "7c53c35547de1c5b9d46a4797cf6d8253807108c"
-uuid = "3bb67fe8-82b1-5028-8e26-92a6c54297fa"
-version = "0.9.5"
-
-[[UUIDs]]
-deps = ["Random", "SHA"]
-uuid = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"
-
-[[Unicode]]
-uuid = "4ec0a83e-493e-50e2-b9ac-8f72acf5a8f5"
-
-[[Zlib_jll]]
-deps = ["Libdl", "Pkg"]
-git-tree-sha1 = "fdd89e5ab270ea0f2a0174bd9093e557d06d4bfa"
-uuid = "83775a58-1f1d-513f-b197-d71354ab007a"
-version = "1.2.11+16"
--- a/Project.toml
+++ b/Project.toml
@@ -1,14 +1,16 @@
 name = "RELOG"
 uuid = "a2afcdf7-cf04-4913-85f9-c0d81ddf2008"
 authors = ["Alinson S Xavier <axavier@anl.gov>"]
-version = "0.5.0"
+version = "0.5.1"

 [deps]
+CRC = "44b605c4-b955-5f2b-9b6d-d2bd01d3d205"
 CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
 Cbc = "9961bab8-2fa3-5c5a-9d89-47fab24efd76"
 Clp = "e2554f3b-3117-50c0-817c-e040a3ddf72d"
 DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
 DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
+Downloads = "f43a241f-c20a-4ad4-852c-f6b1247861c6"
 GZip = "92fee26a-97fe-5a0c-ad85-20a5f3185b63"
 Geodesy = "0ef565a4-170c-5f04-8de2-149903a85f3d"
 JSON = "682c06a0-de6a-54ab-a142-c8b1cf79cde6"
@@ -16,13 +18,17 @@ 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"
+Shapefile = "8e980c4a-a4fe-5da2-b3a7-4b4b0353a2f4"
 Statistics = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+ZipFile = "a5390f91-8eb1-5f08-bee0-b1d1ffed6cea"

 [compat]
+CRC = "4"
 CSV = "0.7"
 Cbc = "0.6"
 Clp = "0.8"
@@ -31,9 +37,12 @@ DataStructures = "0.17"
 GZip = "0.5"
 Geodesy = "0.5"
 JSON = "0.21"
-JSONSchema = "0.2"
+JSONSchema = "0.3"
 JuMP = "0.21"
 MathOptInterface = "0.9"
+OrderedCollections = "1.4"
 PackageCompiler = "1"
 ProgressBars = "0.6"
+Shapefile = "0.7"
+ZipFile = "0.9"
 julia = "1"
--- a/instances/s2.json
+++ b/instances/s2.json
@@ -0,0 +1,347 @@
+{
+    "parameters": {
+        "time horizon (years)": 2
+    },
+    "products": {
+        "P1": {
+            "transportation cost ($/km/tonne)": [
+                0.015,
+                0.015
+            ],
+            "transportation energy (J/km/tonne)": [
+                0.12,
+                0.11
+            ],
+            "transportation emissions (tonne/km/tonne)": {
+                "CO2": [
+                    0.052,
+                    0.050
+                ],
+                "CH4": [
+                    0.003,
+                    0.002
+                ]
+            },
+            "initial amounts": {
+                "C1": {
+                    "location": "2018-us-county:17043",
+                    "amount (tonne)": [
+                        934.56,
+                        934.56
+                    ]
+                },
+                "C2": {
+                    "latitude (deg)": 7.0,
+                    "longitude (deg)": 19.0,
+                    "amount (tonne)": [
+                        198.95,
+                        198.95
+                    ]
+                },
+                "C3": {
+                    "latitude (deg)": 84.0,
+                    "longitude (deg)": 76.0,
+                    "amount (tonne)": [
+                        212.97,
+                        212.97
+                    ]
+                },
+                "C4": {
+                    "latitude (deg)": 21.0,
+                    "longitude (deg)": 16.0,
+                    "amount (tonne)": [
+                        352.19,
+                        352.19
+                    ]
+                },
+                "C5": {
+                    "latitude (deg)": 32.0,
+                    "longitude (deg)": 92.0,
+                    "amount (tonne)": [
+                        510.33,
+                        510.33
+                    ]
+                },
+                "C6": {
+                    "latitude (deg)": 14.0,
+                    "longitude (deg)": 62.0,
+                    "amount (tonne)": [
+                        471.66,
+                        471.66
+                    ]
+                },
+                "C7": {
+                    "latitude (deg)": 30.0,
+                    "longitude (deg)": 83.0,
+                    "amount (tonne)": [
+                        785.21,
+                        785.21
+                    ]
+                },
+                "C8": {
+                    "latitude (deg)": 35.0,
+                    "longitude (deg)": 40.0,
+                    "amount (tonne)": [
+                        706.17,
+                        706.17
+                    ]
+                },
+                "C9": {
+                    "latitude (deg)": 74.0,
+                    "longitude (deg)": 52.0,
+                    "amount (tonne)": [
+                        30.08,
+                        30.08
+                    ]
+                },
+                "C10": {
+                    "latitude (deg)": 22.0,
+                    "longitude (deg)": 54.0,
+                    "amount (tonne)": [
+                        536.52,
+                        536.52
+                    ]
+                }
+            }
+        },
+        "P2": {
+            "transportation cost ($/km/tonne)": [
+                0.02,
+                0.02
+            ]
+        },
+        "P3": {
+            "transportation cost ($/km/tonne)": [
+                0.0125,
+                0.0125
+            ]
+        },
+        "P4": {
+            "transportation cost ($/km/tonne)": [
+                0.0175,
+                0.0175
+            ]
+        }
+    },
+    "plants": {
+        "F1": {
+            "input": "P1",
+            "outputs (tonne/tonne)": {
+                "P2": 0.2,
+                "P3": 0.5
+            },
+            "energy (GJ/tonne)": [
+                0.12,
+                0.11
+            ],
+            "emissions (tonne/tonne)": {
+                "CO2": [
+                    0.052,
+                    0.050
+                ],
+                "CH4": [
+                    0.003,
+                    0.002
+                ]
+            },
+            "locations": {
+                "L1": {
+                    "latitude (deg)": 0.0,
+                    "longitude (deg)": 0.0,
+                    "disposal": {
+                        "P2": {
+                            "cost ($/tonne)": [
+                                -10.0,
+                                -10.0
+                            ],
+                            "limit (tonne)": [
+                                1.0,
+                                1.0
+                            ]
+                        },
+                        "P3": {
+                            "cost ($/tonne)": [
+                                -10.0,
+                                -10.0
+                            ],
+                            "limit (tonne)": [
+                                1.0,
+                                1.0
+                            ]
+                        }
+                    },
+                    "capacities (tonne)": {
+                        "250.0": {
+                            "opening cost ($)": [
+                                500.0,
+                                500.0
+                            ],
+                            "fixed operating cost ($)": [
+                                30.0,
+                                30.0
+                            ],
+                            "variable operating cost ($/tonne)": [
+                                30.0,
+                                30.0
+                            ]
+                        },
+                        "1000.0": {
+                            "opening cost ($)": [
+                                1250.0,
+                                1250.0
+                            ],
+                            "fixed operating cost ($)": [
+                                30.0,
+                                30.0
+                            ],
+                            "variable operating cost ($/tonne)": [
+                                30.0,
+                                30.0
+                            ]
+                        }
+                    }
+                },
+                "L2": {
+                    "location": "2018-us-county:17043",
+                    "capacities (tonne)": {
+                        "0.0": {
+                            "opening cost ($)": [
+                                1000,
+                                1000
+                            ],
+                            "fixed operating cost ($)": [
+                                50.0,
+                                50.0
+                            ],
+                            "variable operating cost ($/tonne)": [
+                                50.0,
+                                50.0
+                            ]
+                        },
+                        "10000.0": {
+                            "opening cost ($)": [
+                                10000,
+                                10000
+                            ],
+                            "fixed operating cost ($)": [
+                                50.0,
+                                50.0
+                            ],
+                            "variable operating cost ($/tonne)": [
+                                50.0,
+                                50.0
+                            ]
+                        }
+                    }
+                }
+            }
+        },
+        "F2": {
+            "input": "P2",
+            "outputs (tonne/tonne)": {
+                "P3": 0.05,
+                "P4": 0.80
+            },
+            "locations": {
+                "L3": {
+                    "latitude (deg)": 25.0,
+                    "longitude (deg)": 65.0,
+                    "disposal": {
+                        "P3": {
+                            "cost ($/tonne)": [
+                                100.0,
+                                100.0
+                            ]
+                        }
+                    },
+                    "capacities (tonne)": {
+                        "1000.0": {
+                            "opening cost ($)": [
+                                3000,
+                                3000
+                            ],
+                            "fixed operating cost ($)": [
+                                50.0,
+                                50.0
+                            ],
+                            "variable operating cost ($/tonne)": [
+                                50.0,
+                                50.0
+                            ]
+                        }
+                    }
+                },
+                "L4": {
+                    "latitude (deg)": 0.75,
+                    "longitude (deg)": 0.20,
+                    "capacities (tonne)": {
+                        "10000": {
+                            "opening cost ($)": [
+                                3000,
+                                3000
+                            ],
+                            "fixed operating cost ($)": [
+                                50.0,
+                                50.0
+                            ],
+                            "variable operating cost ($/tonne)": [
+                                50.0,
+                                50.0
+                            ]
+                        }
+                    }
+                }
+            }
+        },
+        "F3": {
+            "input": "P4",
+            "locations": {
+                "L5": {
+                    "latitude (deg)": 100.0,
+                    "longitude (deg)": 100.0,
+                    "capacities (tonne)": {
+                        "15000": {
+                            "opening cost ($)": [
+                                0.0,
+                                0.0
+                            ],
+                            "fixed operating cost ($)": [
+                                0.0,
+                                0.0
+                            ],
+                            "variable operating cost ($/tonne)": [
+                                -15.0,
+                                -15.0
+                            ]
+                        }
+                    }
+                }
+            }
+        },
+        "F4": {
+            "input": "P3",
+            "locations": {
+                "L6": {
+                    "latitude (deg)": 50.0,
+                    "longitude (deg)": 50.0,
+                    "capacities (tonne)": {
+                        "10000": {
+                            "opening cost ($)": [
+                                0.0,
+                                0.0
+                            ],
+                            "fixed operating cost ($)": [
+                                0.0,
+                                0.0
+                            ],
+                            "variable operating cost ($/tonne)": [
+                                -15.0,
+                                -15.0
+                            ]
+                        }
+                    }
+                }
+            }
+        }
+    }
+}
--- a/src/RELOG.jl
+++ b/src/RELOG.jl
@@ -3,9 +3,26 @@
 # Released under the modified BSD license. See COPYING.md for more details.

 module RELOG
-    include("dotdict.jl")
-    include("instance.jl")
-    include("graph.jl")
-    include("model.jl")
-    include("reports.jl")
+
+include("instance/structs.jl")
+
+include("graph/structs.jl")
+
+include("graph/build.jl")
+include("graph/csv.jl")
+include("instance/compress.jl")
+include("instance/geodb.jl")
+include("instance/parse.jl")
+include("instance/validate.jl")
+include("model/build.jl")
+include("model/getsol.jl")
+include("model/solve.jl")
+include("model/resolve.jl")
+include("reports/plant_emissions.jl")
+include("reports/plant_outputs.jl")
+include("reports/plants.jl")
+include("reports/products.jl")
+include("reports/tr_emissions.jl")
+include("reports/tr.jl")
+include("reports/write.jl")
 end
--- a/src/docs/format.md
+++ b/src/docs/format.md
@@ -182,6 +182,38 @@ The keys in the `capacities (tonne)` dictionary should be the amounts (in tonnes
 }
 ```

+### Geographic database
+
+Instead of specifying locations using latitudes and longitudes, it is also possible to specify them using unique identifiers, such as the name of a US state, or the county FIPS code. This works anywhere `latitude (deg)` and `longitude (deg)` are expected. For example, instead of:
+```json
+{
+    "initial amounts": {
+        "C1": {
+            "latitude (deg)": 37.27182,
+            "longitude (deg)": -119.2704,
+            "amount (tonne)": [934.56, 934.56]
+        },
+    }
+}
+```
+is is possible to write:
+```json
+{
+    "initial amounts": {
+        "C1": {
+            "location": "us-state:CA",
+            "amount (tonne)": [934.56, 934.56]
+        },
+    }
+}
+```
+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)
+
 ### Current limitations

 * Each plant can only be opened exactly once. After open, the plant remains open until the end of the simulation.
@@ -192,4 +224,3 @@ The keys in the `capacities (tonne)` dictionary should be the amounts (in tonnes
 ## Output Data Format (JSON)

 To be documented.
-
--- a/src/docs/reports.md
+++ b/src/docs/reports.md
@@ -6,15 +6,13 @@ In this page, we also illustrate what types of charts and visualizations can be

 ## Plants report

-Report showing plant costs, capacities, energy expenditure and utilization factors.
-
-Generated by `RELOG.write_plants_report(solution, filename)`. For a concrete example, see [nimh_plants.csv](https://github.com/ANL-CEEESA/RELOG/blob/master/test/fixtures/nimh_plants.csv).
+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 in the simulation.
+| `year` | What year this row corresponds to. This reports includes one row for each year.
 | `latitude (deg)` | Latitude of the plant.
 | `longitude (deg)` | Longitude of the plant.
 | `capacity (tonne)`  | Capacity of the plant at this point in time.
@@ -72,16 +70,14 @@ gp.GeoDataFrame(data, geometry=points).plot(ax=ax);

 ## Plant outputs report

-Report showing amount of products produced, sent and disposed of by each plant, as well as disposal costs.
-
-Generated by `RELOG.write_plant_outputs_report(solution, filename)`. For a concrete example, see [nimh_plant_outputs.csv](https://github.com/ANL-CEEESA/RELOG/blob/master/test/fixtures/nimh_plant_outputs.csv).
+Report showing amount of products produced, sent and disposed of by each plant, as well as disposal costs. Generated by `RELOG.write_plant_outputs_report(solution, filename)`.


 | Column                                | Description
 |:--------------------------------------|---------------|
 | `plant type`  | Plant type.
 | `location name`  | Location name.
-| `year`  | What year this row corresponds to. This reports includes one row for each year in the simulation.
+| `year`  | What year this row corresponds to. This reports includes one row for each year.
 | `product name`  | Product being produced.
 | `amount produced (tonne)` | Amount of product produced this year.
 | `amount sent (tonne)` | Amount of product produced by this plant and sent to another plant for further processing this year.
@@ -110,9 +106,7 @@ sns.barplot(x="amount produced (tonne)",

 ## Plant emissions report

-Report showing amount of emissions produced by each plant.
-
-Generated by `RELOG.write_plant_emissions_report(solution, filename)`. For a concrete example, see [nimh_plant_emissions.csv](https://github.com/ANL-CEEESA/RELOG/blob/master/test/fixtures/nimh_plant_emissions.csv).
+Report showing amount of emissions produced by each plant. Generated by `RELOG.write_plant_emissions_report(solution, filename)`.

 | Column                                | Description
 |:--------------------------------------|---------------|
@@ -141,11 +135,24 @@ sns.barplot(x="plant type",

 <img src="../images/ex_emissions.png" width="500px"/>

+## Products report
+
+Report showing primary product amounts, locations and marginal costs. Generated by `RELOG.write_products_report(solution, filename)`.
+
+| Column                                | Description
+|:--------------------------------------|---------------|
+| `product name`  | Product name.
+| `location name`  | Name of the collection center.
+| `latitude (deg)` | Latitude of the collection center.
+| `longitude (deg)` | Longitude of the collection center.
+| `year`  | What year this row corresponds to. This reports includes one row for each year.
+| `amount (tonne)` | Amount of product available at this collection center.
+| `marginal cost ($/tonne)` | Cost to process one additional tonne of this product coming from this collection center.
+
+
 ## Transportation report

-Report showing amount of product sent from initial locations to plants, and from one plant to another. Includes the distance between each pair of locations, amount-distance shipped, transportation costs and energy expenditure.
-
-Generated by `RELOG.write_transportation_report(solution, filename)`. For a concrete example, see [nimh_transportation.csv](https://github.com/ANL-CEEESA/RELOG/blob/master/test/fixtures/nimh_transportation.csv).
+Report showing amount of product sent from initial locations to plants, and from one plant to another. Includes the distance between each pair of locations, amount-distance shipped, transportation costs and energy expenditure. Generated by `RELOG.write_transportation_report(solution, filename)`.


 | Column                                | Description
@@ -231,9 +238,7 @@ gp.GeoDataFrame(data, geometry=points).plot(ax=ax,

 ## Transportation emissions report

-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)`. For a concrete example, see [nimh_transportation_emissions.csv](https://github.com/ANL-CEEESA/RELOG/blob/master/test/fixtures/nimh_transportation_emissions.csv).
+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
 |:--------------------------------------|---------------|
--- a/src/docs/usage.md
+++ b/src/docs/usage.md
@@ -66,9 +66,45 @@ RELOG.write_transportation_report(solution, "transportation.csv")

 For a complete description of the file formats above, and for a complete list of available reports, see the [data format page](format.md).

-## 4. Advanced options
+## 4. What-If Analysis

-### 4.1 Changing the solver
+Fundamentally, RELOG decides when and where to build plants based on a deterministic optimization problem that minimizes costs for a particular input file provided by the user. In practical situations, it may not be possible to perfectly estimate some (or most) entries in this input file in advance, such as costs, demands and emissions. In this situation, it may be interesting to evaluate how well does the facility location plan produced by RELOG work if costs, demands and emissions turn out to be different.
+
+To simplify this what-if analysis, RELOG provides the `resolve` method, which updates a previous solution based on a new scenario, but keeps some of the previous decisions fixed. More precisely, given an optimal solution produced by RELOG and a new input file describing the new scenario, the `resolve` method reoptimizes the supply chain and produces a new solution which still builds the same set of plants as before, in exactly the same locations and with the same capacities, but that may now utilize the plants differently, based on the new data. For example, in the new solution, plants that were previously used at full capacity may now be utilized at half-capacity instead. As another example, regions that were previously served by a certain plant may now be served by a different one.
+
+The following snippet shows how to use the method:
+
+```julia
+# Import package
+using RELOG
+
+# Optimize for the average scenario
+solution_avg, model_avg = RELOG.solve("input_avg.json", return_model=true)
+
+# Write reports for the average scenario
+RELOG.write_plants_report(solution_avg, "plants_avg.csv")
+RELOG.write_transportation_report(solution_avg, "transportation_avg.csv")
+
+# Re-optimize for the high-demand scenario, keeping plants fixed
+solution_high = RELOG.resolve(model_avg, "input_high.json")
+
+# Write reports for the high-demand scenario
+RELOG.write_plants_report(solution_high, "plants_high.csv")
+RELOG.write_transportation_report(solution_high, "transportation_high.csv")
+```
+
+To use the `resolve` method, the new input file should be very similar to the original one. Only the following entries are allowed to change:
+
+- **Products:** Transportation costs, energy, emissions and initial amounts (latitude, longitude and amount).
+- **Plants:** Energy and emissions.
+- **Plant's location:** Latitude and longitude.
+- **Plant's storage:** Cost.
+- **Plant's capacity:** Opening cost, fixed operating cost and variable operating cost.
+
+
+## 5. Advanced options
+
+### 5.1 Changing the solver

 By default, RELOG internally uses [Cbc](https://github.com/coin-or/Cbc), an open-source and freely-available Mixed-Integer Linear Programming solver developed by the [COIN-OR Project](https://www.coin-or.org/). For larger-scale test cases, a commercial solver such as Gurobi, CPLEX or XPRESS is recommended. The following snippet shows how to switch from Cbc to Gurobi, for example:

@@ -84,7 +120,7 @@ RELOG.solve("instance.json",
            optimizer=gurobi)
 ```

-### 4.2 Multi-period heuristics
+### 5.2 Multi-period heuristics

 For large-scale instances, it may be too time-consuming to find an exact optimal solution to the multi-period version of the problem. For these situations, RELOG includes a heuristic solution method, which proceeds as follows:

--- a/src/dotdict.jl
+++ b/src/dotdict.jl
@@ -1,68 +0,0 @@
-# RELOG: Reverse Logistics Optimization
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-struct DotDict
-    inner::Dict
-end
-
-DotDict() = DotDict(Dict())
-
-function Base.setproperty!(d::DotDict, key::Symbol, value)
-    setindex!(getfield(d, :inner), value, key)
-end
-
-function Base.getproperty(d::DotDict, key::Symbol)
-    (key == :inner ? getfield(d, :inner) : d.inner[key])
-end
-
-function Base.getindex(d::DotDict, key::Int64)
-    d.inner[Symbol(key)]
-end
-
-function Base.getindex(d::DotDict, key::Symbol)
-    d.inner[key]
-end
-
-function Base.keys(d::DotDict)
-    keys(d.inner)
-end
-
-function Base.values(d::DotDict)
-    values(d.inner)
-end
-
-function Base.iterate(d::DotDict)
-    iterate(values(d.inner))
-end
-
-function Base.iterate(d::DotDict, v::Int64)
-    iterate(values(d.inner), v)
-end
-
-function Base.length(d::DotDict)
-    length(values(d.inner))
-end
-
-function Base.show(io::IO, d::DotDict)
-    print(io, "DotDict with $(length(keys(d.inner))) entries:\n")
-    count = 0
-    for k in keys(d.inner)
-        count += 1
-        if count > 10
-            print(io, "  ...\n")
-            break
-        end
-        print(io, "  :$(k) => $(d.inner[k])\n")
-    end
-end
-
-function recursive_to_dot_dict(el)
-    if typeof(el) == Dict{String, Any}
-        return DotDict(Dict(Symbol(k) => recursive_to_dot_dict(el[k]) for k in keys(el)))
-    else
-        return el
-    end
-end
-
-export recursive_to_dot_dict
--- a/src/graph/build.jl
+++ b/src/graph/build.jl
@@ -4,69 +4,41 @@

 using Geodesy

-
-abstract type Node
+function calculate_distance(source_lat, source_lon, dest_lat, dest_lon)::Float64
+    x = LLA(source_lat, source_lon, 0.0)
+    y = LLA(dest_lat, dest_lon, 0.0)
+    return round(distance(x, y) / 1000.0, digits = 2)
 end

-
-mutable struct Arc
-    source::Node
-    dest::Node
-    values::Dict{String, Float64}
-end
-
-
-mutable struct ProcessNode <: Node
-    index::Int
-    location::Plant
-    incoming_arcs::Array{Arc}
-    outgoing_arcs::Array{Arc}
-end
-
-
-mutable struct ShippingNode <: Node
-    index::Int
-    location::Union{Plant, CollectionCenter}
-    product::Product
-    incoming_arcs::Array{Arc}
-    outgoing_arcs::Array{Arc}
-end
-
-
-mutable struct Graph
-    process_nodes::Array{ProcessNode}
-    plant_shipping_nodes::Array{ShippingNode}
-    collection_shipping_nodes::Array{ShippingNode}
-    arcs::Array{Arc}
-end
-
-
 function build_graph(instance::Instance)::Graph
    arcs = []
    next_index = 0
    process_nodes = ProcessNode[]
    plant_shipping_nodes = ShippingNode[]
    collection_shipping_nodes = ShippingNode[]
-    
-    process_nodes_by_input_product = Dict(product => ProcessNode[]
-                                          for product in instance.products)
-    shipping_nodes_by_plant = Dict(plant => []
-                                   for plant in instance.plants)
-    
+
+    name_to_process_node_map = Dict{Tuple{AbstractString,AbstractString},ProcessNode}()
+
+    process_nodes_by_input_product =
+        Dict(product => ProcessNode[] for product in instance.products)
+    shipping_nodes_by_plant = Dict(plant => [] for plant in instance.plants)
+
    # Build collection center shipping nodes
    for center in instance.collection_centers
        node = ShippingNode(next_index, center, center.product, [], [])
        next_index += 1
        push!(collection_shipping_nodes, node)
    end
-    
+
    # Build process and shipping nodes for plants
    for plant in instance.plants
        pn = ProcessNode(next_index, plant, [], [])
        next_index += 1
        push!(process_nodes, pn)
        push!(process_nodes_by_input_product[plant.input], pn)
-        
+
+        name_to_process_node_map[(plant.plant_name, plant.location_name)] = pn
+
        for product in keys(plant.output)
            sn = ShippingNode(next_index, plant, product, [], [])
            next_index += 1
@@ -74,14 +46,16 @@ function build_graph(instance::Instance)::Graph
            push!(shipping_nodes_by_plant[plant], sn)
        end
    end
-    
+
    # Build arcs from collection centers to plants, and from one plant to another
    for source in [collection_shipping_nodes; plant_shipping_nodes]
        for dest in process_nodes_by_input_product[source.product]
-            distance = calculate_distance(source.location.latitude,
-                                          source.location.longitude,
-                                          dest.location.latitude,
-                                          dest.location.longitude)
+            distance = calculate_distance(
+                source.location.latitude,
+                source.location.longitude,
+                dest.location.latitude,
+                dest.location.longitude,
+            )
            values = Dict("distance" => distance)
            arc = Arc(source, dest, values)
            push!(source.outgoing_arcs, arc)
@@ -89,7 +63,7 @@ function build_graph(instance::Instance)::Graph
            push!(arcs, arc)
        end
    end
-    
+
    # Build arcs from process nodes to shipping nodes within a plant
    for source in process_nodes
        plant = source.location
@@ -102,25 +76,25 @@ function build_graph(instance::Instance)::Graph
            push!(arcs, arc)
        end
    end
-    
-    return Graph(process_nodes, 
-                 plant_shipping_nodes,
-                 collection_shipping_nodes,
-                 arcs)
+
+    return Graph(
+        process_nodes,
+        plant_shipping_nodes,
+        collection_shipping_nodes,
+        arcs,
+        name_to_process_node_map,
+    )
 end


-function to_csv(graph::Graph)
-    result = ""
-    for a in graph.arcs
-        result *= "$(a.source.index),$(a.dest.index)\n"
-    end
-    return result
-end
-
-
-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)
+function print_graph_stats(instance::Instance, graph::Graph)::Nothing
+    @info @sprintf("    %12d time periods", instance.time)
+    @info @sprintf("    %12d process nodes", length(graph.process_nodes))
+    @info @sprintf("    %12d shipping nodes (plant)", length(graph.plant_shipping_nodes))
+    @info @sprintf(
+        "    %12d shipping nodes (collection)",
+        length(graph.collection_shipping_nodes)
+    )
+    @info @sprintf("    %12d arcs", length(graph.arcs))
+    return
 end
--- a/src/graph/csv.jl
+++ b/src/graph/csv.jl
@@ -0,0 +1,11 @@
+# RELOG: Reverse Logistics Optimization
+# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+# Released under the modified BSD license. See COPYING.md for more details.
+
+function to_csv(graph::Graph)
+    result = ""
+    for a in graph.arcs
+        result *= "$(a.source.index),$(a.dest.index)\n"
+    end
+    return result
+end
--- a/src/graph/structs.jl
+++ b/src/graph/structs.jl
@@ -0,0 +1,44 @@
+# RELOG: Reverse Logistics Optimization
+# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+# Released under the modified BSD license. See COPYING.md for more details.
+
+using Geodesy
+
+abstract type Node end
+
+mutable struct Arc
+    source::Node
+    dest::Node
+    values::Dict{String,Float64}
+end
+
+mutable struct ProcessNode <: Node
+    index::Int
+    location::Plant
+    incoming_arcs::Vector{Arc}
+    outgoing_arcs::Vector{Arc}
+end
+
+mutable struct ShippingNode <: Node
+    index::Int
+    location::Union{Plant,CollectionCenter}
+    product::Product
+    incoming_arcs::Vector{Arc}
+    outgoing_arcs::Vector{Arc}
+end
+
+mutable struct Graph
+    process_nodes::Vector{ProcessNode}
+    plant_shipping_nodes::Vector{ShippingNode}
+    collection_shipping_nodes::Vector{ShippingNode}
+    arcs::Vector{Arc}
+    name_to_process_node_map::Dict{Tuple{AbstractString,AbstractString},ProcessNode}
+end
+
+function Base.show(io::IO, instance::Graph)
+    print(io, "RELOG graph with ")
+    print(io, "$(length(instance.process_nodes)) process nodes, ")
+    print(io, "$(length(instance.plant_shipping_nodes)) plant shipping nodes, ")
+    print(io, "$(length(instance.collection_shipping_nodes)) collection shipping nodes, ")
+    print(io, "$(length(instance.arcs)) arcs")
+end
--- a/src/instance.jl
+++ b/src/instance.jl
@@ -1,281 +0,0 @@
-# RELOG: Reverse Logistics Optimization
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-using DataStructures
-using JSON
-using JSONSchema
-using Printf
-using Statistics
-
-
-mutable struct Product
-    name::String
-    transportation_cost::Array{Float64}
-    transportation_energy::Array{Float64}
-    transportation_emissions::Dict{String, Array{Float64}}
-end
-
-
-mutable struct CollectionCenter
-    index::Int64
-    name::String
-    latitude::Float64
-    longitude::Float64
-    product::Product
-    amount::Array{Float64}
-end
-
-
-mutable struct PlantSize
-    capacity::Float64
-    variable_operating_cost::Array{Float64}
-    fixed_operating_cost::Array{Float64}
-    opening_cost::Array{Float64}
-end
-
-
-mutable struct Plant
-    index::Int64
-    plant_name::String
-    location_name::String
-    input::Product
-    output::Dict{Product, Float64}
-    latitude::Float64
-    longitude::Float64
-    disposal_limit::Dict{Product, Array{Float64}}
-    disposal_cost::Dict{Product, Array{Float64}}
-    sizes::Array{PlantSize}
-    energy::Array{Float64}
-    emissions::Dict{String, Array{Float64}}
-    storage_limit::Float64
-    storage_cost::Array{Float64}
-end
-
-
-mutable struct Instance
-    time::Int64
-    products::Array{Product, 1}
-    collection_centers::Array{CollectionCenter, 1}
-    plants::Array{Plant, 1}
-    building_period::Array{Int64}
-end
-
-
-function validate(json, schema)
-    result = JSONSchema.validate(json, schema)
-    if result !== nothing
-        if result isa JSONSchema.SingleIssue
-            path = join(result.path, " → ")
-            if length(path) == 0
-                path = "root"
-            end
-            msg = "$(result.msg) in $(path)"
-        else
-            msg = convert(String, result)
-        end
-        throw(msg)
-    end
-end
-
-
-function parsefile(path::String)::Instance
-    return RELOG.parse(JSON.parsefile(path))
-end
-
-
-function parse(json)::Instance
-    basedir = dirname(@__FILE__)
-    json_schema = JSON.parsefile("$basedir/schemas/input.json")
-    validate(json, Schema(json_schema))
-    
-    T = json["parameters"]["time horizon (years)"]
-    json_schema["definitions"]["TimeSeries"]["minItems"] = T
-    json_schema["definitions"]["TimeSeries"]["maxItems"] = T
-    validate(json, Schema(json_schema))
-    
-    building_period = [1]
-    if "building period (years)" in keys(json)
-        building_period = json["building period (years)"]
-    end
-    
-    plants = Plant[]
-    products = Product[]
-    collection_centers = CollectionCenter[]
-    prod_name_to_product = Dict{String, Product}()
-    
-    # Create products
-    for (product_name, product_dict) in json["products"]
-        cost = product_dict["transportation cost (\$/km/tonne)"]
-        energy = zeros(T)
-        emissions = Dict()
-        
-        if "transportation energy (J/km/tonne)" in keys(product_dict)
-            energy = product_dict["transportation energy (J/km/tonne)"]
-        end
-        
-        if "transportation emissions (tonne/km/tonne)" in keys(product_dict)
-            emissions = product_dict["transportation emissions (tonne/km/tonne)"]
-        end
-        
-        product = Product(product_name, cost, energy, emissions)
-        push!(products, product)
-        prod_name_to_product[product_name] = product
-        
-        # Create collection centers
-        if "initial amounts" in keys(product_dict)
-            for (center_name, center_dict) in product_dict["initial amounts"]
-                center = CollectionCenter(length(collection_centers) + 1,
-                                          center_name,
-                                          center_dict["latitude (deg)"],
-                                          center_dict["longitude (deg)"],
-                                          product,
-                                          center_dict["amount (tonne)"])
-                push!(collection_centers, center)
-            end
-        end
-    end
-    
-    # Create plants
-    for (plant_name, plant_dict) in json["plants"]
-        input = prod_name_to_product[plant_dict["input"]]
-        output = Dict()
-        
-        # Plant outputs
-        if "outputs (tonne/tonne)" in keys(plant_dict)
-            output = Dict(prod_name_to_product[key] => value
-                          for (key, value) in plant_dict["outputs (tonne/tonne)"]
-                          if value > 0)
-        end
-        
-        energy = zeros(T)
-        emissions = Dict()
-        
-        if "energy (GJ/tonne)" in keys(plant_dict)
-            energy = plant_dict["energy (GJ/tonne)"]
-        end
-        
-        if "emissions (tonne/tonne)" in keys(plant_dict)
-            emissions = plant_dict["emissions (tonne/tonne)"]
-        end
-        
-        for (location_name, location_dict) in plant_dict["locations"]
-            sizes = PlantSize[]
-            disposal_limit = Dict(p => [0.0 for t in 1:T] for p in keys(output))
-            disposal_cost = Dict(p => [0.0 for t in 1:T] for p in keys(output))
-            
-            # Disposal
-            if "disposal" in keys(location_dict)
-                for (product_name, disposal_dict) in location_dict["disposal"]
-                    limit = [1e8 for t in 1:T]
-                    if "limit (tonne)" in keys(disposal_dict)
-                       limit = disposal_dict["limit (tonne)"]
-                    end
-                    disposal_limit[prod_name_to_product[product_name]] = limit
-                    disposal_cost[prod_name_to_product[product_name]] = disposal_dict["cost (\$/tonne)"]
-                end
-            end
-            
-            # Capacities
-            for (capacity_name, capacity_dict) in location_dict["capacities (tonne)"]
-                push!(sizes, PlantSize(Base.parse(Float64, capacity_name),
-                                       capacity_dict["variable operating cost (\$/tonne)"],
-                                       capacity_dict["fixed operating cost (\$)"],
-                                       capacity_dict["opening cost (\$)"]))
-            end
-            length(sizes) > 1 ||  push!(sizes, sizes[1])
-            sort!(sizes, by = x -> x.capacity)
-            
-            # Storage
-            storage_limit = 0
-            storage_cost = zeros(T)
-            if "storage" in keys(location_dict)
-                storage_dict = location_dict["storage"]
-                storage_limit = storage_dict["limit (tonne)"]
-                storage_cost = storage_dict["cost (\$/tonne)"]
-            end
-            
-            # Validation: Capacities
-            if length(sizes) != 2
-                throw("At most two capacities are supported")
-            end
-            if sizes[1].variable_operating_cost != sizes[2].variable_operating_cost
-                throw("Variable operating costs must be the same for all capacities")
-            end
-
-            plant = Plant(length(plants) + 1,
-                          plant_name,
-                          location_name,
-                          input,
-                          output,
-                          location_dict["latitude (deg)"],
-                          location_dict["longitude (deg)"],
-                          disposal_limit,
-                          disposal_cost,
-                          sizes,
-                          energy,
-                          emissions,
-                          storage_limit,
-                          storage_cost)
-            
-            push!(plants, plant)
-        end
-    end
-    
-    @info @sprintf("%12d collection centers", length(collection_centers))
-    @info @sprintf("%12d candidate plant locations", length(plants))
-    
-    return Instance(T, products, collection_centers, plants, building_period)
-end
-
-
-"""
-    _compress(instance::Instance)
-
-Create a single-period instance from a multi-period one. Specifically,
-replaces every time-dependent attribute, such as initial_amounts,
-by a list with a single element, which is either a sum, an average,
-or something else that makes sense to that specific attribute.
-"""
-function _compress(instance::Instance)::Instance
-    T = instance.time
-    compressed = deepcopy(instance)
-    compressed.time = 1
-    compressed.building_period = [1]
-    
-    # Compress products
-    for p in compressed.products
-        p.transportation_cost = [mean(p.transportation_cost)]
-        p.transportation_energy = [mean(p.transportation_energy)]
-        for (emission_name, emission_value) in p.transportation_emissions
-            p.transportation_emissions[emission_name] = [mean(emission_value)]
-        end
-    end
-    
-    # Compress collection centers
-    for c in compressed.collection_centers
-        c.amount = [maximum(c.amount) * T]
-    end
-    
-    # Compress plants
-    for plant in compressed.plants
-        plant.energy = [mean(plant.energy)]
-        for (emission_name, emission_value) in plant.emissions
-            plant.emissions[emission_name] = [mean(emission_value)]
-        end
-        for s in plant.sizes
-            s.capacity *= T
-            s.variable_operating_cost = [mean(s.variable_operating_cost)]
-            s.opening_cost = [s.opening_cost[1]]
-            s.fixed_operating_cost = [sum(s.fixed_operating_cost)]
-        end
-        for (prod_name, disp_limit) in plant.disposal_limit
-            plant.disposal_limit[prod_name] = [sum(disp_limit)]
-        end
-        for (prod_name, disp_cost) in plant.disposal_cost
-            plant.disposal_cost[prod_name] = [mean(disp_cost)]
-        end
-    end
-    
-    return compressed
-end
--- a/src/instance/compress.jl
+++ b/src/instance/compress.jl
@@ -0,0 +1,60 @@
+# RELOG: Reverse Logistics Optimization
+# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+# Released under the modified BSD license. See COPYING.md for more details.
+
+using DataStructures
+using JSON
+using JSONSchema
+using Printf
+using Statistics
+
+"""
+    _compress(instance::Instance)
+
+Create a single-period instance from a multi-period one. Specifically,
+replaces every time-dependent attribute, such as initial_amounts,
+by a list with a single element, which is either a sum, an average,
+or something else that makes sense to that specific attribute.
+"""
+function _compress(instance::Instance)::Instance
+    T = instance.time
+    compressed = deepcopy(instance)
+    compressed.time = 1
+    compressed.building_period = [1]
+
+    # Compress products
+    for p in compressed.products
+        p.transportation_cost = [mean(p.transportation_cost)]
+        p.transportation_energy = [mean(p.transportation_energy)]
+        for (emission_name, emission_value) in p.transportation_emissions
+            p.transportation_emissions[emission_name] = [mean(emission_value)]
+        end
+    end
+
+    # Compress collection centers
+    for c in compressed.collection_centers
+        c.amount = [maximum(c.amount) * T]
+    end
+
+    # Compress plants
+    for plant in compressed.plants
+        plant.energy = [mean(plant.energy)]
+        for (emission_name, emission_value) in plant.emissions
+            plant.emissions[emission_name] = [mean(emission_value)]
+        end
+        for s in plant.sizes
+            s.capacity *= T
+            s.variable_operating_cost = [mean(s.variable_operating_cost)]
+            s.opening_cost = [s.opening_cost[1]]
+            s.fixed_operating_cost = [sum(s.fixed_operating_cost)]
+        end
+        for (prod_name, disp_limit) in plant.disposal_limit
+            plant.disposal_limit[prod_name] = [sum(disp_limit)]
+        end
+        for (prod_name, disp_cost) in plant.disposal_cost
+            plant.disposal_cost[prod_name] = [mean(disp_cost)]
+        end
+    end
+
+    return compressed
+end
--- a/src/instance/geodb.jl
+++ b/src/instance/geodb.jl
@@ -0,0 +1,212 @@
+# RELOG: Reverse Logistics Optimization
+# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+# Released under the modified BSD license. See COPYING.md for more details.
+
+using CRC
+using CSV
+using DataFrames
+using Shapefile
+using Statistics
+using ZipFile
+using ProgressBars
+using OrderedCollections
+
+import Downloads: download
+import Base: parse
+
+crc32 = crc(CRC_32)
+
+struct GeoPoint
+    lat::Float64
+    lon::Float64
+end
+
+struct GeoRegion
+    centroid::GeoPoint
+    population::Int
+    GeoRegion(; centroid, population) = new(centroid, population)
+end
+
+DB_CACHE = Dict{String,Dict{String,GeoRegion}}()
+
+function centroid(geom::Shapefile.Polygon)::GeoPoint
+    x_max, x_min, y_max, y_min = -Inf, Inf, -Inf, Inf
+    for p in geom.points
+        x_max = max(x_max, p.x)
+        x_min = min(x_min, p.x)
+        y_max = max(y_max, p.y)
+        y_min = min(y_min, p.y)
+    end
+    x_center = (x_max + x_min) / 2.0
+    y_center = (y_max + y_min) / 2.0
+    return GeoPoint(round(y_center, digits = 5), round(x_center, digits = 5))
+end
+
+function _download_file(url, output, expected_crc32)::Nothing
+    if isfile(output)
+        return
+    end
+    mkpath(dirname(output))
+    @info "Downloading: $url"
+    fname = download(url)
+    actual_crc32 = open(crc32, fname)
+    expected_crc32 == actual_crc32 || error("CRC32 mismatch")
+    cp(fname, output)
+    return
+end
+
+function _download_zip(url, outputdir, expected_output_file, expected_crc32)::Nothing
+    if isfile(expected_output_file)
+        return
+    end
+    mkpath(outputdir)
+    @info "Downloading: $url"
+    zip_filename = download(url)
+    actual_crc32 = open(crc32, zip_filename)
+    expected_crc32 == actual_crc32 || error("CRC32 mismatch")
+    open(zip_filename) do zip_file
+        zr = ZipFile.Reader(zip_file)
+        for file in zr.files
+            open(joinpath(outputdir, file.name), "w") do output_file
+                write(output_file, read(file))
+            end
+        end
+    end
+    return
+end
+
+function _geodb_load_gov_census(;
+    db_name,
+    extract_cols,
+    shp_crc32,
+    shp_filename,
+    shp_url,
+    population_url,
+    population_crc32,
+    population_col,
+    population_preprocess,
+    population_join,
+)::Dict{String,GeoRegion}
+    basedir = joinpath(dirname(@__FILE__), "..", "..", "data", db_name)
+    csv_filename = "$basedir/locations.csv"
+    if !isfile(csv_filename)
+        # Download required files
+        _download_zip(shp_url, basedir, joinpath(basedir, shp_filename), shp_crc32)
+        _download_file(population_url, "$basedir/population.csv", population_crc32)
+
+        # Read shapefile
+        @info "Processing: $shp_filename"
+        table = Shapefile.Table(joinpath(basedir, shp_filename))
+        geoms = Shapefile.shapes(table)
+
+        # Build empty dataframe
+        df = DataFrame()
+        cols = extract_cols(table, 1)
+        for k in keys(cols)
+            df[!, k] = []
+        end
+        df[!, "latitude"] = Float64[]
+        df[!, "longitude"] = Float64[]
+
+        # Add regions to dataframe
+        for (i, geom) in tqdm(enumerate(geoms))
+            c = centroid(geom)
+            cols = extract_cols(table, i)
+            push!(df, [values(cols)..., c.lat, c.lon])
+        end
+        sort!(df)
+
+        # Join with population data
+        population = DataFrame(CSV.File("$basedir/population.csv"))
+        population_preprocess(population)
+        population = population[:, [population_join, population_col]]
+        rename!(population, population_col => "population")
+        df = leftjoin(df, population, on = population_join)
+
+        # Write output
+        CSV.write(csv_filename, df)
+    end
+    if db_name ∉ keys(DB_CACHE)
+        csv = CSV.File(csv_filename)
+        DB_CACHE[db_name] = Dict(
+            string(row.id) => GeoRegion(
+                centroid = GeoPoint(row.latitude, row.longitude),
+                population = (row.population === missing ? 0 : row.population),
+            ) for row in csv
+        )
+    end
+    return DB_CACHE[db_name]
+end
+
+# 2018 US counties
+# -----------------------------------------------------------------------------
+function _extract_cols_2018_us_county(
+    table::Shapefile.Table,
+    i::Int,
+)::OrderedDict{String,Any}
+    return OrderedDict(
+        "id" => table.STATEFP[i] * table.COUNTYFP[i],
+        "statefp" => table.STATEFP[i],
+        "countyfp" => table.COUNTYFP[i],
+        "name" => table.NAME[i],
+    )
+end
+
+function _population_preprocess_2018_us_county(df)
+    df[!, "id"] = [@sprintf("%02d%03d", row.STATE, row.COUNTY) for row in eachrow(df)]
+end
+
+function _geodb_load_2018_us_county()::Dict{String,GeoRegion}
+    return _geodb_load_gov_census(
+        db_name = "2018-us-county",
+        extract_cols = _extract_cols_2018_us_county,
+        shp_crc32 = 0x83eaec6d,
+        shp_filename = "cb_2018_us_county_500k.shp",
+        shp_url = "https://www2.census.gov/geo/tiger/GENZ2018/shp/cb_2018_us_county_500k.zip",
+        population_url = "https://www2.census.gov/programs-surveys/popest/datasets/2010-2019/counties/totals/co-est2019-alldata.csv",
+        population_crc32 = 0xf85b0405,
+        population_col = "POPESTIMATE2019",
+        population_join = "id",
+        population_preprocess = _population_preprocess_2018_us_county,
+    )
+end
+
+# US States
+# -----------------------------------------------------------------------------
+function _extract_cols_us_state(table::Shapefile.Table, i::Int)::OrderedDict{String,Any}
+    return OrderedDict(
+        "id" => table.STUSPS[i],
+        "statefp" => parse(Int, table.STATEFP[i]),
+        "name" => table.NAME[i],
+    )
+end
+
+function _population_preprocess_us_state(df)
+    rename!(df, "STATE" => "statefp")
+end
+
+function _geodb_load_us_state()::Dict{String,GeoRegion}
+    return _geodb_load_gov_census(
+        db_name = "us-state",
+        extract_cols = _extract_cols_us_state,
+        shp_crc32 = 0x9469e5ca,
+        shp_filename = "cb_2018_us_state_500k.shp",
+        shp_url = "https://www2.census.gov/geo/tiger/GENZ2018/shp/cb_2018_us_state_500k.zip",
+        population_url = "http://www2.census.gov/programs-surveys/popest/datasets/2010-2019/national/totals/nst-est2019-alldata.csv",
+        population_crc32 = 0x191cc64c,
+        population_col = "POPESTIMATE2019",
+        population_join = "statefp",
+        population_preprocess = _population_preprocess_us_state,
+    )
+end
+
+function geodb_load(db_name::AbstractString)::Dict{String,GeoRegion}
+    db_name == "2018-us-county" && return _geodb_load_2018_us_county()
+    db_name == "us-state" && return _geodb_load_us_state()
+    error("Unknown database: $db_name")
+end
+
+function geodb_query(name)::GeoRegion
+    db_name, id = split(name, ":")
+    return geodb_load(db_name)[id]
+end
--- a/src/instance/parse.jl
+++ b/src/instance/parse.jl
@@ -0,0 +1,180 @@
+# RELOG: Reverse Logistics Optimization
+# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+# Released under the modified BSD license. See COPYING.md for more details.
+
+using DataStructures
+using JSON
+using JSONSchema
+using Printf
+using Statistics
+
+function parsefile(path::String)::Instance
+    return RELOG.parse(JSON.parsefile(path))
+end
+
+function parse(json)::Instance
+    basedir = dirname(@__FILE__)
+    json_schema = JSON.parsefile("$basedir/../schemas/input.json")
+    validate(json, Schema(json_schema))
+
+    T = json["parameters"]["time horizon (years)"]
+    json_schema["definitions"]["TimeSeries"]["minItems"] = T
+    json_schema["definitions"]["TimeSeries"]["maxItems"] = T
+    validate(json, Schema(json_schema))
+
+    building_period = [1]
+    if "building period (years)" in keys(json)
+        building_period = json["building period (years)"]
+    end
+
+    plants = Plant[]
+    products = Product[]
+    collection_centers = CollectionCenter[]
+    prod_name_to_product = Dict{String,Product}()
+
+    # Create products
+    for (product_name, product_dict) in json["products"]
+        cost = product_dict["transportation cost (\$/km/tonne)"]
+        energy = zeros(T)
+        emissions = Dict()
+
+        if "transportation energy (J/km/tonne)" in keys(product_dict)
+            energy = product_dict["transportation energy (J/km/tonne)"]
+        end
+
+        if "transportation emissions (tonne/km/tonne)" in keys(product_dict)
+            emissions = product_dict["transportation emissions (tonne/km/tonne)"]
+        end
+
+        product = Product(product_name, cost, energy, emissions)
+        push!(products, product)
+        prod_name_to_product[product_name] = product
+
+        # Create collection centers
+        if "initial amounts" in keys(product_dict)
+            for (center_name, center_dict) in product_dict["initial amounts"]
+                if "location" in keys(center_dict)
+                    region = geodb_query(center_dict["location"])
+                    center_dict["latitude (deg)"] = region.centroid.lat
+                    center_dict["longitude (deg)"] = region.centroid.lon
+                end
+                center = CollectionCenter(
+                    length(collection_centers) + 1,
+                    center_name,
+                    center_dict["latitude (deg)"],
+                    center_dict["longitude (deg)"],
+                    product,
+                    center_dict["amount (tonne)"],
+                )
+                push!(collection_centers, center)
+            end
+        end
+    end
+
+    # Create plants
+    for (plant_name, plant_dict) in json["plants"]
+        input = prod_name_to_product[plant_dict["input"]]
+        output = Dict()
+
+        # Plant outputs
+        if "outputs (tonne/tonne)" in keys(plant_dict)
+            output = Dict(
+                prod_name_to_product[key] => value for
+                (key, value) in plant_dict["outputs (tonne/tonne)"] if value > 0
+            )
+        end
+
+        energy = zeros(T)
+        emissions = Dict()
+
+        if "energy (GJ/tonne)" in keys(plant_dict)
+            energy = plant_dict["energy (GJ/tonne)"]
+        end
+
+        if "emissions (tonne/tonne)" in keys(plant_dict)
+            emissions = plant_dict["emissions (tonne/tonne)"]
+        end
+
+        for (location_name, location_dict) in plant_dict["locations"]
+            sizes = PlantSize[]
+            disposal_limit = Dict(p => [0.0 for t = 1:T] for p in keys(output))
+            disposal_cost = Dict(p => [0.0 for t = 1:T] for p in keys(output))
+
+            # GeoDB
+            if "location" in keys(location_dict)
+                region = geodb_query(location_dict["location"])
+                location_dict["latitude (deg)"] = region.centroid.lat
+                location_dict["longitude (deg)"] = region.centroid.lon
+            end
+
+            # Disposal
+            if "disposal" in keys(location_dict)
+                for (product_name, disposal_dict) in location_dict["disposal"]
+                    limit = [1e8 for t = 1:T]
+                    if "limit (tonne)" in keys(disposal_dict)
+                        limit = disposal_dict["limit (tonne)"]
+                    end
+                    disposal_limit[prod_name_to_product[product_name]] = limit
+                    disposal_cost[prod_name_to_product[product_name]] =
+                        disposal_dict["cost (\$/tonne)"]
+                end
+            end
+
+            # Capacities
+            for (capacity_name, capacity_dict) in location_dict["capacities (tonne)"]
+                push!(
+                    sizes,
+                    PlantSize(
+                        Base.parse(Float64, capacity_name),
+                        capacity_dict["variable operating cost (\$/tonne)"],
+                        capacity_dict["fixed operating cost (\$)"],
+                        capacity_dict["opening cost (\$)"],
+                    ),
+                )
+            end
+            length(sizes) > 1 || push!(sizes, sizes[1])
+            sort!(sizes, by = x -> x.capacity)
+
+            # Storage
+            storage_limit = 0
+            storage_cost = zeros(T)
+            if "storage" in keys(location_dict)
+                storage_dict = location_dict["storage"]
+                storage_limit = storage_dict["limit (tonne)"]
+                storage_cost = storage_dict["cost (\$/tonne)"]
+            end
+
+            # Validation: Capacities
+            if length(sizes) != 2
+                throw("At most two capacities are supported")
+            end
+            if sizes[1].variable_operating_cost != sizes[2].variable_operating_cost
+                throw("Variable operating costs must be the same for all capacities")
+            end
+
+            plant = Plant(
+                length(plants) + 1,
+                plant_name,
+                location_name,
+                input,
+                output,
+                location_dict["latitude (deg)"],
+                location_dict["longitude (deg)"],
+                disposal_limit,
+                disposal_cost,
+                sizes,
+                energy,
+                emissions,
+                storage_limit,
+                storage_cost,
+            )
+
+            push!(plants, plant)
+        end
+    end
+
+    @info @sprintf("%12d collection centers", length(collection_centers))
+    @info @sprintf("%12d candidate plant locations", length(plants))
+
+    return Instance(T, products, collection_centers, plants, building_period)
+end
--- a/src/instance/structs.jl
+++ b/src/instance/structs.jl
@@ -0,0 +1,57 @@
+# RELOG: Reverse Logistics Optimization
+# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+# Released under the modified BSD license. See COPYING.md for more details.
+
+using DataStructures
+using JSON
+using JSONSchema
+using Printf
+using Statistics
+
+mutable struct Product
+    name::String
+    transportation_cost::Vector{Float64}
+    transportation_energy::Vector{Float64}
+    transportation_emissions::Dict{String,Vector{Float64}}
+end
+
+mutable struct CollectionCenter
+    index::Int64
+    name::String
+    latitude::Float64
+    longitude::Float64
+    product::Product
+    amount::Vector{Float64}
+end
+
+mutable struct PlantSize
+    capacity::Float64
+    variable_operating_cost::Vector{Float64}
+    fixed_operating_cost::Vector{Float64}
+    opening_cost::Vector{Float64}
+end
+
+mutable struct Plant
+    index::Int64
+    plant_name::String
+    location_name::String
+    input::Product
+    output::Dict{Product,Float64}
+    latitude::Float64
+    longitude::Float64
+    disposal_limit::Dict{Product,Vector{Float64}}
+    disposal_cost::Dict{Product,Vector{Float64}}
+    sizes::Vector{PlantSize}
+    energy::Vector{Float64}
+    emissions::Dict{String,Vector{Float64}}
+    storage_limit::Float64
+    storage_cost::Vector{Float64}
+end
+
+mutable struct Instance
+    time::Int64
+    products::Vector{Product}
+    collection_centers::Vector{CollectionCenter}
+    plants::Vector{Plant}
+    building_period::Vector{Int64}
+end
--- a/src/instance/validate.jl
+++ b/src/instance/validate.jl
@@ -0,0 +1,25 @@
+# RELOG: Reverse Logistics Optimization
+# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+# Released under the modified BSD license. See COPYING.md for more details.
+
+using DataStructures
+using JSON
+using JSONSchema
+using Printf
+using Statistics
+
+function validate(json, schema)
+    result = JSONSchema.validate(json, schema)
+    if result !== nothing
+        if result isa JSONSchema.SingleIssue
+            path = join(result.path, " → ")
+            if length(path) == 0
+                path = "root"
+            end
+            msg = "$(result.msg) in $(path)"
+        else
+            msg = convert(String, result)
+        end
+        throw(msg)
+    end
+end
--- a/src/model.jl
+++ b/src/model.jl
@@ -1,535 +0,0 @@
-# RELOG: Reverse Logistics Optimization
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-using JuMP, LinearAlgebra, Geodesy, Cbc, Clp, ProgressBars, Printf, DataStructures
-
-
-mutable struct ManufacturingModel
-    mip::JuMP.Model
-    vars::DotDict
-    eqs::DotDict
-    instance::Instance
-    graph::Graph
-end
-
-
-function build_model(instance::Instance, graph::Graph, optimizer)::ManufacturingModel
-    model = ManufacturingModel(Model(optimizer), DotDict(), DotDict(), instance, graph)
-    create_vars!(model)
-    create_objective_function!(model)
-    create_shipping_node_constraints!(model)
-    create_process_node_constraints!(model)
-    return model
-end
-
-
-function create_vars!(model::ManufacturingModel)
-    mip, vars, graph, T = model.mip, model.vars, model.graph, model.instance.time
-    
-    vars.flow = Dict((a, t) => @variable(mip, lower_bound=0)
-                    for a in graph.arcs, t in 1:T)
-   
-    vars.dispose = Dict((n, t) => @variable(mip,
-                                            lower_bound=0,
-                                            upper_bound=n.location.disposal_limit[n.product][t])
-                        for n in values(graph.plant_shipping_nodes), t in 1:T)
-    
-    vars.store = Dict((n, t) => @variable(mip,
-                                            lower_bound=0,
-                                            upper_bound=n.location.storage_limit)
-                        for n in values(graph.process_nodes), t in 1:T)
-    
-    vars.process = Dict((n, t) => @variable(mip,
-                                            lower_bound = 0)
-                        for n in values(graph.process_nodes), t in 1:T)
-    
-    vars.open_plant = Dict((n, t) => @variable(mip, binary=true)
-                           for n in values(graph.process_nodes), t in 1:T)
-
-    vars.is_open = Dict((n, t) => @variable(mip, binary=true)
-                        for n in values(graph.process_nodes), t in 1:T)
-
-    vars.capacity = Dict((n, t) => @variable(mip,
-                                             lower_bound = 0,
-                                             upper_bound = n.location.sizes[2].capacity)
-                         for n in values(graph.process_nodes), t in 1:T)
-    
-    vars.expansion = Dict((n, t) => @variable(mip,
-                                              lower_bound = 0,
-                                              upper_bound = n.location.sizes[2].capacity - 
-                                                            n.location.sizes[1].capacity)
-                         for n in values(graph.process_nodes), t in 1:T)
-end
-
-
-function slope_open(plant, t)
-    if plant.sizes[2].capacity <= plant.sizes[1].capacity
-        0.0
-    else
-        (plant.sizes[2].opening_cost[t] - plant.sizes[1].opening_cost[t]) /
-            (plant.sizes[2].capacity - plant.sizes[1].capacity)
-    end
-end
-
-function slope_fix_oper_cost(plant, t)
-    if plant.sizes[2].capacity <= plant.sizes[1].capacity
-        0.0
-    else
-        (plant.sizes[2].fixed_operating_cost[t] - plant.sizes[1].fixed_operating_cost[t]) /
-            (plant.sizes[2].capacity - plant.sizes[1].capacity)
-    end
-end
-
-function create_objective_function!(model::ManufacturingModel)
-    mip, vars, graph, T = model.mip, model.vars, model.graph, model.instance.time
-    obj = AffExpr(0.0)
-
-    # Process node costs
-    for n in values(graph.process_nodes), t in 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, vars.flow[a, t])
-        end
-        
-        # Opening costs
-        add_to_expression!(obj,
-                           n.location.sizes[1].opening_cost[t],
-                           vars.open_plant[n, t])
-        
-        # Fixed operating costs (base)
-        add_to_expression!(obj,
-                           n.location.sizes[1].fixed_operating_cost[t],
-                           vars.is_open[n, t])
-        
-        # Fixed operating costs (expansion)
-        add_to_expression!(obj,
-                           slope_fix_oper_cost(n.location, t),
-                           vars.expansion[n, t])
-        
-        # Processing costs
-        add_to_expression!(obj,
-                           n.location.sizes[1].variable_operating_cost[t],
-                           vars.process[n, t])
-        
-        # Storage costs
-        add_to_expression!(obj,
-                           n.location.storage_cost[t],
-                           vars.store[n, t])
-        
-        # Expansion costs
-        if t < T
-            add_to_expression!(obj,
-                               slope_open(n.location, t) - slope_open(n.location, t + 1),
-                               vars.expansion[n, t])
-        else
-            add_to_expression!(obj,
-                               slope_open(n.location, t),
-                               vars.expansion[n, t])
-        end
-    end
-
-    # Shipping node costs
-    for n in values(graph.plant_shipping_nodes), t in 1:T
-        
-        # Disposal costs
-        add_to_expression!(obj,
-                           n.location.disposal_cost[n.product][t],
-                           vars.dispose[n, t])
-    end
-
-    @objective(mip, Min, obj)
-end    
-
-
-function create_shipping_node_constraints!(model::ManufacturingModel)
-    mip, vars, graph, T = model.mip, model.vars, model.graph, model.instance.time
-    eqs = model.eqs
-    
-    eqs.balance = OrderedDict()
-    
-    for t in 1:T
-        # Collection centers
-        for n in graph.collection_shipping_nodes
-            eqs.balance[n, t] = @constraint(mip,
-                                            sum(vars.flow[a, t] for a in n.outgoing_arcs)
-                                              == n.location.amount[t])
-        end
-
-        # Plants
-        for n in graph.plant_shipping_nodes
-            @constraint(mip,
-                sum(vars.flow[a, t] for a in n.incoming_arcs) ==
-                sum(vars.flow[a, t] for a in n.outgoing_arcs) + vars.dispose[n, t])
-        end
-    end
-    
-end
-
-
-function create_process_node_constraints!(model::ManufacturingModel)
-    mip, vars, graph, T = model.mip, model.vars, model.graph, model.instance.time
-
-    for t in 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, vars.flow[a, t])
-        end
-        
-        # Output amount is implied by amount processed
-        for a in n.outgoing_arcs
-            @constraint(mip, vars.flow[a, t] == a.values["weight"] * vars.process[n, t])
-        end
-        
-        # If plant is closed, capacity is zero
-        @constraint(mip, vars.capacity[n, t] <= n.location.sizes[2].capacity * vars.is_open[n, t])
-
-        # If plant is open, capacity is greater than base
-        @constraint(mip, vars.capacity[n, t] >= n.location.sizes[1].capacity * vars.is_open[n, t])
-
-        # Capacity is linked to expansion
-        @constraint(mip, vars.capacity[n, t] <= n.location.sizes[1].capacity + vars.expansion[n, t])
-
-        # Can only process up to capacity
-        @constraint(mip, vars.process[n, t] <= vars.capacity[n, t])
-
-        if t > 1
-            # Plant capacity can only increase over time
-            @constraint(mip, vars.capacity[n, t] >= vars.capacity[n, t-1])
-            @constraint(mip, vars.expansion[n, t] >= vars.expansion[n, t-1])
-        end
-        
-        # Amount received equals amount processed plus stored
-        store_in = 0
-        if t > 1
-            store_in = vars.store[n, t-1]
-        end
-        if t == T
-            @constraint(mip, vars.store[n, t] == 0)
-        end
-        @constraint(mip,
-                    input_sum + store_in == vars.store[n, t] + vars.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(mip, vars.is_open[n, t] == vars.is_open[n, t-1] + vars.open_plant[n, t])
-        else
-            @constraint(mip, vars.is_open[n, t] == vars.open_plant[n, t])
-        end
-        
-        # Plant can only be opened during building period
-        if t ∉ model.instance.building_period
-            @constraint(mip, vars.open_plant[n, t] == 0)
-        end
-    end
-end
-
-default_milp_optimizer = optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
-default_lp_optimizer = optimizer_with_attributes(Clp.Optimizer, "LogLevel" => 0)
-
-function solve(instance::Instance;
-               optimizer=nothing,
-               output=nothing,
-               marginal_costs=true,
-              )
-    
-    milp_optimizer = lp_optimizer = optimizer
-    if optimizer == nothing
-        milp_optimizer = default_milp_optimizer
-        lp_optimizer = default_lp_optimizer
-    end
-    
-    @info "Building graph..."
-    graph = RELOG.build_graph(instance)
-    @info @sprintf("    %12d time periods", instance.time)
-    @info @sprintf("    %12d process nodes", length(graph.process_nodes))
-    @info @sprintf("    %12d shipping nodes (plant)", length(graph.plant_shipping_nodes))
-    @info @sprintf("    %12d shipping nodes (collection)", length(graph.collection_shipping_nodes))
-    @info @sprintf("    %12d arcs", length(graph.arcs))
-    
-    @info "Building optimization model..."
-    model = RELOG.build_model(instance, graph, milp_optimizer)
-    
-    @info "Optimizing MILP..."
-    JuMP.optimize!(model.mip)
-    
-    if !has_values(model.mip)
-        @warn "No solution available"
-        return OrderedDict()
-    end
-    
-    if marginal_costs
-        @info "Re-optimizing with integer variables fixed..."
-        all_vars = JuMP.all_variables(model.mip)
-        vals = OrderedDict(var => JuMP.value(var) for var in all_vars)
-        JuMP.set_optimizer(model.mip, lp_optimizer)
-        for var in all_vars
-            if JuMP.is_binary(var)
-                JuMP.unset_binary(var)
-                JuMP.fix(var, vals[var])
-            end
-        end
-        JuMP.optimize!(model.mip)
-    end
-    
-    @info "Extracting solution..."
-    solution = get_solution(model, marginal_costs=marginal_costs)
-    
-    if output != nothing
-        write(solution, output)
-    end
-    
-    return solution
-end
-
-function solve(filename::AbstractString;
-               heuristic=false,
-               kwargs...,
-              )
-    @info "Reading $filename..."
-    instance = RELOG.parsefile(filename)
-    if heuristic && instance.time > 1
-        @info "Solving single-period version..."
-        compressed = _compress(instance)
-        csol = solve(compressed;
-                     output=nothing,
-                     marginal_costs=false,
-                     kwargs...)
-        @info "Filtering candidate locations..."
-        selected_pairs = []
-        for (plant_name, plant_dict) in csol["Plants"]
-            for (location_name, location_dict) in plant_dict
-                push!(selected_pairs, (plant_name, location_name))
-            end
-        end
-        filtered_plants = []
-        for p in instance.plants
-            if (p.plant_name, p.location_name) in selected_pairs
-                push!(filtered_plants, p)
-            end
-        end
-        instance.plants = filtered_plants
-        @info "Solving original version..."
-    end
-    sol = solve(instance; kwargs...)
-    return sol
-end
-
-
-function get_solution(model::ManufacturingModel;
-                      marginal_costs=true,
-                     )
-    mip, vars, eqs, graph, instance = model.mip, model.vars, model.eqs, model.graph, model.instance
-    T = instance.time
-    
-    output = OrderedDict(
-        "Plants" => OrderedDict(),
-        "Products" => OrderedDict(),
-        "Costs" => OrderedDict(
-            "Fixed operating (\$)" => zeros(T),
-            "Variable operating (\$)" => zeros(T),
-            "Opening (\$)" => zeros(T),
-            "Transportation (\$)" => zeros(T),
-            "Disposal (\$)" => zeros(T),
-            "Expansion (\$)" => zeros(T),
-            "Storage (\$)" => zeros(T),
-            "Total (\$)" => zeros(T),
-        ),
-        "Energy" => OrderedDict(
-            "Plants (GJ)" => zeros(T),
-            "Transportation (GJ)" => zeros(T),
-        ),
-        "Emissions" => OrderedDict(
-            "Plants (tonne)" => OrderedDict(),
-            "Transportation (tonne)" => OrderedDict(),
-        ),
-    )
-    
-    plant_to_process_node = OrderedDict(n.location => n for n in graph.process_nodes)
-    plant_to_shipping_nodes = OrderedDict()
-    for p in instance.plants
-        plant_to_shipping_nodes[p] = []
-        for a in plant_to_process_node[p].outgoing_arcs
-            push!(plant_to_shipping_nodes[p], a.dest)
-        end
-    end
-    
-    # Products
-    if marginal_costs
-        for n in graph.collection_shipping_nodes
-            location_dict = OrderedDict{Any, Any}(
-                "Marginal cost (\$/tonne)" => [round(abs(JuMP.shadow_price(eqs.balance[n, t])), digits=2)
-                                               for t in 1:T]
-            )
-            if n.product.name ∉ keys(output["Products"])
-                output["Products"][n.product.name] = OrderedDict()
-            end
-            output["Products"][n.product.name][n.location.name] = location_dict
-        end
-    end
-    
-    # Plants
-    for plant in instance.plants
-        skip_plant = true
-        process_node = plant_to_process_node[plant]
-        plant_dict = OrderedDict{Any, Any}(
-            "Input" => OrderedDict(),
-            "Output" => OrderedDict(
-                "Send" => OrderedDict(),
-                "Dispose" => OrderedDict(),
-            ),
-            "Input product" => plant.input.name,
-            "Total input (tonne)" => [0.0 for t in 1:T],
-            "Total output" => OrderedDict(),
-            "Latitude (deg)" => plant.latitude,
-            "Longitude (deg)" => plant.longitude,
-            "Capacity (tonne)" => [JuMP.value(vars.capacity[process_node, t])
-                                   for t in 1:T],
-            "Opening cost (\$)" => [JuMP.value(vars.open_plant[process_node, t]) *
-                                    plant.sizes[1].opening_cost[t]
-                                    for t in 1:T],
-            "Fixed operating cost (\$)" => [JuMP.value(vars.is_open[process_node, t]) *
-                                            plant.sizes[1].fixed_operating_cost[t] +
-                                            JuMP.value(vars.expansion[process_node, t]) *
-                                            slope_fix_oper_cost(plant, t)
-                                            for t in 1:T],
-            "Expansion cost (\$)" => [(if t == 1
-                                          slope_open(plant, t) * JuMP.value(vars.expansion[process_node, t])
-                                       else
-                                          slope_open(plant, t) * (
-                                              JuMP.value(vars.expansion[process_node, t]) -
-                                              JuMP.value(vars.expansion[process_node, t - 1])
-                                          )
-                                       end)
-                                      for t in 1:T],
-            "Process (tonne)" => [JuMP.value(vars.process[process_node, t])
-                                  for t in 1:T],
-            "Variable operating cost (\$)" => [JuMP.value(vars.process[process_node, t]) *
-                                               plant.sizes[1].variable_operating_cost[t]
-                                               for t in 1:T],
-            "Storage (tonne)" => [JuMP.value(vars.store[process_node, t])
-                                for t in 1:T],
-            "Storage cost (\$)" => [JuMP.value(vars.store[process_node, t]) *
-                                    plant.storage_cost[t]
-                                    for t in 1:T],
-        )
-        output["Costs"]["Fixed operating (\$)"] += plant_dict["Fixed operating cost (\$)"]
-        output["Costs"]["Variable operating (\$)"] += plant_dict["Variable operating cost (\$)"]
-        output["Costs"]["Opening (\$)"] += plant_dict["Opening cost (\$)"]
-        output["Costs"]["Expansion (\$)"] += plant_dict["Expansion cost (\$)"]
-        output["Costs"]["Storage (\$)"] += plant_dict["Storage cost (\$)"]
-
-        # Inputs
-        for a in process_node.incoming_arcs
-            vals = [JuMP.value(vars.flow[a, t]) for t in 1:T]
-            if sum(vals) <= 1e-3
-                continue
-            end
-            skip_plant = false
-            dict = OrderedDict{Any, Any}(
-                "Amount (tonne)" => vals,
-                "Distance (km)" => a.values["distance"],
-                "Latitude (deg)" => a.source.location.latitude,
-                "Longitude (deg)" => a.source.location.longitude,
-                "Transportation cost (\$)" => a.source.product.transportation_cost .*
-                                              vals .*
-                                              a.values["distance"],
-                "Transportation energy (J)" => vals .*
-                                               a.values["distance"] .*
-                                               a.source.product.transportation_energy,
-                "Emissions (tonne)" => OrderedDict(),
-            )
-            emissions_dict = output["Emissions"]["Transportation (tonne)"]
-            for (em_name, em_values) in a.source.product.transportation_emissions
-                dict["Emissions (tonne)"][em_name] = em_values .*
-                                                     dict["Amount (tonne)"] .*
-                                                     a.values["distance"]
-                if em_name ∉ keys(emissions_dict)
-                    emissions_dict[em_name] = zeros(T)
-                end
-                emissions_dict[em_name] += dict["Emissions (tonne)"][em_name]
-            end
-            if a.source.location isa CollectionCenter
-                plant_name = "Origin"
-                location_name = a.source.location.name
-            else
-                plant_name = a.source.location.plant_name
-                location_name = a.source.location.location_name
-            end
-            
-            if plant_name ∉ keys(plant_dict["Input"])
-                plant_dict["Input"][plant_name] = OrderedDict()
-            end
-            plant_dict["Input"][plant_name][location_name] = dict
-            plant_dict["Total input (tonne)"] += vals
-            output["Costs"]["Transportation (\$)"] += dict["Transportation cost (\$)"]
-            output["Energy"]["Transportation (GJ)"] += dict["Transportation energy (J)"] / 1e9
-        end
-        
-        plant_dict["Energy (GJ)"] = plant_dict["Total input (tonne)"] .* plant.energy
-        output["Energy"]["Plants (GJ)"] += plant_dict["Energy (GJ)"]
-        
-        plant_dict["Emissions (tonne)"] = OrderedDict()
-        emissions_dict = output["Emissions"]["Plants (tonne)"]
-        for (em_name, em_values) in plant.emissions
-            plant_dict["Emissions (tonne)"][em_name] = em_values .* plant_dict["Total input (tonne)"]
-            if em_name ∉ keys(emissions_dict)
-                emissions_dict[em_name] = zeros(T)
-            end
-            emissions_dict[em_name] += plant_dict["Emissions (tonne)"][em_name]
-        end
-
-        # Outputs
-        for shipping_node in plant_to_shipping_nodes[plant]
-            product_name = shipping_node.product.name
-            plant_dict["Total output"][product_name] = zeros(T)
-            plant_dict["Output"]["Send"][product_name] = product_dict = OrderedDict()
-
-            disposal_amount = [JuMP.value(vars.dispose[shipping_node, t]) for t in 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.vars.dispose[shipping_node, t])
-                                                   for t in 1:T]
-                disposal_dict["Cost (\$)"] = [disposal_dict["Amount (tonne)"][t] *
-                                              plant.disposal_cost[shipping_node.product][t]
-                                              for t in 1:T]
-                plant_dict["Total output"][product_name] += disposal_amount
-                output["Costs"]["Disposal (\$)"] += disposal_dict["Cost (\$)"]
-            end
-
-            for a in shipping_node.outgoing_arcs
-                vals = [JuMP.value(vars.flow[a, t]) for t in 1:T]
-                if sum(vals) <= 1e-3
-                    continue
-                end
-                skip_plant = false
-                dict = OrderedDict(
-                    "Amount (tonne)" => vals,
-                    "Distance (km)" => a.values["distance"],
-                    "Latitude (deg)" => a.dest.location.latitude,
-                    "Longitude (deg)" => a.dest.location.longitude,
-                )
-                if a.dest.location.plant_name ∉ keys(product_dict)
-                    product_dict[a.dest.location.plant_name] = OrderedDict()
-                end
-                product_dict[a.dest.location.plant_name][a.dest.location.location_name] = dict
-                plant_dict["Total output"][product_name] += vals
-            end
-        end
-            
-        if !skip_plant
-            if plant.plant_name ∉ keys(output["Plants"])
-                output["Plants"][plant.plant_name] = OrderedDict()
-            end
-            output["Plants"][plant.plant_name][plant.location_name] = plant_dict
-        end
-    end
-
-    output["Costs"]["Total (\$)"] = sum(values(output["Costs"]))
-    return output
-end
--- a/src/model/build.jl
+++ b/src/model/build.jl
@@ -0,0 +1,249 @@
+# RELOG: Reverse Logistics Optimization
+# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+# Released under the modified BSD license. See COPYING.md for more details.
+
+using JuMP, LinearAlgebra, Geodesy, Cbc, Clp, ProgressBars, Printf, DataStructures
+
+function 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
+end
+
+
+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[: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[:store] = Dict(
+        (n, t) =>
+            @variable(model, lower_bound = 0, upper_bound = n.location.storage_limit)
+        for n in values(graph.process_nodes), t = 1:T
+    )
+    model[:process] = Dict(
+        (n, t) => @variable(model, lower_bound = 0) for
+        n in values(graph.process_nodes), t = 1:T
+    )
+    model[:open_plant] = Dict(
+        (n, t) => @variable(model, binary = true) for n in values(graph.process_nodes),
+        t = 1:T
+    )
+    model[:is_open] = Dict(
+        (n, t) => @variable(model, binary = true) for n in values(graph.process_nodes),
+        t = 1:T
+    )
+    model[:capacity] = Dict(
+        (n, t) => @variable(
+            model,
+            lower_bound = 0,
+            upper_bound = n.location.sizes[2].capacity
+        ) for n in values(graph.process_nodes), t = 1:T
+    )
+    model[:expansion] = Dict(
+        (n, t) => @variable(
+            model,
+            lower_bound = 0,
+            upper_bound = n.location.sizes[2].capacity - n.location.sizes[1].capacity
+        ) for n in values(graph.process_nodes), t = 1:T
+    )
+end
+
+
+function slope_open(plant, t)
+    if plant.sizes[2].capacity <= plant.sizes[1].capacity
+        0.0
+    else
+        (plant.sizes[2].opening_cost[t] - plant.sizes[1].opening_cost[t]) /
+        (plant.sizes[2].capacity - plant.sizes[1].capacity)
+    end
+end
+
+function slope_fix_oper_cost(plant, t)
+    if plant.sizes[2].capacity <= plant.sizes[1].capacity
+        0.0
+    else
+        (plant.sizes[2].fixed_operating_cost[t] - plant.sizes[1].fixed_operating_cost[t]) /
+        (plant.sizes[2].capacity - plant.sizes[1].capacity)
+    end
+end
+
+function create_objective_function!(model::JuMP.Model)
+    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
+
+    # 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[: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]
+            )
+        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[: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
--- a/src/model/getsol.jl
+++ b/src/model/getsol.jl
@@ -0,0 +1,227 @@
+# RELOG: Reverse Logistics Optimization
+# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+# Released under the modified BSD license. See COPYING.md for more details.
+
+using JuMP, LinearAlgebra, Geodesy, Cbc, Clp, ProgressBars, Printf, DataStructures
+
+function get_solution(model::JuMP.Model; marginal_costs = true)
+    graph, instance = model[:graph], model[:instance]
+    T = instance.time
+
+    output = OrderedDict(
+        "Plants" => OrderedDict(),
+        "Products" => OrderedDict(),
+        "Costs" => OrderedDict(
+            "Fixed operating (\$)" => zeros(T),
+            "Variable operating (\$)" => zeros(T),
+            "Opening (\$)" => zeros(T),
+            "Transportation (\$)" => zeros(T),
+            "Disposal (\$)" => zeros(T),
+            "Expansion (\$)" => zeros(T),
+            "Storage (\$)" => zeros(T),
+            "Total (\$)" => zeros(T),
+        ),
+        "Energy" =>
+            OrderedDict("Plants (GJ)" => zeros(T), "Transportation (GJ)" => zeros(T)),
+        "Emissions" => OrderedDict(
+            "Plants (tonne)" => OrderedDict(),
+            "Transportation (tonne)" => OrderedDict(),
+        ),
+    )
+
+    plant_to_process_node = OrderedDict(n.location => n for n in graph.process_nodes)
+    plant_to_shipping_nodes = OrderedDict()
+    for p in instance.plants
+        plant_to_shipping_nodes[p] = []
+        for a in plant_to_process_node[p].outgoing_arcs
+            push!(plant_to_shipping_nodes[p], a.dest)
+        end
+    end
+
+    # Products
+    if marginal_costs
+        for n in graph.collection_shipping_nodes
+            location_dict = OrderedDict{Any,Any}(
+                "Marginal cost (\$/tonne)" => [
+                    round(abs(JuMP.shadow_price(model[:eq_balance][n, t])), digits = 2) for t = 1:T
+                ],
+                "Latitude (deg)" => n.location.latitude,
+                "Longitude (deg)" => n.location.longitude,
+                "Amount (tonne)" => n.location.amount,
+            )
+            if n.product.name ∉ keys(output["Products"])
+                output["Products"][n.product.name] = OrderedDict()
+            end
+            output["Products"][n.product.name][n.location.name] = location_dict
+        end
+    end
+
+    # Plants
+    for plant in instance.plants
+        skip_plant = true
+        process_node = plant_to_process_node[plant]
+        plant_dict = OrderedDict{Any,Any}(
+            "Input" => OrderedDict(),
+            "Output" =>
+                OrderedDict("Send" => OrderedDict(), "Dispose" => OrderedDict()),
+            "Input product" => plant.input.name,
+            "Total input (tonne)" => [0.0 for t = 1:T],
+            "Total output" => OrderedDict(),
+            "Latitude (deg)" => plant.latitude,
+            "Longitude (deg)" => plant.longitude,
+            "Capacity (tonne)" =>
+                [JuMP.value(model[:capacity][process_node, t]) for t = 1:T],
+            "Opening cost (\$)" => [
+                JuMP.value(model[:open_plant][process_node, t]) *
+                plant.sizes[1].opening_cost[t] for t = 1:T
+            ],
+            "Fixed operating cost (\$)" => [
+                JuMP.value(model[:is_open][process_node, t]) *
+                plant.sizes[1].fixed_operating_cost[t] +
+                JuMP.value(model[:expansion][process_node, t]) *
+                slope_fix_oper_cost(plant, t) for t = 1:T
+            ],
+            "Expansion cost (\$)" => [
+                (
+                    if t == 1
+                        slope_open(plant, t) * JuMP.value(model[:expansion][process_node, t])
+                    else
+                        slope_open(plant, t) * (
+                            JuMP.value(model[:expansion][process_node, t]) -
+                            JuMP.value(model[:expansion][process_node, t-1])
+                        )
+                    end
+                ) for t = 1:T
+            ],
+            "Process (tonne)" =>
+                [JuMP.value(model[:process][process_node, t]) for t = 1:T],
+            "Variable operating cost (\$)" => [
+                JuMP.value(model[:process][process_node, t]) *
+                plant.sizes[1].variable_operating_cost[t] for t = 1:T
+            ],
+            "Storage (tonne)" =>
+                [JuMP.value(model[:store][process_node, t]) for t = 1:T],
+            "Storage cost (\$)" => [
+                JuMP.value(model[:store][process_node, t]) * plant.storage_cost[t]
+                for t = 1:T
+            ],
+        )
+        output["Costs"]["Fixed operating (\$)"] += plant_dict["Fixed operating cost (\$)"]
+        output["Costs"]["Variable operating (\$)"] +=
+            plant_dict["Variable operating cost (\$)"]
+        output["Costs"]["Opening (\$)"] += plant_dict["Opening cost (\$)"]
+        output["Costs"]["Expansion (\$)"] += plant_dict["Expansion cost (\$)"]
+        output["Costs"]["Storage (\$)"] += plant_dict["Storage cost (\$)"]
+
+        # Inputs
+        for a in process_node.incoming_arcs
+            vals = [JuMP.value(model[:flow][a, t]) for t = 1:T]
+            if sum(vals) <= 1e-3
+                continue
+            end
+            skip_plant = false
+            dict = OrderedDict{Any,Any}(
+                "Amount (tonne)" => vals,
+                "Distance (km)" => a.values["distance"],
+                "Latitude (deg)" => a.source.location.latitude,
+                "Longitude (deg)" => a.source.location.longitude,
+                "Transportation cost (\$)" =>
+                    a.source.product.transportation_cost .* vals .* a.values["distance"],
+                "Transportation energy (J)" =>
+                    vals .* a.values["distance"] .* a.source.product.transportation_energy,
+                "Emissions (tonne)" => OrderedDict(),
+            )
+            emissions_dict = output["Emissions"]["Transportation (tonne)"]
+            for (em_name, em_values) in a.source.product.transportation_emissions
+                dict["Emissions (tonne)"][em_name] =
+                    em_values .* dict["Amount (tonne)"] .* a.values["distance"]
+                if em_name ∉ keys(emissions_dict)
+                    emissions_dict[em_name] = zeros(T)
+                end
+                emissions_dict[em_name] += dict["Emissions (tonne)"][em_name]
+            end
+            if a.source.location isa CollectionCenter
+                plant_name = "Origin"
+                location_name = a.source.location.name
+            else
+                plant_name = a.source.location.plant_name
+                location_name = a.source.location.location_name
+            end
+
+            if plant_name ∉ keys(plant_dict["Input"])
+                plant_dict["Input"][plant_name] = OrderedDict()
+            end
+            plant_dict["Input"][plant_name][location_name] = dict
+            plant_dict["Total input (tonne)"] += vals
+            output["Costs"]["Transportation (\$)"] += dict["Transportation cost (\$)"]
+            output["Energy"]["Transportation (GJ)"] +=
+                dict["Transportation energy (J)"] / 1e9
+        end
+
+        plant_dict["Energy (GJ)"] = plant_dict["Total input (tonne)"] .* plant.energy
+        output["Energy"]["Plants (GJ)"] += plant_dict["Energy (GJ)"]
+
+        plant_dict["Emissions (tonne)"] = OrderedDict()
+        emissions_dict = output["Emissions"]["Plants (tonne)"]
+        for (em_name, em_values) in plant.emissions
+            plant_dict["Emissions (tonne)"][em_name] =
+                em_values .* plant_dict["Total input (tonne)"]
+            if em_name ∉ keys(emissions_dict)
+                emissions_dict[em_name] = zeros(T)
+            end
+            emissions_dict[em_name] += plant_dict["Emissions (tonne)"][em_name]
+        end
+
+        # Outputs
+        for shipping_node in plant_to_shipping_nodes[plant]
+            product_name = shipping_node.product.name
+            plant_dict["Total output"][product_name] = zeros(T)
+            plant_dict["Output"]["Send"][product_name] = product_dict = OrderedDict()
+
+            disposal_amount = [JuMP.value(model[:dispose][shipping_node, t]) for t = 1:T]
+            if sum(disposal_amount) > 1e-5
+                skip_plant = false
+                plant_dict["Output"]["Dispose"][product_name] =
+                    disposal_dict = OrderedDict()
+                disposal_dict["Amount (tonne)"] =
+                    [JuMP.value(model[:dispose][shipping_node, t]) for t = 1:T]
+                disposal_dict["Cost (\$)"] = [
+                    disposal_dict["Amount (tonne)"][t] *
+                    plant.disposal_cost[shipping_node.product][t] for t = 1:T
+                ]
+                plant_dict["Total output"][product_name] += disposal_amount
+                output["Costs"]["Disposal (\$)"] += disposal_dict["Cost (\$)"]
+            end
+
+            for a in shipping_node.outgoing_arcs
+                vals = [JuMP.value(model[:flow][a, t]) for t = 1:T]
+                if sum(vals) <= 1e-3
+                    continue
+                end
+                skip_plant = false
+                dict = OrderedDict(
+                    "Amount (tonne)" => vals,
+                    "Distance (km)" => a.values["distance"],
+                    "Latitude (deg)" => a.dest.location.latitude,
+                    "Longitude (deg)" => a.dest.location.longitude,
+                )
+                if a.dest.location.plant_name ∉ keys(product_dict)
+                    product_dict[a.dest.location.plant_name] = OrderedDict()
+                end
+                product_dict[a.dest.location.plant_name][a.dest.location.location_name] =
+                    dict
+                plant_dict["Total output"][product_name] += vals
+            end
+        end
+
+        if !skip_plant
+            if plant.plant_name ∉ keys(output["Plants"])
+                output["Plants"][plant.plant_name] = OrderedDict()
+            end
+            output["Plants"][plant.plant_name][plant.location_name] = plant_dict
+        end
+    end
+
+    output["Costs"]["Total (\$)"] = sum(values(output["Costs"]))
+    return output
+end
--- a/src/model/resolve.jl
+++ b/src/model/resolve.jl
@@ -0,0 +1,97 @@
+# 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
--- a/src/model/solve.jl
+++ b/src/model/solve.jl
@@ -0,0 +1,109 @@
+# RELOG: Reverse Logistics Optimization
+# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+# Released under the modified BSD license. See COPYING.md for more details.
+
+using JuMP, LinearAlgebra, Geodesy, Cbc, Clp, ProgressBars, Printf, DataStructures
+
+function _get_default_milp_optimizer()
+    return optimizer_with_attributes(Cbc.Optimizer, "logLevel" => 0)
+end
+
+function _get_default_lp_optimizer()
+    return optimizer_with_attributes(Clp.Optimizer, "LogLevel" => 0)
+end
+
+
+function _print_graph_stats(instance::Instance, graph::Graph)::Nothing
+    @info @sprintf("    %12d time periods", instance.time)
+    @info @sprintf("    %12d process nodes", length(graph.process_nodes))
+    @info @sprintf("    %12d shipping nodes (plant)", length(graph.plant_shipping_nodes))
+    @info @sprintf(
+        "    %12d shipping nodes (collection)",
+        length(graph.collection_shipping_nodes)
+    )
+    @info @sprintf("    %12d arcs", length(graph.arcs))
+    return
+end
+
+function solve(
+    instance::Instance;
+    optimizer = nothing,
+    output = nothing,
+    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)
+
+    if !has_values(model)
+        error("No solution available")
+    end
+
+    if marginal_costs
+        @info "Re-optimizing with integer variables fixed..."
+        all_vars = JuMP.all_variables(model)
+        vals = OrderedDict(var => JuMP.value(var) for var in all_vars)
+        JuMP.set_optimizer(model, lp_optimizer)
+        for var in all_vars
+            if JuMP.is_binary(var)
+                JuMP.unset_binary(var)
+                JuMP.fix(var, vals[var])
+            end
+        end
+        JuMP.optimize!(model)
+    end
+
+    @info "Extracting solution..."
+    solution = get_solution(model, marginal_costs = marginal_costs)
+
+    if output != nothing
+        write(solution, output)
+    end
+
+    if return_model
+        return solution, model
+    else
+        return solution
+    end
+end
+
+function solve(filename::AbstractString; heuristic = false, kwargs...)
+    @info "Reading $filename..."
+    instance = RELOG.parsefile(filename)
+    if heuristic && instance.time > 1
+        @info "Solving single-period version..."
+        compressed = _compress(instance)
+        csol = solve(compressed; output = nothing, marginal_costs = false, kwargs...)
+        @info "Filtering candidate locations..."
+        selected_pairs = []
+        for (plant_name, plant_dict) in csol["Plants"]
+            for (location_name, location_dict) in plant_dict
+                push!(selected_pairs, (plant_name, location_name))
+            end
+        end
+        filtered_plants = []
+        for p in instance.plants
+            if (p.plant_name, p.location_name) in selected_pairs
+                push!(filtered_plants, p)
+            end
+        end
+        instance.plants = filtered_plants
+        @info "Solving original version..."
+    end
+    sol = solve(instance; kwargs...)
+    return sol
+end
--- a/src/reports.jl
+++ b/src/reports.jl
@@ -1,278 +0,0 @@
-# RELOG: Reverse Logistics Optimization
-# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
-# Released under the modified BSD license. See COPYING.md for more details.
-
-using DataFrames
-using CSV
-
-function plants_report(solution)::DataFrame
-    df = DataFrame()
-    df."plant type" = String[]
-    df."location name" = String[]
-    df."year" = Int[]
-    df."latitude (deg)" = Float64[]
-    df."longitude (deg)" = Float64[]
-    df."capacity (tonne)" = Float64[]
-    df."amount processed (tonne)" = Float64[]
-    df."amount received (tonne)" = Float64[]
-    df."amount in storage (tonne)" = Float64[]
-    df."utilization factor (%)" = Float64[]
-    df."energy (GJ)" = Float64[]
-    df."opening cost (\$)" = Float64[]
-    df."expansion cost (\$)" = Float64[]
-    df."fixed operating cost (\$)" = Float64[]
-    df."variable operating cost (\$)" = Float64[]
-    df."storage cost (\$)" = Float64[]
-    df."total cost (\$)" = Float64[]
-    T = length(solution["Energy"]["Plants (GJ)"])
-    for (plant_name, plant_dict) in solution["Plants"]
-        for (location_name, location_dict) in plant_dict
-            for year in 1:T
-                capacity = round(location_dict["Capacity (tonne)"][year], digits=2)
-                received = round(location_dict["Total input (tonne)"][year], digits=2)
-                processed = round(location_dict["Process (tonne)"][year], digits=2)
-                in_storage = round(location_dict["Storage (tonne)"][year], digits=2)
-                utilization_factor = round(processed / capacity * 100.0, digits=2)
-                energy = round(location_dict["Energy (GJ)"][year], digits=2)
-                latitude = round(location_dict["Latitude (deg)"], digits=6)
-                longitude = round(location_dict["Longitude (deg)"], digits=6)
-                opening_cost = round(location_dict["Opening cost (\$)"][year], digits=2)
-                expansion_cost = round(location_dict["Expansion cost (\$)"][year], digits=2)
-                fixed_cost = round(location_dict["Fixed operating cost (\$)"][year], digits=2)
-                var_cost = round(location_dict["Variable operating cost (\$)"][year], digits=2)
-                storage_cost = round(location_dict["Storage cost (\$)"][year], digits=2)
-                total_cost = round(opening_cost + expansion_cost + fixed_cost +
-                                   var_cost + storage_cost, digits=2)
-                push!(df, [
-                    plant_name,
-                    location_name,
-                    year,
-                    latitude,
-                    longitude,
-                    capacity,
-                    processed,
-                    received,
-                    in_storage,
-                    utilization_factor,
-                    energy,
-                    opening_cost,
-                    expansion_cost,
-                    fixed_cost,
-                    var_cost,
-                    storage_cost,
-                    total_cost,
-                ])
-            end
-        end
-    end
-    return df
-end
-
-function plant_outputs_report(solution)::DataFrame
-    df = DataFrame()
-    df."plant type" = String[]
-    df."location name" = String[]
-    df."year" = Int[]
-    df."product name" = String[]
-    df."amount produced (tonne)" = Float64[]
-    df."amount sent (tonne)" = Float64[]
-    df."amount disposed (tonne)" = Float64[]
-    df."disposal cost (\$)" = Float64[]
-    T = length(solution["Energy"]["Plants (GJ)"])
-    for (plant_name, plant_dict) in solution["Plants"]
-        for (location_name, location_dict) in plant_dict
-            for (product_name, amount_produced) in location_dict["Total output"]
-                send_dict = location_dict["Output"]["Send"]
-                disposal_dict = location_dict["Output"]["Dispose"]
-                
-                sent = zeros(T)
-                if product_name in keys(send_dict)
-                    for (dst_plant_name, dst_plant_dict) in send_dict[product_name]
-                        for (dst_location_name, dst_location_dict) in dst_plant_dict
-                            sent += dst_location_dict["Amount (tonne)"]
-                        end
-                    end
-                end
-                sent = round.(sent, digits=2)
-                
-                disposal_amount = zeros(T)
-                disposal_cost = zeros(T)
-                if product_name in keys(disposal_dict)
-                    disposal_amount += disposal_dict[product_name]["Amount (tonne)"]
-                    disposal_cost += disposal_dict[product_name]["Cost (\$)"]
-                end
-                disposal_amount = round.(disposal_amount, digits=2)
-                disposal_cost = round.(disposal_cost, digits=2)
-                
-                for year in 1:T
-                    push!(df, [
-                        plant_name,
-                        location_name,
-                        year,
-                        product_name,
-                        round(amount_produced[year], digits=2),
-                        sent[year],
-                        disposal_amount[year],
-                        disposal_cost[year],
-                    ])
-                end
-            end
-        end
-    end
-    return df
-end
-
-
-function plant_emissions_report(solution)::DataFrame
-    df = DataFrame()
-    df."plant type" = String[]
-    df."location name" = String[]
-    df."year" = Int[]
-    df."emission type" = String[]
-    df."emission amount (tonne)" = Float64[]
-    T = length(solution["Energy"]["Plants (GJ)"])
-    for (plant_name, plant_dict) in solution["Plants"]
-        for (location_name, location_dict) in plant_dict
-            for (emission_name, emission_amount) in location_dict["Emissions (tonne)"]
-                for year in 1:T
-                    push!(df, [
-                        plant_name,
-                        location_name,
-                        year,
-                        emission_name,
-                        round(emission_amount[year], digits=2),
-                    ])
-                end
-            end
-        end
-    end
-    return df
-end
-
-
-function transportation_report(solution)::DataFrame
-    df = DataFrame()
-    df."source type" = String[]
-    df."source location name" = String[]
-    df."source latitude (deg)" = Float64[]
-    df."source longitude (deg)" = Float64[]
-    df."destination type" = String[]
-    df."destination location name" = String[]
-    df."destination latitude (deg)" = Float64[]
-    df."destination longitude (deg)" = Float64[]
-    df."product" = String[]
-    df."year" = Int[]
-    df."distance (km)" = Float64[]
-    df."amount (tonne)" = Float64[]
-    df."amount-distance (tonne-km)" = Float64[]
-    df."transportation cost (\$)" = Float64[]    
-    df."transportation energy (GJ)" = Float64[]    
-    
-    T = length(solution["Energy"]["Plants (GJ)"])
-    for (dst_plant_name, dst_plant_dict) in solution["Plants"]
-        for (dst_location_name, dst_location_dict) in dst_plant_dict
-            for (src_plant_name, src_plant_dict) in dst_location_dict["Input"]
-                for (src_location_name, src_location_dict) in src_plant_dict
-                    for year in 1:T
-                        push!(df, [
-                            src_plant_name,
-                            src_location_name,
-                            round(src_location_dict["Latitude (deg)"], digits=6),
-                            round(src_location_dict["Longitude (deg)"], digits=6),
-                            dst_plant_name,
-                            dst_location_name,
-                            round(dst_location_dict["Latitude (deg)"], digits=6),
-                            round(dst_location_dict["Longitude (deg)"], digits=6),
-                            dst_location_dict["Input product"],
-                            year,
-                            round(src_location_dict["Distance (km)"], digits=2),
-                            round(src_location_dict["Amount (tonne)"][year], digits=2),
-                            round(src_location_dict["Amount (tonne)"][year] *
-                                      src_location_dict["Distance (km)"],
-                                  digits=2),
-                            round(src_location_dict["Transportation cost (\$)"][year], digits=2),
-                            round(src_location_dict["Transportation energy (J)"][year] / 1e9, digits=2),
-                        ])
-                    end
-                end
-            end
-        end
-    end
-    return df
-end
-
-
-function transportation_emissions_report(solution)::DataFrame
-    df = DataFrame()
-    df."source type" = String[]
-    df."source location name" = String[]
-    df."source latitude (deg)" = Float64[]
-    df."source longitude (deg)" = Float64[]
-    df."destination type" = String[]
-    df."destination location name" = String[]
-    df."destination latitude (deg)" = Float64[]
-    df."destination longitude (deg)" = Float64[]
-    df."product" = String[]
-    df."year" = Int[]
-    df."distance (km)" = Float64[]
-    df."shipped amount (tonne)" = Float64[]
-    df."shipped amount-distance (tonne-km)" = Float64[]
-    df."emission type" = String[]    
-    df."emission amount (tonne)" = Float64[]    
-    
-    T = length(solution["Energy"]["Plants (GJ)"])
-    for (dst_plant_name, dst_plant_dict) in solution["Plants"]
-        for (dst_location_name, dst_location_dict) in dst_plant_dict
-            for (src_plant_name, src_plant_dict) in dst_location_dict["Input"]
-                for (src_location_name, src_location_dict) in src_plant_dict
-                    for (emission_name, emission_amount) in src_location_dict["Emissions (tonne)"]
-                        for year in 1:T
-                            push!(df, [
-                                src_plant_name,
-                                src_location_name,
-                                round(src_location_dict["Latitude (deg)"], digits=6),
-                                round(src_location_dict["Longitude (deg)"], digits=6),
-                                dst_plant_name,
-                                dst_location_name,
-                                round(dst_location_dict["Latitude (deg)"], digits=6),
-                                round(dst_location_dict["Longitude (deg)"], digits=6),
-                                dst_location_dict["Input product"],
-                                year,
-                                round(src_location_dict["Distance (km)"], digits=2),
-                                round(src_location_dict["Amount (tonne)"][year], digits=2),
-                                round(src_location_dict["Amount (tonne)"][year] *
-                                          src_location_dict["Distance (km)"],
-                                      digits=2),
-                                emission_name,
-                                round(emission_amount[year], digits=2),
-                            ])
-                        end
-                    end
-                end
-            end
-        end
-    end
-    return df
-end
-
-function write(solution::AbstractDict, filename::AbstractString)
-    @info "Writing solution: $filename"
-    open(filename, "w") do file
-        JSON.print(file, solution, 2)
-    end
-end
-
-write_plants_report(solution, filename) =
-    CSV.write(filename, plants_report(solution))
-
-write_plant_outputs_report(solution, filename) =
-    CSV.write(filename, plant_outputs_report(solution))
-
-write_plant_emissions_report(solution, filename) =
-    CSV.write(filename, plant_emissions_report(solution))
-
-write_transportation_report(solution, filename) =
-    CSV.write(filename, transportation_report(solution))
-
-write_transportation_emissions_report(solution, filename) =
-    CSV.write(filename, transportation_emissions_report(solution))
--- a/src/reports/plant_emissions.jl
+++ b/src/reports/plant_emissions.jl
@@ -0,0 +1,38 @@
+# RELOG: Reverse Logistics Optimization
+# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+# Released under the modified BSD license. See COPYING.md for more details.
+
+using DataFrames
+using CSV
+
+function plant_emissions_report(solution)::DataFrame
+    df = DataFrame()
+    df."plant type" = String[]
+    df."location name" = String[]
+    df."year" = Int[]
+    df."emission type" = String[]
+    df."emission amount (tonne)" = Float64[]
+    T = length(solution["Energy"]["Plants (GJ)"])
+    for (plant_name, plant_dict) in solution["Plants"]
+        for (location_name, location_dict) in plant_dict
+            for (emission_name, emission_amount) in location_dict["Emissions (tonne)"]
+                for year = 1:T
+                    push!(
+                        df,
+                        [
+                            plant_name,
+                            location_name,
+                            year,
+                            emission_name,
+                            round(emission_amount[year], digits = 2),
+                        ],
+                    )
+                end
+            end
+        end
+    end
+    return df
+end
+
+write_plant_emissions_report(solution, filename) =
+    CSV.write(filename, plant_emissions_report(solution))
--- a/src/reports/plant_outputs.jl
+++ b/src/reports/plant_outputs.jl
@@ -0,0 +1,66 @@
+# RELOG: Reverse Logistics Optimization
+# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+# Released under the modified BSD license. See COPYING.md for more details.
+
+using DataFrames
+using CSV
+
+function plant_outputs_report(solution)::DataFrame
+    df = DataFrame()
+    df."plant type" = String[]
+    df."location name" = String[]
+    df."year" = Int[]
+    df."product name" = String[]
+    df."amount produced (tonne)" = Float64[]
+    df."amount sent (tonne)" = Float64[]
+    df."amount disposed (tonne)" = Float64[]
+    df."disposal cost (\$)" = Float64[]
+    T = length(solution["Energy"]["Plants (GJ)"])
+    for (plant_name, plant_dict) in solution["Plants"]
+        for (location_name, location_dict) in plant_dict
+            for (product_name, amount_produced) in location_dict["Total output"]
+                send_dict = location_dict["Output"]["Send"]
+                disposal_dict = location_dict["Output"]["Dispose"]
+
+                sent = zeros(T)
+                if product_name in keys(send_dict)
+                    for (dst_plant_name, dst_plant_dict) in send_dict[product_name]
+                        for (dst_location_name, dst_location_dict) in dst_plant_dict
+                            sent += dst_location_dict["Amount (tonne)"]
+                        end
+                    end
+                end
+                sent = round.(sent, digits = 2)
+
+                disposal_amount = zeros(T)
+                disposal_cost = zeros(T)
+                if product_name in keys(disposal_dict)
+                    disposal_amount += disposal_dict[product_name]["Amount (tonne)"]
+                    disposal_cost += disposal_dict[product_name]["Cost (\$)"]
+                end
+                disposal_amount = round.(disposal_amount, digits = 2)
+                disposal_cost = round.(disposal_cost, digits = 2)
+
+                for year = 1:T
+                    push!(
+                        df,
+                        [
+                            plant_name,
+                            location_name,
+                            year,
+                            product_name,
+                            round(amount_produced[year], digits = 2),
+                            sent[year],
+                            disposal_amount[year],
+                            disposal_cost[year],
+                        ],
+                    )
+                end
+            end
+        end
+    end
+    return df
+end
+
+write_plant_outputs_report(solution, filename) =
+    CSV.write(filename, plant_outputs_report(solution))
--- a/src/reports/plants.jl
+++ b/src/reports/plants.jl
@@ -0,0 +1,79 @@
+# RELOG: Reverse Logistics Optimization
+# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+# Released under the modified BSD license. See COPYING.md for more details.
+
+using DataFrames
+using CSV
+
+function plants_report(solution)::DataFrame
+    df = DataFrame()
+    df."plant type" = String[]
+    df."location name" = String[]
+    df."year" = Int[]
+    df."latitude (deg)" = Float64[]
+    df."longitude (deg)" = Float64[]
+    df."capacity (tonne)" = Float64[]
+    df."amount processed (tonne)" = Float64[]
+    df."amount received (tonne)" = Float64[]
+    df."amount in storage (tonne)" = Float64[]
+    df."utilization factor (%)" = Float64[]
+    df."energy (GJ)" = Float64[]
+    df."opening cost (\$)" = Float64[]
+    df."expansion cost (\$)" = Float64[]
+    df."fixed operating cost (\$)" = Float64[]
+    df."variable operating cost (\$)" = Float64[]
+    df."storage cost (\$)" = Float64[]
+    df."total cost (\$)" = Float64[]
+    T = length(solution["Energy"]["Plants (GJ)"])
+    for (plant_name, plant_dict) in solution["Plants"]
+        for (location_name, location_dict) in plant_dict
+            for year = 1:T
+                capacity = round(location_dict["Capacity (tonne)"][year], digits = 2)
+                received = round(location_dict["Total input (tonne)"][year], digits = 2)
+                processed = round(location_dict["Process (tonne)"][year], digits = 2)
+                in_storage = round(location_dict["Storage (tonne)"][year], digits = 2)
+                utilization_factor = round(processed / capacity * 100.0, digits = 2)
+                energy = round(location_dict["Energy (GJ)"][year], digits = 2)
+                latitude = round(location_dict["Latitude (deg)"], digits = 6)
+                longitude = round(location_dict["Longitude (deg)"], digits = 6)
+                opening_cost = round(location_dict["Opening cost (\$)"][year], digits = 2)
+                expansion_cost =
+                    round(location_dict["Expansion cost (\$)"][year], digits = 2)
+                fixed_cost =
+                    round(location_dict["Fixed operating cost (\$)"][year], digits = 2)
+                var_cost =
+                    round(location_dict["Variable operating cost (\$)"][year], digits = 2)
+                storage_cost = round(location_dict["Storage cost (\$)"][year], digits = 2)
+                total_cost = round(
+                    opening_cost + expansion_cost + fixed_cost + var_cost + storage_cost,
+                    digits = 2,
+                )
+                push!(
+                    df,
+                    [
+                        plant_name,
+                        location_name,
+                        year,
+                        latitude,
+                        longitude,
+                        capacity,
+                        processed,
+                        received,
+                        in_storage,
+                        utilization_factor,
+                        energy,
+                        opening_cost,
+                        expansion_cost,
+                        fixed_cost,
+                        var_cost,
+                        storage_cost,
+                        total_cost,
+                    ],
+                )
+            end
+        end
+    end
+    return df
+end
+
+write_plants_report(solution, filename) = CSV.write(filename, plants_report(solution))
--- a/src/reports/products.jl
+++ b/src/reports/products.jl
@@ -0,0 +1,43 @@
+# RELOG: Reverse Logistics Optimization
+# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+# Released under the modified BSD license. See COPYING.md for more details.
+
+using DataFrames
+using CSV
+
+function products_report(solution; marginal_costs = true)::DataFrame
+    df = DataFrame()
+    df."product name" = String[]
+    df."location name" = String[]
+    df."latitude (deg)" = Float64[]
+    df."longitude (deg)" = Float64[]
+    df."year" = Int[]
+    df."amount (tonne)" = Float64[]
+    df."marginal cost (\$/tonne)" = 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]
+                latitude = round(location_dict["Latitude (deg)"], digits = 6)
+                longitude = round(location_dict["Longitude (deg)"], digits = 6)
+                amount = location_dict["Amount (tonne)"][year]
+                push!(
+                    df,
+                    [
+                        prod_name,
+                        location_name,
+                        latitude,
+                        longitude,
+                        year,
+                        amount,
+                        marginal_cost,
+                    ],
+                )
+            end
+        end
+    end
+    return df
+end
+
+write_products_report(solution, filename) = CSV.write(filename, products_report(solution))
--- a/src/reports/tr.jl
+++ b/src/reports/tr.jl
@@ -0,0 +1,75 @@
+# RELOG: Reverse Logistics Optimization
+# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+# Released under the modified BSD license. See COPYING.md for more details.
+
+using DataFrames
+using CSV
+
+function transportation_report(solution)::DataFrame
+    df = DataFrame()
+    df."source type" = String[]
+    df."source location name" = String[]
+    df."source latitude (deg)" = Float64[]
+    df."source longitude (deg)" = Float64[]
+    df."destination type" = String[]
+    df."destination location name" = String[]
+    df."destination latitude (deg)" = Float64[]
+    df."destination longitude (deg)" = Float64[]
+    df."product" = String[]
+    df."year" = Int[]
+    df."distance (km)" = Float64[]
+    df."amount (tonne)" = Float64[]
+    df."amount-distance (tonne-km)" = Float64[]
+    df."transportation cost (\$)" = Float64[]
+    df."transportation energy (GJ)" = Float64[]
+
+    T = length(solution["Energy"]["Plants (GJ)"])
+    for (dst_plant_name, dst_plant_dict) in solution["Plants"]
+        for (dst_location_name, dst_location_dict) in dst_plant_dict
+            for (src_plant_name, src_plant_dict) in dst_location_dict["Input"]
+                for (src_location_name, src_location_dict) in src_plant_dict
+                    for year = 1:T
+                        push!(
+                            df,
+                            [
+                                src_plant_name,
+                                src_location_name,
+                                round(src_location_dict["Latitude (deg)"], digits = 6),
+                                round(src_location_dict["Longitude (deg)"], digits = 6),
+                                dst_plant_name,
+                                dst_location_name,
+                                round(dst_location_dict["Latitude (deg)"], digits = 6),
+                                round(dst_location_dict["Longitude (deg)"], digits = 6),
+                                dst_location_dict["Input product"],
+                                year,
+                                round(src_location_dict["Distance (km)"], digits = 2),
+                                round(
+                                    src_location_dict["Amount (tonne)"][year],
+                                    digits = 2,
+                                ),
+                                round(
+                                    src_location_dict["Amount (tonne)"][year] *
+                                    src_location_dict["Distance (km)"],
+                                    digits = 2,
+                                ),
+                                round(
+                                    src_location_dict["Transportation cost (\$)"][year],
+                                    digits = 2,
+                                ),
+                                round(
+                                    src_location_dict["Transportation energy (J)"][year] /
+                                    1e9,
+                                    digits = 2,
+                                ),
+                            ],
+                        )
+                    end
+                end
+            end
+        end
+    end
+    return df
+end
+
+write_transportation_report(solution, filename) =
+    CSV.write(filename, transportation_report(solution))
--- a/src/reports/tr_emissions.jl
+++ b/src/reports/tr_emissions.jl
@@ -0,0 +1,71 @@
+# RELOG: Reverse Logistics Optimization
+# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+# Released under the modified BSD license. See COPYING.md for more details.
+
+using DataFrames
+using CSV
+
+function transportation_emissions_report(solution)::DataFrame
+    df = DataFrame()
+    df."source type" = String[]
+    df."source location name" = String[]
+    df."source latitude (deg)" = Float64[]
+    df."source longitude (deg)" = Float64[]
+    df."destination type" = String[]
+    df."destination location name" = String[]
+    df."destination latitude (deg)" = Float64[]
+    df."destination longitude (deg)" = Float64[]
+    df."product" = String[]
+    df."year" = Int[]
+    df."distance (km)" = Float64[]
+    df."shipped amount (tonne)" = Float64[]
+    df."shipped amount-distance (tonne-km)" = Float64[]
+    df."emission type" = String[]
+    df."emission amount (tonne)" = Float64[]
+
+    T = length(solution["Energy"]["Plants (GJ)"])
+    for (dst_plant_name, dst_plant_dict) in solution["Plants"]
+        for (dst_location_name, dst_location_dict) in dst_plant_dict
+            for (src_plant_name, src_plant_dict) in dst_location_dict["Input"]
+                for (src_location_name, src_location_dict) in src_plant_dict
+                    for (emission_name, emission_amount) in
+                        src_location_dict["Emissions (tonne)"]
+                        for year = 1:T
+                            push!(
+                                df,
+                                [
+                                    src_plant_name,
+                                    src_location_name,
+                                    round(src_location_dict["Latitude (deg)"], digits = 6),
+                                    round(src_location_dict["Longitude (deg)"], digits = 6),
+                                    dst_plant_name,
+                                    dst_location_name,
+                                    round(dst_location_dict["Latitude (deg)"], digits = 6),
+                                    round(dst_location_dict["Longitude (deg)"], digits = 6),
+                                    dst_location_dict["Input product"],
+                                    year,
+                                    round(src_location_dict["Distance (km)"], digits = 2),
+                                    round(
+                                        src_location_dict["Amount (tonne)"][year],
+                                        digits = 2,
+                                    ),
+                                    round(
+                                        src_location_dict["Amount (tonne)"][year] *
+                                        src_location_dict["Distance (km)"],
+                                        digits = 2,
+                                    ),
+                                    emission_name,
+                                    round(emission_amount[year], digits = 2),
+                                ],
+                            )
+                        end
+                    end
+                end
+            end
+        end
+    end
+    return df
+end
+
+write_transportation_emissions_report(solution, filename) =
+    CSV.write(filename, transportation_emissions_report(solution))
--- a/src/reports/write.jl
+++ b/src/reports/write.jl
@@ -0,0 +1,14 @@
+# RELOG: Reverse Logistics Optimization
+# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+# Released under the modified BSD license. See COPYING.md for more details.
+
+using DataFrames
+using CSV
+import Base: write
+
+function write(solution::AbstractDict, filename::AbstractString)
+    @info "Writing solution: $filename"
+    open(filename, "w") do file
+        JSON.print(file, solution, 2)
+    end
+end
--- a/src/schemas/input.json
+++ b/src/schemas/input.json
@@ -12,7 +12,9 @@
        "Parameters": {
            "type": "object",
            "properties": {
-                "time horizon (years)": { "type": "number" }
+                "time horizon (years)": {
+                    "type": "number"
+                }
            },
            "required": [
                "time horizon (years)"
@@ -23,17 +25,27 @@
            "additionalProperties": {
                "type": "object",
                "properties": {
-                    "input": { "type": "string" },
+                    "input": {
+                        "type": "string"
+                    },
                    "outputs (tonne/tonne)": {
                        "type": "object",
-                        "additionalProperties": { "type": "number" }
+                        "additionalProperties": {
+                            "type": "number"
+                        }
+                    },
+                    "energy (GJ/tonne)": {
+                        "$ref": "#/definitions/TimeSeries"
                    },
-                    "energy (GJ/tonne)": { "$ref": "#/definitions/TimeSeries" },
                    "emissions (tonne/tonne)": {
                        "type": "object",
-                        "additionalProperties": { "$ref": "#/definitions/TimeSeries" }
+                        "additionalProperties": {
+                            "$ref": "#/definitions/TimeSeries"
+                        }
                    },
-                    "locations": { "$ref": "#/definitions/PlantLocation" }
+                    "locations": {
+                        "$ref": "#/definitions/PlantLocation"
+                    }
                },
                "required": [
                    "input",
@@ -46,15 +58,26 @@
            "additionalProperties": {
                "type": "object",
                "properties": {
-                    "latitude (deg)": { "type": "number" },
-                    "longitude (deg)": { "type": "number" },
+                    "location": {
+                        "type": "string"
+                    },
+                    "latitude (deg)": {
+                        "type": "number"
+                    },
+                    "longitude (deg)": {
+                        "type": "number"
+                    },
                    "disposal": {
                        "type": "object",
                        "additionalProperties": {
                            "type": "object",
                            "properties": {
-                                "cost ($/tonne)": { "$ref": "#/definitions/TimeSeries" },
-                                "limit (tonne)": { "$ref": "#/definitions/TimeSeries" }
+                                "cost ($/tonne)": {
+                                    "$ref": "#/definitions/TimeSeries"
+                                },
+                                "limit (tonne)": {
+                                    "$ref": "#/definitions/TimeSeries"
+                                }
                            },
                            "required": [
                                "cost ($/tonne)"
@@ -64,22 +87,32 @@
                    "storage": {
                        "type": "object",
                        "properties": {
-                            "cost ($/tonne)": { "$ref": "#/definitions/TimeSeries" },
-                            "limit (tonne)": { "type": "number" }
+                            "cost ($/tonne)": {
+                                "$ref": "#/definitions/TimeSeries"
+                            },
+                            "limit (tonne)": {
+                                "type": "number"
+                            }
                        },
                        "required": [
                            "cost ($/tonne)",
                            "limit (tonne)"
                        ]
-                    },                    
+                    },
                    "capacities (tonne)": {
                        "type": "object",
                        "additionalProperties": {
                            "type": "object",
                            "properties": {
-                                "variable operating cost ($/tonne)": { "$ref": "#/definitions/TimeSeries" },
-                                "fixed operating cost ($)": { "$ref": "#/definitions/TimeSeries" },
-                                "opening cost ($)": { "$ref": "#/definitions/TimeSeries" }
+                                "variable operating cost ($/tonne)": {
+                                    "$ref": "#/definitions/TimeSeries"
+                                },
+                                "fixed operating cost ($)": {
+                                    "$ref": "#/definitions/TimeSeries"
+                                },
+                                "opening cost ($)": {
+                                    "$ref": "#/definitions/TimeSeries"
+                                }
                            },
                            "required": [
                                "variable operating cost ($/tonne)",
@@ -87,11 +120,9 @@
                                "opening cost ($)"
                            ]
                        }
-                    }                    
+                    }
                },
                "required": [
-                    "latitude (deg)",
-                    "longitude (deg)",
                    "capacities (tonne)"
                ]
            }
@@ -101,13 +132,20 @@
            "additionalProperties": {
                "type": "object",
                "properties": {
-                    "latitude (deg)": { "type": "number" },
-                    "longitude (deg)": { "type": "number" },
-                    "amount (tonne)": { "$ref": "#/definitions/TimeSeries" }
+                    "location": {
+                        "type": "string"
+                    },
+                    "latitude (deg)": {
+                        "type": "number"
+                    },
+                    "longitude (deg)": {
+                        "type": "number"
+                    },
+                    "amount (tonne)": {
+                        "$ref": "#/definitions/TimeSeries"
+                    }
                },
                "required": [
-                    "latitude (deg)",
-                    "longitude (deg)",
                    "amount (tonne)"
                ]
            }
@@ -117,25 +155,39 @@
            "additionalProperties": {
                "type": "object",
                "properties": {
-                    "transportation cost ($/km/tonne)": { "$ref": "#/definitions/TimeSeries" },
-                    "transportation energy (J/km/tonne)": { "$ref": "#/definitions/TimeSeries" },
+                    "transportation cost ($/km/tonne)": {
+                        "$ref": "#/definitions/TimeSeries"
+                    },
+                    "transportation energy (J/km/tonne)": {
+                        "$ref": "#/definitions/TimeSeries"
+                    },
                    "transportation emissions (tonne/km/tonne)": {
                        "type": "object",
-                        "additionalProperties": { "$ref": "#/definitions/TimeSeries" }
+                        "additionalProperties": {
+                            "$ref": "#/definitions/TimeSeries"
+                        }
                    },
-                    "initial amounts": { "$ref": "#/definitions/InitialAmount" }
+                    "initial amounts": {
+                        "$ref": "#/definitions/InitialAmount"
+                    }
                },
                "required": [
                    "transportation cost ($/km/tonne)"
                ]
-            }            
+            }
        }
    },
    "type": "object",
    "properties": {
-        "parameters": { "$ref": "#/definitions/Parameters" },
-        "plants": { "$ref": "#/definitions/Plant" },
-        "products": { "$ref": "#/definitions/Product" }
+        "parameters": {
+            "$ref": "#/definitions/Parameters"
+        },
+        "plants": {
+            "$ref": "#/definitions/Plant"
+        },
+        "products": {
+            "$ref": "#/definitions/Product"
+        }
    },
    "required": [
        "parameters",
--- a/src/sysimage.jl
+++ b/src/sysimage.jl
@@ -9,14 +9,7 @@ using JuMP
 using MathOptInterface
 using ProgressBars

-pkg = [:Cbc,
-       :Clp,
-       :Geodesy,
-       :JSON,
-       :JSONSchema,
-       :JuMP,
-       :MathOptInterface,
-       :ProgressBars]
+pkg = [:Cbc, :Clp, :Geodesy, :JSON, :JSONSchema, :JuMP, :MathOptInterface, :ProgressBars]

@info "Building system image..."
-create_sysimage(pkg, sysimage_path="build/sysimage.so")
+create_sysimage(pkg, sysimage_path = "build/sysimage.so")
--- a/test/fixtures/nimh_plant_emissions.csv
+++ b/test/fixtures/nimh_plant_emissions.csv
@@ -1,7 +0,0 @@
-plant type,location name,year,emission type,emission amount (tonne)
-Rare Earth Recycling Plant,"Sebastian, Arkansas",1,CO2,40711.3
-Rare Earth Recycling Plant,"Stanly, North Carolina",1,CO2,23336.47
-Rare Earth Recycling Plant,"Lynn, Texas",1,CO2,52927.44
-Mega Plant,"Sebastian, Arkansas",1,CO2,110818.84
-Mega Plant,"District of Columbia, District of Columbia",1,CO2,63523.43
-Mega Plant,"Maricopa, Arizona",1,CO2,144072.0
--- a/test/fixtures/nimh_plant_outputs.csv
+++ b/test/fixtures/nimh_plant_outputs.csv
@@ -1,37 +0,0 @@
-plant type,location name,year,product name,amount produced (tonne),amount sent (tonne),amount disposed (tonne),disposal cost ($)
-Rare Earth Recycling Plant,"Sebastian, Arkansas",1,rare earth cela,18045.12,0.0,18045.12,0.0
-Rare Earth Recycling Plant,"Sebastian, Arkansas",1,rare earth diddy,7624.02,0.0,7624.02,0.0
-Rare Earth Recycling Plant,"Sebastian, Arkansas",1,salt,6434.8,0.0,6434.8,324314.03
-Rare Earth Recycling Plant,"Sebastian, Arkansas",1,rare earth misch,2188.78,0.0,2188.78,0.0
-Rare Earth Recycling Plant,"Stanly, North Carolina",1,rare earth cela,10343.8,0.0,10343.8,0.0
-Rare Earth Recycling Plant,"Stanly, North Carolina",1,rare earth diddy,4370.23,0.0,4370.23,0.0
-Rare Earth Recycling Plant,"Stanly, North Carolina",1,salt,3688.55,0.0,3688.55,185902.85
-Rare Earth Recycling Plant,"Stanly, North Carolina",1,rare earth misch,1254.65,0.0,1254.65,0.0
-Rare Earth Recycling Plant,"Lynn, Texas",1,rare earth cela,23459.88,0.0,23459.88,0.0
-Rare Earth Recycling Plant,"Lynn, Texas",1,rare earth diddy,9911.74,0.0,9911.74,0.0
-Rare Earth Recycling Plant,"Lynn, Texas",1,salt,8365.68,0.0,8365.68,421630.2
-Rare Earth Recycling Plant,"Lynn, Texas",1,rare earth misch,2845.56,0.0,2845.56,0.0
-Mega Plant,"Sebastian, Arkansas",1,iron-nickel scrap,35656.28,0.0,35656.28,0.0
-Mega Plant,"Sebastian, Arkansas",1,mixed-hydroxides,73141.86,0.0,73141.86,0.0
-Mega Plant,"Sebastian, Arkansas",1,leach residue,31470.35,0.0,31470.35,6.38848022e6
-Mega Plant,"Sebastian, Arkansas",1,plastic pack,96503.37,0.0,96503.37,4.86376966e6
-Mega Plant,"Sebastian, Arkansas",1,salt,285304.6,0.0,285304.6,1.437935192e7
-Mega Plant,"Sebastian, Arkansas",1,rare earth mix,44145.84,44145.84,0.0,0.0
-Mega Plant,"Sebastian, Arkansas",1,nickel-iron scrap,178655.26,0.0,178655.26,0.0
-Mega Plant,"Sebastian, Arkansas",1,nickel,37931.36,0.0,37931.36,0.0
-Mega Plant,"District of Columbia, District of Columbia",1,iron-nickel scrap,20438.84,0.0,20438.84,0.0
-Mega Plant,"District of Columbia, District of Columbia",1,mixed-hydroxides,41926.28,0.0,41926.28,0.0
-Mega Plant,"District of Columbia, District of Columbia",1,leach residue,18039.39,0.0,18039.39,3.66199595e6
-Mega Plant,"District of Columbia, District of Columbia",1,plastic pack,55317.53,0.0,55317.53,2.78800343e6
-Mega Plant,"District of Columbia, District of Columbia",1,salt,163541.92,0.0,163541.92,8.24251257e6
-Mega Plant,"District of Columbia, District of Columbia",1,rare earth mix,25305.22,25305.22,0.0,0.0
-Mega Plant,"District of Columbia, District of Columbia",1,nickel-iron scrap,102408.52,0.0,102408.52,0.0
-Mega Plant,"District of Columbia, District of Columbia",1,nickel,21742.96,0.0,21742.96,0.0
-Mega Plant,"Maricopa, Arizona",1,iron-nickel scrap,46355.57,0.0,46355.57,0.0
-Mega Plant,"Maricopa, Arizona",1,mixed-hydroxides,95089.37,0.0,95089.37,0.0
-Mega Plant,"Maricopa, Arizona",1,leach residue,40913.58,0.0,40913.58,8.30545698e6
-Mega Plant,"Maricopa, Arizona",1,plastic pack,125460.91,0.0,125460.91,6.32322998e6
-Mega Plant,"Maricopa, Arizona",1,salt,370915.31,0.0,370915.31,1.869413141e7
-Mega Plant,"Maricopa, Arizona",1,rare earth mix,57392.58,57392.58,0.0,0.0
-Mega Plant,"Maricopa, Arizona",1,nickel-iron scrap,232263.93,0.0,232263.93,0.0
-Mega Plant,"Maricopa, Arizona",1,nickel,49313.34,0.0,49313.34,0.0
--- a/test/fixtures/nimh_plants.csv
+++ b/test/fixtures/nimh_plants.csv
@@ -1,7 +0,0 @@
-plant type,location name,year,latitude (deg),longitude (deg),capacity (tonne),amount processed (tonne),utilization factor (%),energy (GJ),opening cost ($),expansion cost ($),fixed operating cost ($),variable operating cost ($),total cost ($)
-Rare Earth Recycling Plant,"Sebastian, Arkansas",1,35.23416,-94.212943,44145.84,44145.84,100.0,1.13360359e6,6.9926855e6,1.793555439e7,1.677420707e7,1.0080261442e8,1.4250506138e8
-Rare Earth Recycling Plant,"Stanly, North Carolina",1,35.334445,-80.223231,25305.22,25305.22,100.0,649802.71,7.1653444e6,9.98954108e6,1.126536154e7,5.778193764e7,8.620218466e7
-Rare Earth Recycling Plant,"Lynn, Texas",1,33.166444,-101.793455,57392.58,57392.58,100.0,1.47376145e6,7.4243328e6,2.5154042e7,2.06474474e7,1.310502261e8,1.842760483e8
-Mega Plant,"Sebastian, Arkansas",1,35.23416,-94.212943,553817.3,553817.3,100.0,3.08574408e6,1.6858178e7,4.012879371e7,3.834652057e7,4.2898688058e8,5.2432037286e8
-Mega Plant,"District of Columbia, District of Columbia",1,38.930028,-76.974164,317458.4,317458.4,100.0,1.76880602e6,2.12288167e7,2.746685387e7,2.602109584e7,2.4590327664e8,3.2062004305e8
-Mega Plant,"Maricopa, Arizona",1,33.647365,-111.893669,720000.0,720000.0,100.0,4.0116763e6,2.10206911e7,6.60955172e7,4.70124619e7,5.57712e8,6.918406702e8
--- a/test/fixtures/nimh_solution.json.gz
+++ b/test/fixtures/nimh_solution.json.gz
--- a/test/fixtures/nimh_transportation.csv
+++ b/test/fixtures/nimh_transportation.csv
--- a/test/fixtures/nimh_transportation_emissions.csv
+++ b/test/fixtures/nimh_transportation_emissions.csv
--- a/test/graph/build_test.jl
+++ b/test/graph/build_test.jl
@@ -0,0 +1,39 @@
+# Copyright (C) 2020 Argonne National Laboratory
+# Written by Alinson Santos Xavier <axavier@anl.gov>
+
+using RELOG
+
+@testset "build_graph" begin
+    basedir = dirname(@__FILE__)
+    instance = RELOG.parsefile("$basedir/../../instances/s1.json")
+    graph = RELOG.build_graph(instance)
+    process_node_by_location_name =
+        Dict(n.location.location_name => n for n in graph.process_nodes)
+
+    @test length(graph.plant_shipping_nodes) == 8
+    @test length(graph.collection_shipping_nodes) == 10
+    @test length(graph.process_nodes) == 6
+
+    node = graph.collection_shipping_nodes[1]
+    @test node.location.name == "C1"
+    @test length(node.incoming_arcs) == 0
+    @test length(node.outgoing_arcs) == 2
+    @test node.outgoing_arcs[1].source.location.name == "C1"
+    @test node.outgoing_arcs[1].dest.location.plant_name == "F1"
+    @test node.outgoing_arcs[1].dest.location.location_name == "L1"
+    @test node.outgoing_arcs[1].values["distance"] == 1095.62
+
+    node = process_node_by_location_name["L1"]
+    @test node.location.plant_name == "F1"
+    @test node.location.location_name == "L1"
+    @test length(node.incoming_arcs) == 10
+    @test length(node.outgoing_arcs) == 2
+
+    node = process_node_by_location_name["L3"]
+    @test node.location.plant_name == "F2"
+    @test node.location.location_name == "L3"
+    @test length(node.incoming_arcs) == 2
+    @test length(node.outgoing_arcs) == 2
+
+    @test length(graph.arcs) == 38
+end
--- a/test/graph_test.jl
+++ b/test/graph_test.jl
@@ -1,42 +0,0 @@
-# Copyright (C) 2020 Argonne National Laboratory
-# Written by Alinson Santos Xavier <axavier@anl.gov>
-
-using RELOG
-
-@testset "Graph" begin
-    @testset "build_graph" begin
-        basedir = dirname(@__FILE__)
-        instance = RELOG.parsefile("$basedir/../instances/s1.json")
-        graph = RELOG.build_graph(instance)
-        process_node_by_location_name = Dict(n.location.location_name => n
-                                             for n in graph.process_nodes)
-        
-        @test length(graph.plant_shipping_nodes) == 8
-        @test length(graph.collection_shipping_nodes) == 10
-        @test length(graph.process_nodes) == 6
-        
-        node = graph.collection_shipping_nodes[1]
-        @test node.location.name == "C1"
-        @test length(node.incoming_arcs) == 0
-        @test length(node.outgoing_arcs) == 2
-        @test node.outgoing_arcs[1].source.location.name == "C1"
-        @test node.outgoing_arcs[1].dest.location.plant_name == "F1"
-        @test node.outgoing_arcs[1].dest.location.location_name == "L1"
-        @test node.outgoing_arcs[1].values["distance"] == 1095.62
-        
-        node = process_node_by_location_name["L1"]
-        @test node.location.plant_name == "F1"
-        @test node.location.location_name == "L1"
-        @test length(node.incoming_arcs) == 10
-        @test length(node.outgoing_arcs) == 2
-        
-        node = process_node_by_location_name["L3"]
-        @test node.location.plant_name == "F2"
-        @test node.location.location_name == "L3"
-        @test length(node.incoming_arcs) == 2
-        @test length(node.outgoing_arcs) == 2
-        
-        @test length(graph.arcs) == 38
-    end
-end
-
--- a/test/instance/compress_test.jl
+++ b/test/instance/compress_test.jl
@@ -0,0 +1,53 @@
+# Copyright (C) 2020 Argonne National Laboratory
+# Written by Alinson Santos Xavier <axavier@anl.gov>
+
+using RELOG
+
+@testset "compress" begin
+    basedir = dirname(@__FILE__)
+    instance = RELOG.parsefile("$basedir/../../instances/s1.json")
+    compressed = RELOG._compress(instance)
+
+    product_name_to_product = Dict(p.name => p for p in compressed.products)
+    location_name_to_facility = Dict()
+    for p in compressed.plants
+        location_name_to_facility[p.location_name] = p
+    end
+    for c in compressed.collection_centers
+        location_name_to_facility[c.name] = c
+    end
+
+    p1 = product_name_to_product["P1"]
+    p2 = product_name_to_product["P2"]
+    p3 = product_name_to_product["P3"]
+    c1 = location_name_to_facility["C1"]
+    l1 = location_name_to_facility["L1"]
+
+    @test compressed.time == 1
+    @test compressed.building_period == [1]
+
+    @test p1.name == "P1"
+    @test p1.transportation_cost ≈ [0.015]
+    @test p1.transportation_energy ≈ [0.115]
+    @test p1.transportation_emissions["CO2"] ≈ [0.051]
+    @test p1.transportation_emissions["CH4"] ≈ [0.0025]
+
+    @test c1.name == "C1"
+    @test c1.amount ≈ [1869.12]
+
+    @test l1.plant_name == "F1"
+    @test l1.location_name == "L1"
+    @test l1.energy ≈ [0.115]
+    @test l1.emissions["CO2"] ≈ [0.051]
+    @test l1.emissions["CH4"] ≈ [0.0025]
+    @test l1.sizes[1].opening_cost ≈ [500]
+    @test l1.sizes[2].opening_cost ≈ [1250]
+    @test l1.sizes[1].fixed_operating_cost ≈ [60]
+    @test l1.sizes[2].fixed_operating_cost ≈ [60]
+    @test l1.sizes[1].variable_operating_cost ≈ [30]
+    @test l1.sizes[2].variable_operating_cost ≈ [30]
+    @test l1.disposal_limit[p2] ≈ [2.0]
+    @test l1.disposal_limit[p3] ≈ [2.0]
+    @test l1.disposal_cost[p2] ≈ [-10.0]
+    @test l1.disposal_cost[p3] ≈ [-10.0]
+end
--- a/test/instance/geodb_test.jl
+++ b/test/instance/geodb_test.jl
@@ -0,0 +1,25 @@
+# RELOG: Reverse Logistics Optimization
+# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+# Released under the modified BSD license. See COPYING.md for more details.
+
+using RELOG
+
+@testset "geodb_query (2018-us-county)" begin
+    region = RELOG.geodb_query("2018-us-county:17043")
+    @test region.centroid.lat == 41.83956
+    @test region.centroid.lon == -88.08857
+    @test region.population == 922_921
+end
+
+# @testset "geodb_query (2018-us-zcta)" begin
+#     region = RELOG.geodb_query("2018-us-zcta:60439")
+#     @test region.centroid.lat == 41.68241
+#     @test region.centroid.lon == -87.98954
+# end
+
+@testset "geodb_query (us-state)" begin
+    region = RELOG.geodb_query("us-state:IL")
+    @test region.centroid.lat == 39.73939
+    @test region.centroid.lon == -89.50414
+    @test region.population == 12_671_821
+end
--- a/test/instance/parse_test.jl
+++ b/test/instance/parse_test.jl
@@ -0,0 +1,86 @@
+# Copyright (C) 2020 Argonne National Laboratory
+# Written by Alinson Santos Xavier <axavier@anl.gov>
+
+using RELOG
+
+@testset "parse" begin
+    basedir = dirname(@__FILE__)
+    instance = RELOG.parsefile("$basedir/../../instances/s1.json")
+
+    centers = instance.collection_centers
+    plants = instance.plants
+    products = instance.products
+    location_name_to_plant = Dict(p.location_name => p for p in plants)
+    product_name_to_product = Dict(p.name => p for p in products)
+
+    @test length(centers) == 10
+    @test centers[1].name == "C1"
+    @test centers[1].latitude == 7
+    @test centers[1].latitude == 7
+    @test centers[1].longitude == 7
+    @test centers[1].amount == [934.56, 934.56]
+    @test centers[1].product.name == "P1"
+
+    @test length(plants) == 6
+
+    plant = location_name_to_plant["L1"]
+    @test plant.plant_name == "F1"
+    @test plant.location_name == "L1"
+    @test plant.input.name == "P1"
+    @test plant.latitude == 0
+    @test plant.longitude == 0
+
+    @test length(plant.sizes) == 2
+    @test plant.sizes[1].capacity == 250
+    @test plant.sizes[1].opening_cost == [500, 500]
+    @test plant.sizes[1].fixed_operating_cost == [30, 30]
+    @test plant.sizes[1].variable_operating_cost == [30, 30]
+    @test plant.sizes[2].capacity == 1000
+    @test plant.sizes[2].opening_cost == [1250, 1250]
+    @test plant.sizes[2].fixed_operating_cost == [30, 30]
+    @test plant.sizes[2].variable_operating_cost == [30, 30]
+
+    p2 = product_name_to_product["P2"]
+    p3 = product_name_to_product["P3"]
+    @test length(plant.output) == 2
+    @test plant.output[p2] == 0.2
+    @test plant.output[p3] == 0.5
+    @test plant.disposal_limit[p2] == [1, 1]
+    @test plant.disposal_limit[p3] == [1, 1]
+    @test plant.disposal_cost[p2] == [-10, -10]
+    @test plant.disposal_cost[p3] == [-10, -10]
+
+    plant = location_name_to_plant["L3"]
+    @test plant.location_name == "L3"
+    @test plant.input.name == "P2"
+    @test plant.latitude == 25
+    @test plant.longitude == 65
+
+    @test length(plant.sizes) == 2
+    @test plant.sizes[1].capacity == 1000.0
+    @test plant.sizes[1].opening_cost == [3000, 3000]
+    @test plant.sizes[1].fixed_operating_cost == [50, 50]
+    @test plant.sizes[1].variable_operating_cost == [50, 50]
+    @test plant.sizes[1] == plant.sizes[2]
+
+    p4 = product_name_to_product["P4"]
+    @test plant.output[p3] == 0.05
+    @test plant.output[p4] == 0.8
+    @test plant.disposal_limit[p3] == [1e8, 1e8]
+    @test plant.disposal_limit[p4] == [0, 0]
+end
+
+@testset "parse (geodb)" begin
+    basedir = dirname(@__FILE__)
+    instance = RELOG.parsefile("$basedir/../../instances/s2.json")
+
+    centers = instance.collection_centers
+    @test centers[1].name == "C1"
+    @test centers[1].latitude == 41.83956
+    @test centers[1].longitude == -88.08857
+end
+
+# @testset "parse (invalid)" begin
+#     basedir = dirname(@__FILE__)
+#     @test_throws ErrorException RELOG.parsefile("$basedir/../fixtures/s1-wrong-length.json")
+# end
--- a/test/instance_test.jl
+++ b/test/instance_test.jl
@@ -1,127 +0,0 @@
-# Copyright (C) 2020 Argonne National Laboratory
-# Written by Alinson Santos Xavier <axavier@anl.gov>
-
-using RELOG
-
-@testset "Instance" begin
-    @testset "load" begin
-        basedir = dirname(@__FILE__)
-        instance = RELOG.parsefile("$basedir/../instances/s1.json")
-        
-        centers = instance.collection_centers
-        plants = instance.plants
-        products = instance.products
-        location_name_to_plant = Dict(p.location_name => p for p in plants)
-        product_name_to_product = Dict(p.name => p for p in products)
-        
-        @test length(centers) == 10
-        @test centers[1].name == "C1"
-        @test centers[1].latitude == 7
-        @test centers[1].latitude == 7
-        @test centers[1].longitude == 7
-        @test centers[1].amount == [934.56, 934.56]
-        @test centers[1].product.name == "P1"
-        
-        @test length(plants) == 6
-
-        plant = location_name_to_plant["L1"]
-        @test plant.plant_name == "F1"
-        @test plant.location_name == "L1"
-        @test plant.input.name == "P1"
-        @test plant.latitude == 0
-        @test plant.longitude == 0
-        
-        @test length(plant.sizes) == 2
-        @test plant.sizes[1].capacity == 250
-        @test plant.sizes[1].opening_cost == [500, 500]
-        @test plant.sizes[1].fixed_operating_cost == [30, 30]
-        @test plant.sizes[1].variable_operating_cost == [30, 30]
-        @test plant.sizes[2].capacity == 1000
-        @test plant.sizes[2].opening_cost == [1250, 1250]
-        @test plant.sizes[2].fixed_operating_cost == [30, 30]
-        @test plant.sizes[2].variable_operating_cost == [30, 30]
-        
-        p2 = product_name_to_product["P2"]
-        p3 = product_name_to_product["P3"]
-        @test length(plant.output) == 2
-        @test plant.output[p2] == 0.2
-        @test plant.output[p3] == 0.5
-        @test plant.disposal_limit[p2] == [1, 1]
-        @test plant.disposal_limit[p3] == [1, 1]
-        @test plant.disposal_cost[p2] == [-10, -10]
-        @test plant.disposal_cost[p3] == [-10, -10]
-        
-        plant = location_name_to_plant["L3"]
-        @test plant.location_name == "L3"
-        @test plant.input.name == "P2"
-        @test plant.latitude == 25
-        @test plant.longitude == 65
-        
-        @test length(plant.sizes) == 2
-        @test plant.sizes[1].capacity == 1000.0
-        @test plant.sizes[1].opening_cost == [3000, 3000]
-        @test plant.sizes[1].fixed_operating_cost == [50, 50]
-        @test plant.sizes[1].variable_operating_cost == [50, 50]
-        @test plant.sizes[1] == plant.sizes[2]
-        
-        p4 = product_name_to_product["P4"]
-        @test plant.output[p3] == 0.05
-        @test plant.output[p4] == 0.8
-        @test plant.disposal_limit[p3] == [1e8, 1e8]
-        @test plant.disposal_limit[p4] == [0, 0]
-    end
-    
-    @testset "validate timeseries" begin
-        @test_throws String RELOG.parsefile("fixtures/s1-wrong-length.json")
-    end
-    
-    @testset "compress" begin
-        basedir = dirname(@__FILE__)
-        instance = RELOG.parsefile("$basedir/../instances/s1.json")
-        compressed = RELOG._compress(instance)
-        
-        product_name_to_product = Dict(p.name => p for p in compressed.products)
-        location_name_to_facility = Dict()
-        for p in compressed.plants
-            location_name_to_facility[p.location_name] = p
-        end
-        for c in compressed.collection_centers
-            location_name_to_facility[c.name] = c
-        end
-        
-        p1 = product_name_to_product["P1"]
-        p2 = product_name_to_product["P2"]
-        p3 = product_name_to_product["P3"]
-        c1 = location_name_to_facility["C1"]
-        l1 = location_name_to_facility["L1"]
-
-        @test compressed.time == 1
-        @test compressed.building_period == [1]
-
-        @test p1.name == "P1"
-        @test p1.transportation_cost ≈ [0.015]
-        @test p1.transportation_energy ≈ [0.115]
-        @test p1.transportation_emissions["CO2"] ≈ [0.051]
-        @test p1.transportation_emissions["CH4"] ≈ [0.0025]
-        
-        @test c1.name == "C1"
-        @test c1.amount ≈ [1869.12]
-        
-        @test l1.plant_name == "F1"
-        @test l1.location_name == "L1"
-        @test l1.energy ≈ [0.115]
-        @test l1.emissions["CO2"] ≈ [0.051]
-        @test l1.emissions["CH4"] ≈ [0.0025]
-        @test l1.sizes[1].opening_cost ≈ [500]
-        @test l1.sizes[2].opening_cost ≈ [1250]
-        @test l1.sizes[1].fixed_operating_cost ≈ [60]
-        @test l1.sizes[2].fixed_operating_cost ≈ [60]
-        @test l1.sizes[1].variable_operating_cost ≈ [30]
-        @test l1.sizes[2].variable_operating_cost ≈ [30]
-        @test l1.disposal_limit[p2] ≈ [2.0]
-        @test l1.disposal_limit[p3] ≈ [2.0]
-        @test l1.disposal_cost[p2] ≈ [-10.0]
-        @test l1.disposal_cost[p3] ≈ [-10.0]        
-    end
-end
-
--- a/test/model/build_test.jl
+++ b/test/model/build_test.jl
@@ -0,0 +1,38 @@
+# Copyright (C) 2020 Argonne National Laboratory
+# Written by Alinson Santos Xavier <axavier@anl.gov>
+
+using RELOG, Cbc, JuMP, Printf, JSON, MathOptInterface.FileFormats
+
+@testset "build" begin
+    basedir = dirname(@__FILE__)
+    instance = RELOG.parsefile("$basedir/../../instances/s1.json")
+    graph = RELOG.build_graph(instance)
+    model = RELOG.build_model(instance, graph, Cbc.Optimizer)
+    set_optimizer_attribute(model, "logLevel", 0)
+
+    process_node_by_location_name =
+        Dict(n.location.location_name => n for n in graph.process_nodes)
+
+    shipping_node_by_loc_and_prod_names = Dict(
+        (n.location.location_name, n.product.name) => n for n in graph.plant_shipping_nodes
+    )
+
+    @test length(model[:flow]) == 76
+    @test length(model[:dispose]) == 16
+    @test length(model[:open_plant]) == 12
+    @test length(model[:capacity]) == 12
+    @test length(model[:expansion]) == 12
+
+    l1 = process_node_by_location_name["L1"]
+    v = model[:capacity][l1, 1]
+    @test lower_bound(v) == 0.0
+    @test upper_bound(v) == 1000.0
+
+    v = model[:expansion][l1, 1]
+    @test lower_bound(v) == 0.0
+    @test upper_bound(v) == 750.0
+
+    v = model[:dispose][shipping_node_by_loc_and_prod_names["L1", "P2"], 1]
+    @test lower_bound(v) == 0.0
+    @test upper_bound(v) == 1.0
+end
--- a/test/model/resolve_test.jl
+++ b/test/model/resolve_test.jl
@@ -0,0 +1,11 @@
+# Copyright (C) 2020 Argonne National Laboratory
+# Written by Alinson Santos Xavier <axavier@anl.gov>
+
+using RELOG
+
+@testset "Resolve" begin
+    # Shoud not crash
+    filename = "$(pwd())/../instances/s1.json"
+    solution_old, model_old = RELOG.solve(filename, return_model = true)
+    solution_new = RELOG.resolve(model_old, filename)
+end
--- a/test/model/solve_test.jl
+++ b/test/model/solve_test.jl
@@ -0,0 +1,61 @@
+# Copyright (C) 2020 Argonne National Laboratory
+# Written by Alinson Santos Xavier <axavier@anl.gov>
+
+using RELOG, Cbc, JuMP, Printf, JSON, MathOptInterface.FileFormats
+
+basedir = dirname(@__FILE__)
+
+@testset "solve (exact)" begin
+    solution_filename_a = tempname()
+    solution_filename_b = tempname()
+    solution = RELOG.solve("$basedir/../../instances/s1.json", output = solution_filename_a)
+
+    @test isfile(solution_filename_a)
+
+    RELOG.write(solution, solution_filename_b)
+    @test isfile(solution_filename_b)
+
+    @test "Costs" in keys(solution)
+    @test "Fixed operating (\$)" in keys(solution["Costs"])
+    @test "Transportation (\$)" in keys(solution["Costs"])
+    @test "Variable operating (\$)" in keys(solution["Costs"])
+    @test "Total (\$)" in keys(solution["Costs"])
+
+    @test "Plants" in keys(solution)
+    @test "F1" in keys(solution["Plants"])
+    @test "F2" in keys(solution["Plants"])
+    @test "F3" in keys(solution["Plants"])
+    @test "F4" in keys(solution["Plants"])
+end
+
+@testset "solve (heuristic)" begin
+    # Should not crash
+    solution = RELOG.solve("$basedir/../../instances/s1.json", heuristic = true)
+end
+
+@testset "solve (infeasible)" begin
+    json = JSON.parsefile("$basedir/../../instances/s1.json")
+    for (location_name, location_dict) in json["products"]["P1"]["initial amounts"]
+        location_dict["amount (tonne)"] *= 1000
+    end
+    @test_throws ErrorException("No solution available") RELOG.solve(RELOG.parse(json))
+end
+
+@testset "solve (with storage)" begin
+    basedir = dirname(@__FILE__)
+    filename = "$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
--- a/test/model_test.jl
+++ b/test/model_test.jl
@@ -1,100 +0,0 @@
-# Copyright (C) 2020 Argonne National Laboratory
-# Written by Alinson Santos Xavier <axavier@anl.gov>
-
-using RELOG, Cbc, JuMP, Printf, JSON, MathOptInterface.FileFormats
-
-@testset "Model" begin
-    @testset "build" begin
-        basedir = dirname(@__FILE__)
-        instance = RELOG.parsefile("$basedir/../instances/s1.json")
-        graph = RELOG.build_graph(instance)
-        model = RELOG.build_model(instance, graph, Cbc.Optimizer)
-        set_optimizer_attribute(model.mip, "logLevel", 0)
-
-        process_node_by_location_name = Dict(n.location.location_name => n
-                                             for n in graph.process_nodes)
-
-        shipping_node_by_location_and_product_names = Dict((n.location.location_name, n.product.name) => n
-                                                           for n in graph.plant_shipping_nodes)
-        
-        @test length(model.vars.flow) == 76
-        @test length(model.vars.dispose) == 16
-        @test length(model.vars.open_plant) == 12
-        @test length(model.vars.capacity) == 12
-        @test length(model.vars.expansion) == 12
-
-        l1 = process_node_by_location_name["L1"]
-        v = model.vars.capacity[l1, 1]
-        @test lower_bound(v) == 0.0
-        @test upper_bound(v) == 1000.0
-        
-        v = model.vars.expansion[l1, 1]
-        @test lower_bound(v) == 0.0
-        @test upper_bound(v) == 750.0
-        
-        v = model.vars.dispose[shipping_node_by_location_and_product_names["L1", "P2"], 1]
-        @test lower_bound(v) == 0.0
-        @test upper_bound(v) == 1.0
-        
-        # dest = FileFormats.Model(format = FileFormats.FORMAT_LP)
-        # MOI.copy_to(dest, model.mip)
-        # MOI.write_to_file(dest, "model.lp")
-    end
-
-    @testset "solve (exact)" begin
-        solution_filename_a = tempname()
-        solution_filename_b = tempname()
-        solution = RELOG.solve("$(pwd())/../instances/s1.json",
-                               output=solution_filename_a)
-
-        @test isfile(solution_filename_a)
-                               
-        RELOG.write(solution, solution_filename_b)
-        @test isfile(solution_filename_b)
-        
-        @test "Costs" in keys(solution)
-        @test "Fixed operating (\$)" in keys(solution["Costs"])
-        @test "Transportation (\$)" in keys(solution["Costs"])
-        @test "Variable operating (\$)" in keys(solution["Costs"])
-        @test "Total (\$)" in keys(solution["Costs"])
-
-        @test "Plants" in keys(solution)
-        @test "F1" in keys(solution["Plants"])
-        @test "F2" in keys(solution["Plants"])
-        @test "F3" in keys(solution["Plants"])
-        @test "F4" in keys(solution["Plants"])
-    end
-    
-    
-    @testset "solve (heuristic)" begin
-        # Should not crash
-        solution = RELOG.solve("$(pwd())/../instances/s1.json", heuristic=true)
-    end
-
-    @testset "infeasible solve" begin
-        json = JSON.parsefile("$(pwd())/../instances/s1.json")
-        for (location_name, location_dict) in json["products"]["P1"]["initial amounts"]
-            location_dict["amount (tonne)"] *= 1000
-        end
-        RELOG.solve(RELOG.parse(json))
-    end
-    
-    @testset "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
-end
--- a/test/reports_test.jl
+++ b/test/reports_test.jl
@@ -4,38 +4,16 @@

 using RELOG, JSON, GZip

-load_json_gz(filename) = JSON.parse(GZip.gzopen(filename))
-
-# function check(func, expected_csv_filename::String)
-#     solution = load_json_gz("fixtures/nimh_solution.json.gz")
-#     actual_csv_filename = tempname()
-#     func(solution, actual_csv_filename)
-#     @test isfile(actual_csv_filename)
-#     if readlines(actual_csv_filename) != readlines(expected_csv_filename)
-#         out_filename = replace(expected_csv_filename, ".csv" => "_actual.csv")
-#         @error "$func: Unexpected CSV contents: $out_filename"
-#         write(out_filename, read(actual_csv_filename))
-#         @test false
-#     end
-# end
-
@testset "Reports" begin
-#     @testset "from fixture" begin
-#         check(RELOG.write_plants_report, "fixtures/nimh_plants.csv")
-#         check(RELOG.write_plant_outputs_report, "fixtures/nimh_plant_outputs.csv")
-#         check(RELOG.write_plant_emissions_report, "fixtures/nimh_plant_emissions.csv")
-#         check(RELOG.write_transportation_report, "fixtures/nimh_transportation.csv")
-#         check(RELOG.write_transportation_emissions_report, "fixtures/nimh_transportation_emissions.csv")
-#     end
-    
    @testset "from solve" begin
        solution = RELOG.solve("$(pwd())/../instances/s1.json")
        tmp_filename = tempname()
        # The following should not crash
-        RELOG.write_plants_report(solution, tmp_filename)
-        RELOG.write_plant_outputs_report(solution, tmp_filename)
        RELOG.write_plant_emissions_report(solution, tmp_filename)
-        RELOG.write_transportation_report(solution, tmp_filename)
+        RELOG.write_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
--- a/test/runtests.jl
+++ b/test/runtests.jl
@@ -4,8 +4,18 @@
 using Test

@testset "RELOG" begin
-    include("instance_test.jl")
-    include("graph_test.jl")
-    include("model_test.jl")
+    @testset "Instance" begin
+        include("instance/compress_test.jl")
+        include("instance/geodb_test.jl")
+        include("instance/parse_test.jl")
+    end
+    @testset "Graph" begin
+        include("graph/build_test.jl")
+    end
+    @testset "Model" begin
+        include("model/build_test.jl")
+        include("model/solve_test.jl")
+        include("model/resolve_test.jl")
+    end
    include("reports_test.jl")
-end
+end
Author	SHA1	Message	Date
Alinson S Xavier	505e3a8e1e	Update CHANGELOG	2021-07-23 17:42:48 -05:00
Alinson S Xavier	d4fa75297f	Fix OrderedCollections version	2021-07-23 17:42:29 -05:00
Alinson S Xavier	881957d6b5	Implement resolve	2021-07-21 14:53:49 -05:00
Alinson S Xavier	86cf7f5bd9	Throw exception for infeasible models	2021-07-21 14:18:10 -05:00
Alinson S Xavier	a8c7047e2d	Add custom show function for Instance and Graph Without these functions, Julia 1.5 enters an infinite loop whenever it tries to generate a stack trace, so any error (such as a missing method) causes the program to hang, instead of an error message to appear.	2021-07-21 14:11:01 -05:00
Alinson S Xavier	099e0fae3a	Docs: Minor fixes to what-if analsis section	2021-07-21 14:07:00 -05:00
Alinson S Xavier	1b8f392852	Docs: Add description of resolve	2021-07-21 14:07:00 -05:00
Alinson S Xavier	7a95aa66f6	Update CHANGELOG	2021-07-21 11:49:54 -05:00
Alinson S Xavier	40d28c727a	Add products report	2021-07-16 11:25:40 -05:00
Alinson S Xavier	a9ac164833	Fix GeoDB download	2021-07-16 10:31:21 -05:00
Alinson S Xavier	e244ded51d	GH Actions: Add Julia 1.6, remove nightly	2021-07-16 10:18:10 -05:00
Alinson S Xavier	7180651cfa	Reformat source code	2021-07-16 10:15:41 -05:00
Alinson S Xavier	0c9465411f	Document GeoDB; remove unused code; minor fixes	2021-07-16 10:13:58 -05:00
Alinson S Xavier	658d5ddbdc	Add population to region; disable zip codes	2021-07-01 17:14:00 -05:00
Alinson S Xavier	399db41f86	Temporarily disable failing test	2021-07-01 16:13:38 -05:00
Alinson S Xavier	e407a53ecf	Download and join population	2021-07-01 16:10:55 -05:00
Alinson S Xavier	33ab4c5f76	GeoDB: Prepare for population	2021-07-01 14:56:08 -05:00
Alinson S Xavier	c9391dd299	Update JSONSchema	2021-07-01 14:56:08 -05:00
Alinson S Xavier	6c70d9acd5	GeoDB: Add 2018-us-zcta and us-state	2021-07-01 14:56:08 -05:00
Alinson S Xavier	339255bf9b	Enable geodb in input files	2021-07-01 14:56:08 -05:00
Alinson S Xavier	ca187fe78e	Implement geodb.jl	2021-07-01 14:56:08 -05:00
Alinson S. Xavier	c256cd8b75	Update CHANGELOG.md	2021-06-25 06:16:20 -05:00
Alinson S. Xavier	05d48e2cbf	Update tagbot.yml	2021-06-25 06:13:27 -05:00
Alinson S Xavier	9446b1921d	Add tagbot.yml	2021-06-22 11:10:15 -05:00
Alinson S Xavier	1b0cc141bb	Remove Manifest.toml from repository	2021-06-22 11:00:11 -05:00
Alinson S Xavier	a333ab0b04	Remove unused code and test resources	2021-06-22 10:58:46 -05:00
Alinson S Xavier	630ae49d4a	Replace Array by Vector	2021-06-22 10:53:40 -05:00
Alinson S Xavier	9df416ed75	Split files	2021-06-22 10:50:11 -05:00
Alinson S Xavier	849f902562	Reformat code	2021-06-22 10:21:17 -05:00
Alinson S Xavier	1990563476	Remove dotdict	2021-06-22 10:20:40 -05:00
Alinson S Xavier	7e783c8b91	Replace ManufacturingModel by JuMP.Model	2021-06-22 10:19:31 -05:00
Alinson S Xavier	93cc6fbf32	Remove model.eqs	2021-06-22 10:10:48 -05:00
Alinson S Xavier	a7938b7260	Remove model.vars	2021-06-22 10:08:01 -05:00
Alinson S Xavier	56ef1f7bc2	Update dependencies	2021-06-22 10:07:40 -05:00
Alinson S Xavier	b00b24ffbc	Reformat source code; set up lint GH Action	2021-06-22 09:49:45 -05:00
Alinson S. Xavier	823db2838b	GH Actions: Run tests daily	2021-06-22 09:41:01 -05:00