Fix some merge issues

Merge branch 'dev' into akazachk/formulations
Implement multiple formulations
2025-12-06 08:18:51 -06:00 · 2020-11-20 12:17:59 -06:00 · 2020-11-20 10:55:48 -06:00 · 2020-11-20 10:52:23 -06:00
340 changed files with 7054 additions and 7433 deletions
--- a/.JuliaFormatter.toml
+++ b/.JuliaFormatter.toml
@@ -1,5 +0,0 @@
-always_for_in = true
-always_use_return = true
-margin = 80
-remove_extra_newlines = true
-short_to_long_function_def = true
--- a/.github/ISSUE_TEMPLATE/bug_report.md
+++ b/.github/ISSUE_TEMPLATE/bug_report.md
@@ -1,25 +0,0 @@
---
-name: Bug report
-about: Something is broken in the package
-title: ''
-labels: ''
-assignees: ''
-
---
-
-## Description
-
-A clear and concise description of what the bug is.
-
-## Steps to Reproduce
-
-Please describe how can the developers reproduce the problem in their own computers. Code snippets and sample input files are specially helpful. For example:
-
-1. Install the package
-2. Run the code below with the attached input file...
-3. The following error appears...
-
-## System Information
- - Operating System: [e.g. Ubuntu 20.04]
- - Julia version: [e.g. 1.4]
- - Package version: [e.g. 0.0.1]
--- a/.github/ISSUE_TEMPLATE/config.yml
+++ b/.github/ISSUE_TEMPLATE/config.yml
@@ -1,8 +0,0 @@
-blank_issues_enabled: false
-contact_links:
-  - name: Feature Request
-    url: https://github.com/ANL-CEEESA/UnitCommitment.jl/discussions/categories/feature-requests
-    about:  Submit ideas for new features and small enhancements
-  - name: Help & FAQ
-    url: https://github.com/ANL-CEEESA/UnitCommitment.jl/discussions/categories/help-faq
-    about: Ask questions about the package and get help from the community
--- a/.github/workflows/benchmark.yml
+++ b/.github/workflows/benchmark.yml
@@ -0,0 +1,28 @@
+name: Benchmark
+on: push
+jobs:
+  benchmark:
+    runs-on: [self-hosted, benchmark]
+    if: "contains(github.event.head_commit.message, '[benchmark]')"
+    timeout-minutes: 10080
+    steps:
+    - uses: actions/checkout@v1
+    - name: Benchmark
+      run: |
+        julia --project=@. -e 'using Pkg; Pkg.instantiate()'
+        make build/sysimage.so
+        make -C benchmark clean
+        make -C benchmark -kj4
+        make -C benchmark tables
+        make -C benchmark clean-mps clean-sol
+    - name: Upload logs
+      uses: actions/upload-artifact@v2
+      with:
+        name: Logs
+        path: benchmark/results/*
+    - name: Upload tables & charts
+      uses: actions/upload-artifact@v2
+      with:
+        name: Tables
+        path: benchmark/tables/*
+
--- a/.github/workflows/lint.yml
+++ b/.github/workflows/lint.yml
@@ -1,28 +0,0 @@
-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)
-          format("benchmark", 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/test.yml
+++ b/.github/workflows/test.yml
@@ -1,35 +1,28 @@
-name: Build & Test
+name: Tests
 on:
  push:
+    paths:
+      - '**.jl'
+      - '**.toml'
  pull_request:
-  schedule:
-    - cron: '45 10 * * *'
+    paths:
+      - '**.jl'
+      - '**.toml'
 jobs:
  test:
-    name: Julia ${{ matrix.version }} - ${{ matrix.os }} - ${{ matrix.arch }}
    runs-on: ${{ matrix.os }}
    strategy:
      matrix:
-        version: ['1.6', '1.7', '1.8', '1.9']
-        os:
-          - ubuntu-latest
-        arch:
-          - x64
+        julia-version: ['1.3', '1.4', '1']
+        julia-arch: [x64, x86]
+        os: [ubuntu-latest, windows-latest, macOS-latest]
+        exclude:
+          - os: macOS-latest
+            julia-arch: x86
    steps:
      - uses: actions/checkout@v2
-      - uses: julia-actions/setup-julia@v1
+      - uses: julia-actions/setup-julia@latest
        with:
-          version: ${{ matrix.version }}
-          arch: ${{ matrix.arch }}
-      - name: Run tests
-        shell: julia --color=yes --project=test {0}
-        run: |
-          using Pkg
-          Pkg.develop(path=".")
-          Pkg.update()
-          using UnitCommitmentT
-          try
-            runtests()
-          catch
-            exit(1)
-          end
+          version: ${{ matrix.julia-version }}
+      - uses: julia-actions/julia-buildpkg@latest
+      - uses: julia-actions/julia-runtest@latest
--- a/.gitignore
+++ b/.gitignore
@@ -1,38 +1,16 @@
 *.bak
 *.gz
-*.ipynb
 *.lastrun
-*.mps
 *.so
-*/Manifest.toml
-.AppleDB
-.AppleDesktop
-.AppleDouble
-.DS_Store
-.DocumentRevisions-V100
-.LSOverride
-.Spotlight-V100
-.TemporaryItems
-.Trashes
-.VolumeIcon.icns
-._*
-.apdisk
-.com.apple.timemachine.donotpresent
-.fseventsd
+*.mps
+*.ipynb
 .ipy*
-.vscode
-Icon
-Manifest.toml
-Network Trash Folder
-TODO.md
-Temporary Items
 benchmark/results
 benchmark/runs
 benchmark/tables
-benchmark/tmp.json
 build
-docs/_build
 instances/**/*.json
 instances/_source
 local
 notebooks
+TODO.md
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,75 +1,11 @@
-# Changelog
+# UnitCommitment.jl

-All notable changes to this project will be documented in this file.
+### Version 0.1.1 (Nov 16, 2020)

- 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`.
+* Fixes to MATLAB and PGLIB-UC instances
+* Add OR-LIB and Tejada19 instances
+* Improve documentation

-[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
+### Version 0.1.0 (Nov 6, 2020)

-## [0.3.0] - 2022-07-18
-### Added
- Add support for multiple reserve products and zonal reserves.
- Add flexiramp reserve products, following WanHob2016's formulation (@oyurdakul, #21).
- Add 365 variations for each MATPOWER instance, corresponding to each day of the year.
-
-### Changed
- To support multiple/zonal reserves, the input data format has been modified as follows:
-    - In `Generators`, replace `Provides spinning reserves?` by `Reserve eligibility`
-    - In `Parameters`, remove `Reserve shortfall penalty`
-    - Revise `Reserves` section
- To allow new versions of UnitCommitment.jl to read old instance files, a new required field `Version` has been added to the `Parameters` section. To load v0.2 files in v0.3, please add `{"Parameters":{"Version":"0.2"}}` to the file.
- Benchmark test cases are now downloaded on-the-fly as needed, instead of being stored in our GitHub repository. Test cases can also be directly downloaded from: https://axavier.org/UnitCommitment.jl/
-
-
-## [0.2.2] - 2021-07-21
-### Fixed
- Fix small bug in validation scripts related to startup costs
- Fix duplicated startup constraints (@mtanneau, #12)
-
-## [0.2.1] - 2021-06-02
-### Added
- Add multiple ramping formulations (ArrCon2000, MorLatRam2013, DamKucRajAta2016, PanGua2016)
- Add multiple piecewise-linear costs formulations (Garver1962, CarArr2006, KnuOstWat2018)
- Allow benchmark scripts to compare multiple formulations
-
-## [0.2.0] - 2021-05-28
-### Added
- Add sub-hourly unit commitment.
- Add `UnitCommitment.write(filename, solution)`.
- Add current mathematical formulation to the documentation.
-
-### Changed
- Rename "Time (h)" parameter to "Time horizon (h)".
- Rename `UnitCommitment.get_solution` to `UnitCommitment.solution`, for better
-  consistency with JuMP style.
- Add an underscore to the name of all functions that do not appear in the
-  documentation (e.g. `something` becomes `_something`) These functions are not
-  part of the public API and may change without notice, even in PATCH releases.
- The function `UnitCommitment.build_model` now returns a plain JuMP model. The
-  struct `UnitCommitmentModel` has been completely removed. Accessing model
-  elements can now be accomplished as follows:
-    - `model.vars.x[idx]` becomes `model[:x][idx]`
-    - `model.eqs.y[idx]` becomes `model[:eq_y][idx]`
-    - `model.expr.z[idx]` becomes `model[:expr_z][idx]`
-    - `model.obj` becomes `model[:obj]`
-    - `model.isf` becomes `model[:isf]`
-    - `model.lodf` becomes `model[:lodf]`
-
-### Fixed
- Properly validate solutions with price-sensitive loads.
-
-## [0.1.1] - 2020-11-16
-### Added
- Add OR-LIB and Tejada19 instances.
- Improve documentation.
-
-## Fixed
- Fixes to MATLAB and PGLIB-UC instances.
-
-## [0.1.0] - 2020-11-06
- Initial public release.
+* Initial public release
--- a/LICENSE.md
+++ b/LICENSE.md
@@ -1,4 +1,4 @@
-Copyright © 2020-2022, UChicago Argonne, LLC
+Copyright © 2020, UChicago Argonne, LLC

 All Rights Reserved

--- a/26
+++ b/26
@@ -2,10 +2,28 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.

-VERSION := 0.3
+JULIA := julia --color=yes --project=@.
+MKDOCS := ~/.local/bin/mkdocs
+VERSION := 0.1
+
+build/sysimage.so: src/sysimage.jl Project.toml Manifest.toml
+	mkdir -p build
+	mkdir -p benchmark/results/test
+	cd benchmark; $(JULIA) --trace-compile=../build/precompile.jl run.jl test/case14.1.sol.json
+	$(JULIA) src/sysimage.jl
+
+clean:
+	rm -rf build/*

 docs:
-	cd docs; julia --project=. make.jl; cd ..
-	rsync -avP --delete-after docs/build/ ../docs/$(VERSION)/
+	$(MKDOCS) build -d ../docs/$(VERSION)/
+	rm ../docs/$(VERSION)/*.ipynb
 	
-.PHONY: docs
+install-deps-docs:
+	pip install --user mkdocs mkdocs-cinder python-markdown-math
+
+test: build/sysimage.so
+	@echo Running tests...
+	$(JULIA) --sysimage build/sysimage.so -e 'using Pkg; Pkg.test("UnitCommitment")' | tee build/test.log
+
+.PHONY: docs test
--- a/Manifest.toml
+++ b/Manifest.toml
@@ -0,0 +1,367 @@
+# This file is machine-generated - editing it directly is not advised
+
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+
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+
+[[OrderedCollections]]
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+
+[[Osi_jll]]
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+
+[[Parsers]]
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+
+[[Pkg]]
+deps = ["Dates", "LibGit2", "Libdl", "Logging", "Markdown", "Printf", "REPL", "Random", "SHA", "UUIDs"]
+uuid = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
+
+[[Printf]]
+deps = ["Unicode"]
+uuid = "de0858da-6303-5e67-8744-51eddeeeb8d7"
+
+[[REPL]]
+deps = ["InteractiveUtils", "Markdown", "Sockets"]
+uuid = "3fa0cd96-eef1-5676-8a61-b3b8758bbffb"
+
+[[Random]]
+deps = ["Serialization"]
+uuid = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
+
+[[SHA]]
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+
+[[Serialization]]
+uuid = "9e88b42a-f829-5b0c-bbe9-9e923198166b"
+
+[[SharedArrays]]
+deps = ["Distributed", "Mmap", "Random", "Serialization"]
+uuid = "1a1011a3-84de-559e-8e89-a11a2f7dc383"
+
+[[Sockets]]
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+
+[[SparseArrays]]
+deps = ["LinearAlgebra", "Random"]
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+
+[[SpecialFunctions]]
+deps = ["OpenSpecFun_jll"]
+git-tree-sha1 = "d8d8b8a9f4119829410ecd706da4cc8594a1e020"
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+
+[[StaticArrays]]
+deps = ["LinearAlgebra", "Random", "Statistics"]
+git-tree-sha1 = "da4cf579416c81994afd6322365d00916c79b8ae"
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+
+[[Statistics]]
+deps = ["LinearAlgebra", "SparseArrays"]
+uuid = "10745b16-79ce-11e8-11f9-7d13ad32a3b2"
+
+[[Test]]
+deps = ["Distributed", "InteractiveUtils", "Logging", "Random"]
+uuid = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+
+[[TranscodingStreams]]
+deps = ["Random", "Test"]
+git-tree-sha1 = "7c53c35547de1c5b9d46a4797cf6d8253807108c"
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+
+[[UUIDs]]
+deps = ["Random", "SHA"]
+uuid = "cf7118a7-6976-5b1a-9a39-7adc72f591a4"
+
+[[Unicode]]
+uuid = "4ec0a83e-493e-50e2-b9ac-8f72acf5a8f5"
+
+[[ZipFile]]
+deps = ["Libdl", "Printf", "Zlib_jll"]
+git-tree-sha1 = "c3a5637e27e914a7a445b8d0ad063d701931e9f7"
+uuid = "a5390f91-8eb1-5f08-bee0-b1d1ffed6cea"
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+
+[[Zlib_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"]
+git-tree-sha1 = "320228915c8debb12cb434c59057290f0834dbf6"
+uuid = "83775a58-1f1d-513f-b197-d71354ab007a"
+version = "1.2.11+18"
--- a/Project.toml
+++ b/Project.toml
@@ -2,29 +2,34 @@ name = "UnitCommitment"
 uuid = "64606440-39ea-11e9-0f29-3303a1d3d877"
 authors = ["Santos Xavier, Alinson <axavier@anl.gov>"]
 repo = "https://github.com/ANL-CEEESA/UnitCommitment.jl"
-version = "0.3.0"
+version = "0.1.1"

 [deps]
 DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
-Distributed = "8ba89e20-285c-5b6f-9357-94700520ee1b"
-Distributions = "31c24e10-a181-5473-b8eb-7969acd0382f"
 GZip = "92fee26a-97fe-5a0c-ad85-20a5f3185b63"
 JSON = "682c06a0-de6a-54ab-a142-c8b1cf79cde6"
 JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 Logging = "56ddb016-857b-54e1-b83d-db4d58db5568"
 MathOptInterface = "b8f27783-ece8-5eb3-8dc8-9495eed66fee"
+OrderedCollections = "bac558e1-5e72-5ebc-8fee-abe8a469f55d"
 PackageCompiler = "9b87118b-4619-50d2-8e1e-99f35a4d4d9d"
 Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
-Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"

 [compat]
+Cbc = "0.7"
 DataStructures = "0.18"
-Distributions = "0.25"
 GZip = "0.5"
 JSON = "0.21"
-JuMP = "1"
-MathOptInterface = "1"
+JuMP = "0.21"
+MathOptInterface = "0.9"
 PackageCompiler = "1"
 julia = "1"
+
+[extras]
+Cbc = "9961bab8-2fa3-5c5a-9d89-47fab24efd76"
+Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+
+[targets]
+test = ["Cbc", "Test"]
--- a/README.md
+++ b/README.md
@@ -1,147 +1,44 @@
-<h1 align="center">UnitCommitment.jl</h1>
-<p align="center">
-  <a href="https://github.com/ANL-CEEESA/UnitCommitment.jl/actions?query=workflow%3ATest+branch%3Adev">
-    <img src="https://github.com/iSoron/UnitCommitment.jl/workflows/Tests/badge.svg"></img>
-  </a>
-  <a href="https://doi.org/10.5281/zenodo.4269874">
-    <img src="https://zenodo.org/badge/doi/10.5281/zenodo.4269874.svg" alt="DOI"></img>
-  </a>
-  <a href="https://github.com/ANL-CEEESA/UnitCommitment.jl/releases/">
-    <img src="https://img.shields.io/github/v/release/ANL-CEEESA/UnitCommitment.jl?include_prereleases&label=pre-release">
-  </a>
-  <a href="https://github.com/ANL-CEEESA/UnitCommitment.jl/discussions">
-    <img src="https://img.shields.io/badge/GitHub-Discussions-%23fc4ebc" />
-  </a>
-</p>
+<a href="https://github.com/ANL-CEEESA/UnitCommitment.jl/actions?query=workflow%3ATest+branch%3Adev"><img src="https://github.com/iSoron/UnitCommitment.jl/workflows/Tests/badge.svg"></img></a>
+<a href="https://github.com/ANL-CEEESA/UnitCommitment.jl/actions?query=workflow%3ABenchmark+branch%3Adev+is%3Asuccess"><img src="https://github.com/iSoron/UnitCommitment.jl/workflows/Benchmark/badge.svg"></img></a>
+<a href="https://doi.org/10.5281/zenodo.4269874"><img src="https://zenodo.org/badge/doi/10.5281/zenodo.4269874.svg" alt="DOI"></a>

-**UnitCommitment.jl** (UC.jl) is an optimization package for the Security-Constrained Unit Commitment Problem (SCUC), a fundamental optimization problem in power systems used, for example, to clear the day-ahead electricity markets. The package provides benchmark instances for the problem and Julia/JuMP implementations of state-of-the-art mixed-integer programming formulations.

-## Package Components
+# UnitCommitment.jl

-* **Data Format:** The package proposes an extensible and fully-documented JSON-based data format for SCUC, developed in collaboration with Independent System Operators (ISOs), which describes the most important aspects of the problem. The format supports the most common generator characteristics (including ramping, piecewise-linear production cost curves and time-dependent startup costs), as well as operating reserves, price-sensitive loads, transmission networks and contingencies.
-* **Benchmark Instances:** The package provides a diverse collection of large-scale benchmark instances collected from the literature, converted into a common data format, and extended using data-driven methods to make them more challenging and realistic.
-* **Model Implementation**: The package provides Julia/JuMP implementations of state-of-the-art formulations and solution methods for SCUC, including multiple ramping formulations ([ArrCon2000][ArrCon2000], [MorLatRam2013][MorLatRam2013], [DamKucRajAta2016][DamKucRajAta2016], [PanGua2016][PanGua2016]), multiple piecewise-linear costs formulations ([Gar1962][Gar1962], [CarArr2006][CarArr2006], [KnuOstWat2018][KnuOstWat2018]) and contingency screening methods ([XavQiuWanThi2019][XavQiuWanThi2019]). Our goal is to keep these implementations up-to-date as new methods are proposed in the literature.
+**UnitCommitment.jl** (UC.jl) is an optimization package for the Security-Constrained Unit Commitment Problem (SCUC), a fundamental optimization problem in power systems used, for example, to clear the day-ahead electricity markets. The package provides benchmark instances for the problem and JuMP implementations of state-of-the-art mixed-integer programming formulations.
+
+### Package Components
+
+* **Data Format:** The package proposes an extensible and fully-documented JSON-based data specification format for SCUC, developed in collaboration with Independent System Operators (ISOs), which describes the most important aspects of the problem. The format supports all the most common generator characteristics (including ramping, piecewise-linear production cost curves and time-dependent startup costs), as well as operating reserves, price-sensitive loads, transmission networks and contingencies.
+* **Benchmark Instances:** The package provides a diverse collection of large-scale benchmark instances collected from the literature and extended to make them more challenging and realistic.
+* **Model Implementation**: The package provides a Julia/JuMP implementation of state-of-the-art formulations and solution methods for SCUC. Our goal is to keep this implementation up-to-date, as new methods are proposed in the literature.
 * **Benchmark Tools:** The package provides automated benchmark scripts to accurately evaluate the performance impact of proposed code changes.

-[ArrCon2000]: https://doi.org/10.1109/59.871739
-[CarArr2006]: https://doi.org/10.1109/TPWRS.2006.876672
-[DamKucRajAta2016]: https://doi.org/10.1007/s10107-015-0919-9
-[Gar1962]: https://doi.org/10.1109/AIEEPAS.1962.4501405
-[KnuOstWat2018]: https://doi.org/10.1109/TPWRS.2017.2783850
-[MorLatRam2013]: https://doi.org/10.1109/TPWRS.2013.2251373
-[PanGua2016]: https://doi.org/10.1287/opre.2016.1520
-[XavQiuWanThi2019]: https://doi.org/10.1109/TPWRS.2019.2892620
+### Documentation

-## Sample Usage
+* [Usage](https://anl-ceeesa.github.io/UnitCommitment.jl/0.1/usage/)
+* [Data Format](https://anl-ceeesa.github.io/UnitCommitment.jl/0.1/format/)
+* [Instances](https://anl-ceeesa.github.io/UnitCommitment.jl/0.1/instances/)

-```julia
-using Cbc
-using JuMP
-using UnitCommitment
-
-import UnitCommitment:
-    Formulation,
-    KnuOstWat2018,
-    MorLatRam2013,
-    ShiftFactorsFormulation
-
-# Read benchmark instance
-instance = UnitCommitment.read_benchmark(
-    "matpower/case118/2017-02-01",
-)
-
-# Construct model (using state-of-the-art defaults)
-model = UnitCommitment.build_model(
-    instance = instance,
-    optimizer = Cbc.Optimizer,
-)
-
-# Construct model (using customized formulation)
-model = UnitCommitment.build_model(
-    instance = instance,
-    optimizer = Cbc.Optimizer,
-    formulation = Formulation(
-        pwl_costs = KnuOstWat2018.PwlCosts(),
-        ramping = MorLatRam2013.Ramping(),
-        startup_costs = MorLatRam2013.StartupCosts(),
-        transmission = ShiftFactorsFormulation(
-            isf_cutoff = 0.005,
-            lodf_cutoff = 0.001,
-        ),
-    ),
-)
-
-# Modify the model (e.g. add custom constraints)
-@constraint(
-    model,
-    model[:is_on]["g3", 1] + model[:is_on]["g4", 1] <= 1,
-)
-
-# Solve model
-UnitCommitment.optimize!(model)
-
-# Extract solution
-solution = UnitCommitment.solution(model)
-UnitCommitment.write("/tmp/output.json", solution)
-```
-
-## Documentation
-
-1. [Usage](https://anl-ceeesa.github.io/UnitCommitment.jl/0.3/usage/)
-2. [Data Format](https://anl-ceeesa.github.io/UnitCommitment.jl/0.3/format/)
-3. [Instances](https://anl-ceeesa.github.io/UnitCommitment.jl/0.3/instances/)
-4. [JuMP Model](https://anl-ceeesa.github.io/UnitCommitment.jl/0.3/model/)
-5. [API Reference](https://anl-ceeesa.github.io/UnitCommitment.jl/0.3/api/)
-
-## Authors
-* **Alinson S. Xavier** (Argonne National Laboratory)
-* **Aleksandr M. Kazachkov** (University of Florida)
-* **Ogün Yurdakul** (Technische Universität Berlin)
-* **Jun He** (Purdue University)
+### Authors
+* **Alinson Santos Xavier** (Argonne National Laboratory)
 * **Feng Qiu** (Argonne National Laboratory)

-## Acknowledgments
+### Acknowledgments

-* We would like to thank **Yonghong Chen** (Midcontinent Independent System Operator), **Feng Pan** (Pacific Northwest National Laboratory) for valuable feedback on early versions of this package.
+* We would like to thank **Aleksandr M. Kazachkov** (University of Florida), **Yonghong Chen** (Midcontinent Independent System Operator), **Feng Pan** (Pacific Northwest National Laboratory) for valuable feedback on early versions of this package.

-* Based upon work supported by **Laboratory Directed Research and Development** (LDRD) funding from Argonne National Laboratory, provided by the Director, Office of Science, of the U.S. Department of Energy under Contract No. DE-AC02-06CH11357
+* Based upon work supported by **Laboratory Directed Research and Development** (LDRD) funding from Argonne National Laboratory, provided by the Director, Office of Science, of the U.S. Department of Energy under Contract No. DE-AC02-06CH11357.

-* Based upon work supported by the **U.S. Department of Energy Advanced Grid Modeling Program** under Grant DE-OE0000875.
+### Citing

-## Citing
+If you use UnitCommitment.jl in your research, we request that you cite the package as follows:

-If you use UnitCommitment.jl in your research (instances, models or algorithms), we kindly request that you cite the package as follows:
+* **Alinson S. Xavier, Feng Qiu**. "UnitCommitment.jl: A Julia/JuMP Optimization Package for Security-Constrained Unit Commitment". Zenodo (2020). [DOI: 10.5281/zenodo.4269874](https://doi.org/10.5281/zenodo.4269874).

-* **Alinson S. Xavier, Aleksandr M. Kazachkov, Ogün Yurdakul, Feng Qiu**. "UnitCommitment.jl: A Julia/JuMP Optimization Package for Security-Constrained Unit Commitment (Version 0.3)". Zenodo (2022). [DOI: 10.5281/zenodo.4269874](https://doi.org/10.5281/zenodo.4269874).
+If you make use of the provided instances files, we request that you additionally cite the original sources, as described in the [instances page](https://anl-ceeesa.github.io/UnitCommitment.jl/0.1/instances/).

-If you use the instances, we additionally request that you cite the original sources, as described in the documentation.
+### License

-## License
-
-```text
-UnitCommitment.jl: A Julia/JuMP Optimization Package for Security-Constrained Unit Commitment
-Copyright © 2020-2022, UChicago Argonne, LLC. All Rights Reserved.
-
-Redistribution and use in source and binary forms, with or without modification, are permitted
-provided that the following conditions are met:
-
-1. Redistributions of source code must retain the above copyright notice, this list of
-   conditions and the following disclaimer.
-2. Redistributions in binary form must reproduce the above copyright notice, this list of
-   conditions and the following disclaimer in the documentation and/or other materials provided
-   with the distribution.
-3. Neither the name of the copyright holder nor the names of its contributors may be used to
-   endorse or promote products derived from this software without specific prior written
-   permission.
-
-THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR
-IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY
-AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR
-CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
-CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
-SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
-THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
-OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
-POSSIBILITY OF SUCH DAMAGE.
-```
+Released under the modified BSD license. See `LICENSE.md` for more details.

--- a/benchmark/Makefile
+++ b/benchmark/Makefile
@@ -0,0 +1,327 @@
+# UnitCommitment.jl: Optimization Package for Security-Constrained Unit Commitment
+# Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+# Released under the modified BSD license. See COPYING.md for more details.
+
+SHELL := /bin/bash
+JULIA := julia --project=. --sysimage ../build/sysimage.so
+TIMESTAMP := $(shell date "+%Y-%m-%d %H:%M")
+SRC_FILES := $(wildcard ../src/*.jl)
+DEST := .
+FORMULATION := tight
+results_dir := results_$(FORMULATION)
+
+INSTANCES_PGLIB := \
+        pglib-uc/ca/2014-09-01_reserves_0 \
+        pglib-uc/ca/2014-09-01_reserves_1 \
+        pglib-uc/ca/2015-03-01_reserves_0 \
+        pglib-uc/ca/2015-06-01_reserves_0 \
+        pglib-uc/ca/Scenario400_reserves_1 \
+        pglib-uc/ferc/2015-01-01_lw \
+        pglib-uc/ferc/2015-05-01_lw \
+        pglib-uc/ferc/2015-07-01_hw \
+        pglib-uc/ferc/2015-10-01_lw \
+        pglib-uc/ferc/2015-12-01_lw \
+        pglib-uc/rts_gmlc/2020-04-03 \
+        pglib-uc/rts_gmlc/2020-09-20 \
+        pglib-uc/rts_gmlc/2020-10-27 \
+        pglib-uc/rts_gmlc/2020-11-25 \
+        pglib-uc/rts_gmlc/2020-12-23
+
+INSTANCES_MATPOWER := \
+	matpower/case118/2017-02-01 \
+	matpower/case118/2017-08-01 \
+	matpower/case300/2017-02-01 \
+	matpower/case300/2017-08-01 \
+	matpower/case1354pegase/2017-02-01 \
+	matpower/case1888rte/2017-02-01 \
+	matpower/case1951rte/2017-08-01 \
+	matpower/case2848rte/2017-02-01 \
+	matpower/case2868rte/2017-08-01 \
+	matpower/case3375wp/2017-08-01 \
+	matpower/case6468rte/2017-08-01 \
+	matpower/case6515rte/2017-08-01
+
+INSTANCES_INFORMS1 := \
+  matpower/case1888rte/2017-01-01 \
+  matpower/case1888rte/2017-01-02 \
+  matpower/case1888rte/2017-01-03 \
+  matpower/case1888rte/2017-01-04 \
+  matpower/case1888rte/2017-01-05 \
+  matpower/case1888rte/2017-01-06 \
+  matpower/case1888rte/2017-01-07 \
+  matpower/case1888rte/2017-01-08 \
+  matpower/case1888rte/2017-01-09 \
+  matpower/case1888rte/2017-01-10 \
+  matpower/case1888rte/2017-01-11 \
+  matpower/case1888rte/2017-01-12 \
+  matpower/case1888rte/2017-01-13 \
+  matpower/case1888rte/2017-01-14 \
+  matpower/case1888rte/2017-01-15 \
+  matpower/case1888rte/2017-01-16 \
+  matpower/case1888rte/2017-01-17 \
+  matpower/case1888rte/2017-01-18 \
+  matpower/case1888rte/2017-01-19 \
+  matpower/case1888rte/2017-01-20 \
+  matpower/case1888rte/2017-01-21 \
+  matpower/case1888rte/2017-01-22 \
+  matpower/case1888rte/2017-01-23 \
+  matpower/case1888rte/2017-01-24 \
+  matpower/case1888rte/2017-01-25 \
+  matpower/case1888rte/2017-01-26 \
+  matpower/case1888rte/2017-01-27 \
+  matpower/case1888rte/2017-01-28 \
+  matpower/case1888rte/2017-01-29 \
+  matpower/case1888rte/2017-01-30 \
+  matpower/case1888rte/2017-01-31 \
+  matpower/case1888rte/2017-02-01 \
+  matpower/case1888rte/2017-02-02 \
+  matpower/case1888rte/2017-02-03 \
+  matpower/case1888rte/2017-02-04 \
+  matpower/case1888rte/2017-02-05 \
+  matpower/case1888rte/2017-02-06 \
+  matpower/case1888rte/2017-02-07 \
+  matpower/case1888rte/2017-02-08 \
+  matpower/case1888rte/2017-02-09 \
+  matpower/case1888rte/2017-02-10 \
+  matpower/case1888rte/2017-02-11 \
+  matpower/case1888rte/2017-02-12 \
+  matpower/case1888rte/2017-02-13 \
+  matpower/case1888rte/2017-02-14 \
+  matpower/case1888rte/2017-02-15 \
+  matpower/case1888rte/2017-02-16 \
+  matpower/case1888rte/2017-02-17 \
+  matpower/case1888rte/2017-02-18 \
+  matpower/case1888rte/2017-02-19 \
+  matpower/case1888rte/2017-02-20 \
+  matpower/case1888rte/2017-02-21 \
+  matpower/case1888rte/2017-02-22 \
+  matpower/case1888rte/2017-02-23 \
+  matpower/case1888rte/2017-02-24 \
+  matpower/case1888rte/2017-02-25 \
+  matpower/case1888rte/2017-02-26 \
+  matpower/case1888rte/2017-02-27 \
+  matpower/case1888rte/2017-02-28 \
+  matpower/case1888rte/2017-03-01
+
+INSTANCES_INFORMS2 := \
+  matpower/case3375wp/2017-01-01 \
+  matpower/case3375wp/2017-01-02 \
+  matpower/case3375wp/2017-01-03 \
+  matpower/case3375wp/2017-01-04 \
+  matpower/case3375wp/2017-01-05 \
+  matpower/case3375wp/2017-01-06 \
+  matpower/case3375wp/2017-01-07 \
+  matpower/case3375wp/2017-01-08 \
+  matpower/case3375wp/2017-01-09 \
+  matpower/case3375wp/2017-01-10 \
+  matpower/case3375wp/2017-01-11 \
+  matpower/case3375wp/2017-01-12 \
+  matpower/case3375wp/2017-01-13 \
+  matpower/case3375wp/2017-01-14 \
+  matpower/case3375wp/2017-01-15 \
+  matpower/case3375wp/2017-01-16 \
+  matpower/case3375wp/2017-01-17 \
+  matpower/case3375wp/2017-01-18 \
+  matpower/case3375wp/2017-01-19 \
+  matpower/case3375wp/2017-01-20 \
+  matpower/case3375wp/2017-01-21 \
+  matpower/case3375wp/2017-01-22 \
+  matpower/case3375wp/2017-01-23 \
+  matpower/case3375wp/2017-01-24 \
+  matpower/case3375wp/2017-01-25 \
+  matpower/case3375wp/2017-01-26 \
+  matpower/case3375wp/2017-01-27 \
+  matpower/case3375wp/2017-01-28 \
+  matpower/case3375wp/2017-01-29 \
+  matpower/case3375wp/2017-01-30 \
+  matpower/case3375wp/2017-01-31 \
+  matpower/case3375wp/2017-02-01 \
+  matpower/case3375wp/2017-02-02 \
+  matpower/case3375wp/2017-02-03 \
+  matpower/case3375wp/2017-02-04 \
+  matpower/case3375wp/2017-02-05 \
+  matpower/case3375wp/2017-02-06 \
+  matpower/case3375wp/2017-02-07 \
+  matpower/case3375wp/2017-02-08 \
+  matpower/case3375wp/2017-02-09 \
+  matpower/case3375wp/2017-02-10 \
+  matpower/case3375wp/2017-02-11 \
+  matpower/case3375wp/2017-02-12 \
+  matpower/case3375wp/2017-02-13 \
+  matpower/case3375wp/2017-02-14 \
+  matpower/case3375wp/2017-02-15 \
+  matpower/case3375wp/2017-02-16 \
+  matpower/case3375wp/2017-02-17 \
+  matpower/case3375wp/2017-02-18 \
+  matpower/case3375wp/2017-02-19 \
+  matpower/case3375wp/2017-02-20 \
+  matpower/case3375wp/2017-02-21 \
+  matpower/case3375wp/2017-02-22 \
+  matpower/case3375wp/2017-02-23 \
+  matpower/case3375wp/2017-02-24 \
+  matpower/case3375wp/2017-02-25 \
+  matpower/case3375wp/2017-02-26 \
+  matpower/case3375wp/2017-02-27 \
+  matpower/case3375wp/2017-02-28 \
+  matpower/case3375wp/2017-03-01
+
+INSTANCES_INFORMS3 := \
+  matpower/case6468rte/2017-01-01 \
+  matpower/case6468rte/2017-01-02 \
+  matpower/case6468rte/2017-01-03 \
+  matpower/case6468rte/2017-01-04 \
+  matpower/case6468rte/2017-01-05 \
+  matpower/case6468rte/2017-01-06 \
+  matpower/case6468rte/2017-01-07 \
+  matpower/case6468rte/2017-01-08 \
+  matpower/case6468rte/2017-01-09 \
+  matpower/case6468rte/2017-01-10 \
+  matpower/case6468rte/2017-01-11 \
+  matpower/case6468rte/2017-01-12 \
+  matpower/case6468rte/2017-01-13 \
+  matpower/case6468rte/2017-01-14 \
+  matpower/case6468rte/2017-01-15 \
+  matpower/case6468rte/2017-01-16 \
+  matpower/case6468rte/2017-01-17 \
+  matpower/case6468rte/2017-01-18 \
+  matpower/case6468rte/2017-01-19 \
+  matpower/case6468rte/2017-01-20 \
+  matpower/case6468rte/2017-01-21 \
+  matpower/case6468rte/2017-01-22 \
+  matpower/case6468rte/2017-01-23 \
+  matpower/case6468rte/2017-01-24 \
+  matpower/case6468rte/2017-01-25 \
+  matpower/case6468rte/2017-01-26 \
+  matpower/case6468rte/2017-01-27 \
+  matpower/case6468rte/2017-01-28 \
+  matpower/case6468rte/2017-01-29 \
+  matpower/case6468rte/2017-01-30 \
+  matpower/case6468rte/2017-01-31 \
+  matpower/case6468rte/2017-02-01 \
+  matpower/case6468rte/2017-02-02 \
+  matpower/case6468rte/2017-02-03 \
+  matpower/case6468rte/2017-02-04 \
+  matpower/case6468rte/2017-02-05 \
+  matpower/case6468rte/2017-02-06 \
+  matpower/case6468rte/2017-02-07 \
+  matpower/case6468rte/2017-02-08 \
+  matpower/case6468rte/2017-02-09 \
+  matpower/case6468rte/2017-02-10 \
+  matpower/case6468rte/2017-02-11 \
+  matpower/case6468rte/2017-02-12 \
+  matpower/case6468rte/2017-02-13 \
+  matpower/case6468rte/2017-02-14 \
+  matpower/case6468rte/2017-02-15 \
+  matpower/case6468rte/2017-02-16 \
+  matpower/case6468rte/2017-02-17 \
+  matpower/case6468rte/2017-02-18 \
+  matpower/case6468rte/2017-02-19 \
+  matpower/case6468rte/2017-02-20 \
+  matpower/case6468rte/2017-02-21 \
+  matpower/case6468rte/2017-02-22 \
+  matpower/case6468rte/2017-02-23 \
+  matpower/case6468rte/2017-02-24 \
+  matpower/case6468rte/2017-02-25 \
+  matpower/case6468rte/2017-02-26 \
+  matpower/case6468rte/2017-02-27 \
+  matpower/case6468rte/2017-02-28 \
+  matpower/case6468rte/2017-03-01
+
+INSTANCES_TEST := \
+	test/case14
+
+#SAMPLES := 1 2 3
+SAMPLES := 1
+SOLUTIONS_MATPOWER := $(foreach s,$(SAMPLES),$(addprefix $(results_dir)/,$(addsuffix .$(s).sol.json,$(INSTANCES_MATPOWER))))
+SOLUTIONS_PGLIB := $(foreach s,$(SAMPLES),$(addprefix $(results_dir)/,$(addsuffix .$(s).sol.json,$(INSTANCES_PGLIB))))
+SOLUTIONS_INFORMS1 := $(foreach s,$(SAMPLES),$(addprefix $(results_dir)/,$(addsuffix .$(s).sol.json,$(INSTANCES_INFORMS1))))
+SOLUTIONS_INFORMS2 := $(foreach s,$(SAMPLES),$(addprefix $(results_dir)/,$(addsuffix .$(s).sol.json,$(INSTANCES_INFORMS2))))
+SOLUTIONS_INFORMS3 := $(foreach s,$(SAMPLES),$(addprefix $(results_dir)/,$(addsuffix .$(s).sol.json,$(INSTANCES_INFORMS3))))
+SOLUTIONS_TEST := $(foreach s,$(SAMPLES),$(addprefix $(results_dir)/,$(addsuffix .$(s).sol.json,$(INSTANCES_TEST))))
+
+.PHONY: tables save small large clean-mps matpower pglib informs1 informs2 informs3 test pglib orlib
+
+INSTANCES_ORLIB := \
+	or-lib/20_0_1_w \
+	or-lib/20_0_5_w \
+	or-lib/50_0_2_w \
+	or-lib/75_0_2_w \
+	or-lib/100_0_1_w \
+	or-lib/100_0_4_w \
+	or-lib/100_0_5_w \
+	or-lib/200_0_3_w \
+	or-lib/200_0_7_w \
+	or-lib/200_0_9_w
+
+INSTANCES_TEJADA19 := \
+	tejada19/UC_24h_290g \
+	tejada19/UC_24h_623g \
+	tejada19/UC_24h_959g \
+	tejada19/UC_24h_1577g \
+	tejada19/UC_24h_1888g \
+	tejada19/UC_168h_72g \
+	tejada19/UC_168h_86g \
+	tejada19/UC_168h_130g \
+	tejada19/UC_168h_131g \
+	tejada19/UC_168h_199g
+
+SOLUTIONS_ORLIB := $(foreach s,$(SAMPLES),$(addprefix $(results_dir)/,$(addsuffix .$(s).sol.json,$(INSTANCES_ORLIB))))
+SOLUTIONS_TEJADA19 := $(foreach s,$(SAMPLES),$(addprefix $(results_dir)/,$(addsuffix .$(s).sol.json,$(INSTANCES_TEJADA19))))
+
+all: matpower pglib orlib tejada19
+
+matpower: $(SOLUTIONS_MATPOWER)
+
+pglib: $(SOLUTIONS_PGLIB)
+
+informs1: $(SOLUTIONS_INFORMS1)
+informs2: $(SOLUTIONS_INFORMS2)
+informs3: $(SOLUTIONS_INFORMS3)
+
+test: $(SOLUTIONS_TEST)
+
+orlib: $(SOLUTIONS_ORLIB)
+
+tejada19: $(SOLUTIONS_TEJADA19)
+
+clean:
+	@rm -rf tables/benchmark* tables/compare* $(results_dir)
+    
+clean-mps:
+	@rm -fv $(results_dir)/*/*.mps.gz results/*/*/*.mps.gz
+
+clean-sol:
+	@rm -rf $(results_dir)/*/*.sol.* results/*/*/*.sol.*
+        
+save:
+	mkdir -p "runs/$(TIMESTAMP)"
+	rsync -avP $(results_dir) tables "runs/$(TIMESTAMP)/"
+
+results/%.sol.json: run.jl
+	@echo "run  $*"
+	@mkdir -p $(dir $(DEST)/$(results_dir)/$*)
+	@$(JULIA) run.jl $* default $(DEST)/$(results_dir) 2>&1 | cat > $(DEST)/$(results_dir)/$*.log
+	@echo "run  $* [done]"
+
+results_tight/%.sol.json: run.jl
+	@echo "run  $*"
+	@mkdir -p $(dir $(DEST)/$(results_dir)/$*)
+	@$(JULIA) run.jl $* tight $(DEST)/$(results_dir) 2>&1 | cat > $(DEST)/$(results_dir)/$*.log
+	@echo "run  $* [done]"
+
+results_default/%.sol.json: run.jl
+	@echo "run  $*"
+	@mkdir -p $(dir $(DEST)/$(results_dir)/$*)
+	@$(JULIA) run.jl $* default $(DEST)/$(results_dir) 2>&1 | cat > $(DEST)/$(results_dir)/$*.log
+	@echo "run  $* [done]"
+
+results_sparse/%.sol.json: run.jl
+	@echo "run  $*"
+	@mkdir -p $(dir $(DEST)/$(results_dir)/$*)
+	@$(JULIA) run.jl $* sparse $(DEST)/$(results_dir) 2>&1 | cat > $(DEST)/$(results_dir)/$*.log
+	@echo "run  $* [done]"
+
+tables:
+	@mkdir -p tables
+	@python scripts/table.py
+	#@python scripts/compare.py tables/reference.csv tables/benchmark.csv
--- a/benchmark/Manifest.toml
+++ b/benchmark/Manifest.toml
@@ -0,0 +1,389 @@
+# This file is machine-generated - editing it directly is not advised
+
+[[Artifacts]]
+deps = ["Pkg"]
+git-tree-sha1 = "c30985d8821e0cd73870b17b0ed0ce6dc44cb744"
+uuid = "56f22d72-fd6d-98f1-02f0-08ddc0907c33"
+version = "1.3.0"
+
+[[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 = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"]
+git-tree-sha1 = "c3598e525718abcc440f69cc6d5f60dda0a1b61e"
+uuid = "6e34b625-4abd-537c-b88f-471c36dfa7a0"
+version = "1.0.6+5"
+
+[[CEnum]]
+git-tree-sha1 = "215a9aa4a1f23fbd05b92769fdd62559488d70e9"
+uuid = "fa961155-64e5-5f13-b03f-caf6b980ea82"
+version = "0.4.1"
+
+[[Calculus]]
+deps = ["LinearAlgebra"]
+git-tree-sha1 = "f641eb0a4f00c343bbc32346e1217b86f3ce9dad"
+uuid = "49dc2e85-a5d0-5ad3-a950-438e2897f1b9"
+version = "0.5.1"
+
+[[Cbc]]
+deps = ["BinaryProvider", "CEnum", "Cbc_jll", "Libdl", "MathOptInterface", "SparseArrays"]
+git-tree-sha1 = "929d0500c50387e7ac7ae9956ca7d7ce5312c90d"
+uuid = "9961bab8-2fa3-5c5a-9d89-47fab24efd76"
+version = "0.7.1"
+
+[[Cbc_jll]]
+deps = ["Cgl_jll", "Clp_jll", "CoinUtils_jll", "CompilerSupportLibraries_jll", "Libdl", "OpenBLAS32_jll", "Osi_jll", "Pkg"]
+git-tree-sha1 = "16b8ffa56b3ded6b201aa2f50623f260448aa205"
+uuid = "38041ee0-ae04-5750-a4d2-bb4d0d83d27d"
+version = "2.10.3+4"
+
+[[Cgl_jll]]
+deps = ["Clp_jll", "CompilerSupportLibraries_jll", "Libdl", "Pkg"]
+git-tree-sha1 = "32be20ec1e4c40e5c5d1bbf949ba9918a92a7569"
+uuid = "3830e938-1dd0-5f3e-8b8e-b3ee43226782"
+version = "0.60.2+5"
+
+[[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"
+
+[[CompilerSupportLibraries_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"]
+git-tree-sha1 = "8e695f735fca77e9708e795eda62afdb869cbb70"
+uuid = "e66e0078-7015-5450-92f7-15fbd957f2ae"
+version = "0.3.4+0"
+
+[[DataStructures]]
+deps = ["InteractiveUtils", "OrderedCollections"]
+git-tree-sha1 = "88d48e133e6d3dd68183309877eac74393daa7eb"
+uuid = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
+version = "0.17.20"
+
+[[Dates]]
+deps = ["Printf"]
+uuid = "ade2ca70-3891-5945-98fb-dc099432e06a"
+
+[[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"
+
+[[DocStringExtensions]]
+deps = ["LibGit2", "Markdown", "Pkg", "Test"]
+git-tree-sha1 = "50ddf44c53698f5e784bbebb3f4b21c5807401b1"
+uuid = "ffbed154-4ef7-542d-bbb7-c09d3a79fcae"
+version = "0.8.3"
+
+[[Documenter]]
+deps = ["Base64", "Dates", "DocStringExtensions", "InteractiveUtils", "JSON", "LibGit2", "Logging", "Markdown", "REPL", "Test", "Unicode"]
+git-tree-sha1 = "fb1ff838470573adc15c71ba79f8d31328f035da"
+uuid = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
+version = "0.25.2"
+
+[[ForwardDiff]]
+deps = ["CommonSubexpressions", "DiffResults", "DiffRules", "NaNMath", "Random", "SpecialFunctions", "StaticArrays"]
+git-tree-sha1 = "1d090099fb82223abc48f7ce176d3f7696ede36d"
+uuid = "f6369f11-7733-5829-9624-2563aa707210"
+version = "0.10.12"
+
+[[GLPK]]
+deps = ["BinaryProvider", "CEnum", "GLPK_jll", "Libdl", "MathOptInterface"]
+git-tree-sha1 = "0984f1669480cdecd465458b4abf81b238fbfe50"
+uuid = "60bf3e95-4087-53dc-ae20-288a0d20c6a6"
+version = "0.14.2"
+
+[[GLPK_jll]]
+deps = ["GMP_jll", "Libdl", "Pkg"]
+git-tree-sha1 = "ccc855de74292e478d4278e3a6fdd8212f75e81e"
+uuid = "e8aa6df9-e6ca-548a-97ff-1f85fc5b8b98"
+version = "4.64.0+0"
+
+[[GMP_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"]
+git-tree-sha1 = "15abc5f976569a1c9d651aff02f7222ef305eb2a"
+uuid = "781609d7-10c4-51f6-84f2-b8444358ff6d"
+version = "6.1.2+6"
+
+[[GZip]]
+deps = ["Libdl"]
+git-tree-sha1 = "039be665faf0b8ae36e089cd694233f5dee3f7d6"
+uuid = "92fee26a-97fe-5a0c-ad85-20a5f3185b63"
+version = "0.5.1"
+
+[[Gurobi]]
+deps = ["CEnum", "Libdl", "MathOptInterface"]
+git-tree-sha1 = "de2015da3bffcf005ef51b78163e81bfb7b2301d"
+uuid = "2e9cd046-0924-5485-92f1-d5272153d98b"
+version = "0.9.2"
+
+[[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"
+
+[[JLLWrappers]]
+git-tree-sha1 = "c70593677bbf2c3ccab4f7500d0f4dacfff7b75c"
+uuid = "692b3bcd-3c85-4b1f-b108-f13ce0eb3210"
+version = "1.1.3"
+
+[[JSON]]
+deps = ["Dates", "Mmap", "Parsers", "Unicode"]
+git-tree-sha1 = "b34d7cef7b337321e97d22242c3c2b91f476748e"
+uuid = "682c06a0-de6a-54ab-a142-c8b1cf79cde6"
+version = "0.21.0"
+
+[[JSONSchema]]
+deps = ["HTTP", "JSON", "ZipFile"]
+git-tree-sha1 = "a9ecdbc90be216912a2e3e8a8e38dc4c93f0d065"
+uuid = "7d188eb4-7ad8-530c-ae41-71a32a6d4692"
+version = "0.3.2"
+
+[[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 = "6a8a2a625ab0dea913aba95c11370589e0239ff0"
+uuid = "1914dd2f-81c6-5fcd-8719-6d5c9610ff09"
+version = "0.5.6"
+
+[[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 = "5a1d631e0a9087d425e024d66b9c71e92e78fda8"
+uuid = "b8f27783-ece8-5eb3-8dc8-9495eed66fee"
+version = "0.9.17"
+
+[[MbedTLS]]
+deps = ["Dates", "MbedTLS_jll", "Random", "Sockets"]
+git-tree-sha1 = "1c38e51c3d08ef2278062ebceade0e46cefc96fe"
+uuid = "739be429-bea8-5141-9913-cc70e7f3736d"
+version = "1.0.3"
+
+[[MbedTLS_jll]]
+deps = ["Libdl", "Pkg"]
+git-tree-sha1 = "c0b1286883cac4e2b617539de41111e0776d02e8"
+uuid = "c8ffd9c3-330d-5841-b78e-0817d7145fa1"
+version = "2.16.8+0"
+
+[[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 = ["Artifacts", "CompilerSupportLibraries_jll", "JLLWrappers", "Libdl", "Pkg"]
+git-tree-sha1 = "19c33675cdeb572c1b17f96c492459d4f4958036"
+uuid = "656ef2d0-ae68-5445-9ca0-591084a874a2"
+version = "0.3.10+0"
+
+[[OpenSpecFun_jll]]
+deps = ["Artifacts", "CompilerSupportLibraries_jll", "JLLWrappers", "Libdl", "Pkg"]
+git-tree-sha1 = "9db77584158d0ab52307f8c04f8e7c08ca76b5b3"
+uuid = "efe28fd5-8261-553b-a9e1-b2916fc3738e"
+version = "0.5.3+4"
+
+[[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 = "3eee77c94646163f15bd8626acf494360897f890"
+uuid = "9b87118b-4619-50d2-8e1e-99f35a4d4d9d"
+version = "1.2.3"
+
+[[Parsers]]
+deps = ["Dates"]
+git-tree-sha1 = "6fa4202675c05ba0f8268a6ddf07606350eda3ce"
+uuid = "69de0a69-1ddd-5017-9359-2bf0b02dc9f0"
+version = "1.0.11"
+
+[[Pkg]]
+deps = ["Dates", "LibGit2", "Libdl", "Logging", "Markdown", "Printf", "REPL", "Random", "SHA", "UUIDs"]
+uuid = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
+
+[[Printf]]
+deps = ["Unicode"]
+uuid = "de0858da-6303-5e67-8744-51eddeeeb8d7"
+
+[[REPL]]
+deps = ["InteractiveUtils", "Markdown", "Sockets"]
+uuid = "3fa0cd96-eef1-5676-8a61-b3b8758bbffb"
+
+[[Random]]
+deps = ["Serialization"]
+uuid = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
+
+[[Requires]]
+deps = ["UUIDs"]
+git-tree-sha1 = "28faf1c963ca1dc3ec87f166d92982e3c4a1f66d"
+uuid = "ae029012-a4dd-5104-9daa-d747884805df"
+version = "1.1.0"
+
+[[SHA]]
+uuid = "ea8e919c-243c-51af-8825-aaa63cd721ce"
+
+[[Serialization]]
+uuid = "9e88b42a-f829-5b0c-bbe9-9e923198166b"
+
+[[Sockets]]
+uuid = "6462fe0b-24de-5631-8697-dd941f90decc"
+
+[[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"
+
+[[Test]]
+deps = ["Distributed", "InteractiveUtils", "Logging", "Random"]
+uuid = "8dfed614-e22c-5e08-85e1-65c5234f0b40"
+
+[[TimerOutputs]]
+deps = ["Printf"]
+git-tree-sha1 = "f458ca23ff80e46a630922c555d838303e4b9603"
+uuid = "a759f4b9-e2f1-59dc-863e-4aeb61b1ea8f"
+version = "0.5.6"
+
+[[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"
+
+[[UnitCommitment]]
+deps = ["Cbc", "DataStructures", "Documenter", "GLPK", "GZip", "Gurobi", "JSON", "JuMP", "LinearAlgebra", "Logging", "MathOptInterface", "OrderedCollections", "PackageCompiler", "Printf", "Requires", "SparseArrays", "Test", "TimerOutputs"]
+path = ".."
+uuid = "64606440-39ea-11e9-0f29-3303a1d3d877"
+version = "2.1.0"
+
+[[ZipFile]]
+deps = ["Libdl", "Printf", "Zlib_jll"]
+git-tree-sha1 = "c3a5637e27e914a7a445b8d0ad063d701931e9f7"
+uuid = "a5390f91-8eb1-5f08-bee0-b1d1ffed6cea"
+version = "0.9.3"
+
+[[Zlib_jll]]
+deps = ["Artifacts", "JLLWrappers", "Libdl", "Pkg"]
+git-tree-sha1 = "320228915c8debb12cb434c59057290f0834dbf6"
+uuid = "83775a58-1f1d-513f-b197-d71354ab007a"
+version = "1.2.11+18"
--- a/benchmark/Project.toml
+++ b/benchmark/Project.toml
@@ -1,5 +1,4 @@
 [deps]
-DocOpt = "968ba79b-81e4-546f-ab3a-2eecfa62a9db"
 Gurobi = "2e9cd046-0924-5485-92f1-d5272153d98b"
 JSON = "682c06a0-de6a-54ab-a142-c8b1cf79cde6"
 JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
--- a/benchmark/run.jl
+++ b/benchmark/run.jl
@@ -2,208 +2,103 @@
 # Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
 # Released under the modified BSD license. See COPYING.md for more details.

-doc = """UnitCommitment.jl Benchmark Runner
-
-Usage:
-  run.jl [-s ARG]... [-m ARG]... [-c ARG]... [-f ARG]... [options]
-
-Examples:
-
-    1. Benchmark all solvers, methods and formulations:
-
-        julia run.jl
-
-    2. Benchmark formulations "default" and "ArrCon200" using Gurobi:
-
-        julia run.jl -s gurobi -f default -f ArrCon2000
-
-    3. Benchmark a few test cases, using all solvers, methods and formulations:
-
-        julia run.jl -c or-lib/20_0_1_w -c matpower/case1888rte/2017-02-01
-
-    4. Solve 4 test cases in parallel, with 2 threads available per worker:
-
-        JULIA_NUM_THREADS=2 julia --procs 4 run.jl
-
-Options:
-  -h --help             Show this screen.
-  -s --solver=ARG       Mixed-integer linear solver (e.g. gurobi)
-  -c --case=ARG         Unit commitment test case (e.g. or-lib/20_0_1_w)
-  -m --method=ARG       Solution method (e.g. default)
-  -f --formulation=ARG  Formulation (e.g. ArrCon2000)
-  --time-limit=ARG      Time limit in seconds [default: 3600]
-  --gap=ARG             Relative MIP gap tolerance [default: 0.001]
-  --trials=ARG          Number of trials [default: 5]
-"""
-
-using Distributed
-using Pkg
-Pkg.activate(".")
-@everywhere using Pkg
-@everywhere Pkg.activate(".")
-
-using DocOpt
-args = docopt(doc)
-
-@everywhere using UnitCommitment
-@everywhere UnitCommitment._setup_logger()
-
 using UnitCommitment
-using Gurobi
-using Logging
 using JuMP
+using Gurobi
+using JSON
+using Logging
+using Printf
+using LinearAlgebra

-import UnitCommitment:
-    ArrCon2000,
-    CarArr2006,
-    DamKucRajAta2016,
-    Formulation,
-    Gar1962,
-    KnuOstWat2018,
-    MorLatRam2013,
-    PanGua2016,
-    XavQiuWanThi2019
+function main()
+    NUM_THREADS = 4
+    time_limit = 60 * 20
+    BLAS.set_num_threads(NUM_THREADS)

-# Benchmark test cases
-# -----------------------------------------------------------------------------
-cases = [
-    "pglib-uc/ca/2014-09-01_reserves_0",
-    "pglib-uc/ca/2014-09-01_reserves_1",
-    "pglib-uc/ca/2015-03-01_reserves_0",
-    "pglib-uc/ca/2015-06-01_reserves_0",
-    "pglib-uc/ca/Scenario400_reserves_1",
-    "pglib-uc/ferc/2015-01-01_lw",
-    "pglib-uc/ferc/2015-05-01_lw",
-    "pglib-uc/ferc/2015-07-01_hw",
-    "pglib-uc/ferc/2015-10-01_lw",
-    "pglib-uc/ferc/2015-12-01_lw",
-    "pglib-uc/rts_gmlc/2020-04-03",
-    "pglib-uc/rts_gmlc/2020-09-20",
-    "pglib-uc/rts_gmlc/2020-10-27",
-    "pglib-uc/rts_gmlc/2020-11-25",
-    "pglib-uc/rts_gmlc/2020-12-23",
-    "or-lib/20_0_1_w",
-    "or-lib/20_0_5_w",
-    "or-lib/50_0_2_w",
-    "or-lib/75_0_2_w",
-    "or-lib/100_0_1_w",
-    "or-lib/100_0_4_w",
-    "or-lib/100_0_5_w",
-    "or-lib/200_0_3_w",
-    "or-lib/200_0_7_w",
-    "or-lib/200_0_9_w",
-    "tejada19/UC_24h_290g",
-    "tejada19/UC_24h_623g",
-    "tejada19/UC_24h_959g",
-    "tejada19/UC_24h_1577g",
-    "tejada19/UC_24h_1888g",
-    "tejada19/UC_168h_72g",
-    "tejada19/UC_168h_86g",
-    "tejada19/UC_168h_130g",
-    "tejada19/UC_168h_131g",
-    "tejada19/UC_168h_199g",
-    "matpower/case1888rte/2017-02-01",
-    "matpower/case1951rte/2017-02-01",
-    "matpower/case2848rte/2017-02-01",
-    "matpower/case3012wp/2017-02-01",
-    "matpower/case3375wp/2017-02-01",
-    "matpower/case6468rte/2017-02-01",
-    "matpower/case6515rte/2017-02-01",
-]
-
-# Formulations
-# -----------------------------------------------------------------------------
-formulations = Dict(
-    "default" => Formulation(),
-    "ArrCon2000" => Formulation(ramping = ArrCon2000.Ramping()),
-    "CarArr2006" => Formulation(pwl_costs = CarArr2006.PwlCosts()),
-    "DamKucRajAta2016" => Formulation(ramping = DamKucRajAta2016.Ramping()),
-    "Gar1962" => Formulation(pwl_costs = Gar1962.PwlCosts()),
-    "KnuOstWat2018" => Formulation(pwl_costs = KnuOstWat2018.PwlCosts()),
-    "MorLatRam2013" => Formulation(ramping = MorLatRam2013.Ramping()),
-    "PanGua2016" => Formulation(ramping = PanGua2016.Ramping()),
-)
-
-# Solution methods
-# -----------------------------------------------------------------------------
-const gap_limit = parse(Float64, args["--gap"])
-const time_limit = parse(Float64, args["--time-limit"])
-methods = Dict(
-    "default" => XavQiuWanThi2019.Method(
-        time_limit = time_limit,
-        gap_limit = gap_limit,
-    ),
-)
-
-# MIP solvers
-# -----------------------------------------------------------------------------
-optimizers = Dict(
-    "gurobi" => optimizer_with_attributes(
-        Gurobi.Optimizer,
-        "Threads" => Threads.nthreads(),
-    ),
-)
-
-# Parse command line arguments
-# -----------------------------------------------------------------------------
-if !isempty(args["--case"])
-    cases = args["--case"]
-end
-if !isempty(args["--formulation"])
-    formulations = filter(p -> p.first in args["--formulation"], formulations)
-end
-if !isempty(args["--method"])
-    methods = filter(p -> p.first in args["--method"], methods)
-end
-if !isempty(args["--solver"])
-    optimizers = filter(p -> p.first in args["--solver"], optimizers)
-end
-const ntrials = parse(Int, args["--trials"])
-
-# Print benchmark settings
-# -----------------------------------------------------------------------------
-function printlist(d::Dict)
-    for key in keys(d)
-        @info "  - $key"
+    if length(ARGS) >= 2
+      mode = string("_", ARGS[2])
+    else
+      mode = "_default"
    end
-end
-
-function printlist(d::Vector)
-    for key in d
-        @info "  - $key"
+    if length(ARGS) >= 3 && !isempty(strip(ARGS[3]))
+      results_dir = ARGS[3]
+    else
+      results_dir = string("./","results$mode")
    end
-end

-@info "Computational environment:"
-@info "  - CPU: $(Sys.cpu_info()[1].model)"
-@info "  - Logical CPU cores: $(length(Sys.cpu_info()))"
-@info "  - System memory: $(round(Sys.total_memory() / 2^30, digits=2)) GiB"
-@info "  - Available workers: $(nworkers())"
-@info "  - Available threads per worker: $(Threads.nthreads())"
+    # Validate mode and set formulation
+    if mode == "_default"
+      formulation = UnitCommitment.DefaultFormulation
+    elseif mode == "_tight"
+      formulation = UnitCommitment.TightFormulation
+    elseif mode == "_sparse"
+      formulation = UnitCommitment.SparseDefaultFormulation
+    else
+      error("Unknown formulation requested: ", ARGS[2])
+    end

-@info "Parameters:"
-@info "  - Number of trials: $ntrials"
-@info "  - Time limit (s): $time_limit"
-@info "  - Relative MIP gap tolerance: $gap_limit"
+    # Filename is instance_name.sample_number.sol.gz
+    # Parse out the instance + sample parts to create output files
+    basename, suffix = split(ARGS[1], ".") # will not work if suffix part is not present
+    model_filename_stub = string(results_dir,"/$basename.$suffix")
+    solution_filename = string("$model_filename_stub.sol.json")

-@info "Solvers:"
-printlist(optimizers)
+    # Choose logging options
+    logname, logfile = nothing, nothing
+    #logname = string("$model_filename_stub.out")
+    if isa(logname, String) && !isempty(logname)
+      logfile = open(logname, "w")
+      global_logger(TimeLogger(initial_time = time(), file = logfile))
+    else
+      global_logger(TimeLogger(initial_time = time()))
+    end

-@info "Methods:"
-printlist(methods)
+    total_time = @elapsed begin
+        @info "Reading: $basename"
+        time_read = @elapsed begin
+            instance = UnitCommitment.read_benchmark(basename)
+        end
+        @info @sprintf("Read problem in %.2f seconds", time_read)

-@info "Formulations:"
-printlist(formulations)
+        time_model = @elapsed begin
+            optimizer=optimizer_with_attributes(Gurobi.Optimizer,
+                                                "Threads" => NUM_THREADS,
+                                                "Seed" => rand(1:1000))
+            model = build_model(instance=instance, optimizer=optimizer, formulation=formulation)
+        end
+    end

-@info "Cases:"
-printlist(cases)
+    @info "Setting names..."
+    UnitCommitment.set_variable_names!(model)

-# Run benchmarks
-# -----------------------------------------------------------------------------
-UnitCommitment._run_benchmarks(
-    cases = cases,
-    formulations = formulations,
-    methods = methods,
-    optimizers = optimizers,
-    trials = 1:ntrials,
-)
+    model_filename = string(model_filename_stub,".init",".mps.gz")
+    @info string("Exporting initial model without transmission constraints to ", model_filename)
+    JuMP.write_to_file(model.mip, model_filename)
+
+    total_time += @elapsed begin
+        @info "Optimizing..."
+        BLAS.set_num_threads(1)
+        UnitCommitment.optimize!(model, time_limit=time_limit, gap_limit=1e-3)
+    end
+
+    @info @sprintf("Total time was %.2f seconds", total_time)
+
+    @info "Writing: $solution_filename"
+    solution = UnitCommitment.get_solution(model)
+    open(solution_filename, "w") do file
+        JSON.print(file, solution, 2)
+    end
+
+    @info "Verifying solution..."
+    UnitCommitment.validate(instance, solution) 
+
+    model_filename = string(model_filename_stub,".final",".mps.gz")
+    @info string("Exporting final model to ", model_filename)
+    JuMP.write_to_file(model.mip, model_filename)
+
+    if !isnothing(logfile)
+      close(logfile)
+    end
+end # main
+
+main()
--- a/benchmark/scripts/compare.py
+++ b/benchmark/scripts/compare.py
@@ -5,82 +5,60 @@
 import pandas as pd
 import numpy as np
 import seaborn as sns
-import matplotlib
 import matplotlib.pyplot as plt
 import sys

-matplotlib.use("Agg")
-sns.set("talk")
-sns.set_palette(
-    [
-        "#9b59b6",
-        "#3498db",
-        "#95a5a6",
-        "#e74c3c",
-        "#34495e",
-        "#2ecc71",
-    ]
-)
+#easy_cutoff = 120

-filename = sys.argv[1]
-m1 = sys.argv[2]
-m2 = sys.argv[3]
+b1 = pd.read_csv(sys.argv[1], index_col=0)
+b2 = pd.read_csv(sys.argv[2], index_col=0)

-# Prepare data
-data = pd.read_csv(filename, index_col=0)
-b1 = (
-    data[data["Group"] == m1]
-    .groupby(["Instance", "Sample"])
-    .mean()[["Optimization time (s)"]]
-)
-b2 = (
-    data[data["Group"] == m2]
-    .groupby(["Instance", "Sample"])
-    .mean()[["Optimization time (s)"]]
-)
-b1.columns = [f"{m1} time (s)"]
-b2.columns = [f"{m2} time (s)"]
-merged = pd.merge(b1, b2, left_index=True, right_index=True).reset_index().dropna()
-merged["Speedup"] = merged[f"{m1} time (s)"] / merged[f"{m2} time (s)"]
-merged["Group"] = merged["Instance"].str.replace(r"\/.*", "", regex=True)
-merged = merged.sort_values(by=["Instance", "Sample"], ascending=True)
-merged = merged[(merged[f"{m1} time (s)"] > 0) & (merged[f"{m2} time (s)"] > 0)]
+c1 = b1.groupby(["Group", "Instance", "Sample"])[["Optimization time (s)", "Primal bound"]].mean()
+c2 = b2.groupby(["Group", "Instance", "Sample"])[["Optimization time (s)", "Primal bound"]].mean()
+c1.columns = ["A Time (s)", "A Value"]
+c2.columns = ["B Time (s)", "B Value"]

-# Plot results
-k1 = len(merged.groupby("Instance").mean())
-k2 = len(merged.groupby("Group").mean())
-k = k1 + k2
-fig = plt.figure(
-    constrained_layout=True,
-    figsize=(15, max(5, 0.75 * k)),
-)
-plt.suptitle(f"{m1} vs {m2}")
-gs1 = fig.add_gridspec(nrows=k, ncols=1)
-ax1 = fig.add_subplot(gs1[0:k1, 0:1])
-ax2 = fig.add_subplot(gs1[k1:, 0:1], sharex=ax1)
-sns.barplot(
-    data=merged,
-    x="Speedup",
-    y="Instance",
-    color="tab:purple",
-    errcolor="k",
-    errwidth=1.25,
-    ax=ax1,
-)
-sns.barplot(
-    data=merged,
-    x="Speedup",
-    y="Group",
-    color="tab:purple",
-    errcolor="k",
-    errwidth=1.25,
-    ax=ax2,
-)
-ax1.axvline(1.0, linestyle="--", color="k")
-ax2.axvline(1.0, linestyle="--", color="k")
+merged = pd.concat([c1, c2], axis=1)
+merged["Speedup"] = merged["A Time (s)"] / merged["B Time (s)"]
+merged["Time diff (s)"] = merged["B Time (s)"] - merged["A Time (s)"]
+merged["Value diff (%)"] = np.round((merged["B Value"] - merged["A Value"]) / merged["A Value"] * 100.0, 5)
+merged.loc[merged.loc[:, "B Time (s)"] <= 0, "Speedup"] = float("nan")
+merged.loc[merged.loc[:, "B Time (s)"] <= 0, "Time diff (s)"] = float("nan")
+#merged = merged[(merged["A Time (s)"] >= easy_cutoff) | (merged["B Time (s)"] >= easy_cutoff)]
+merged.reset_index(inplace=True)
+merged["Name"] = merged["Group"] + "/" + merged["Instance"]
+#merged = merged.sort_values(by="Speedup", ascending=False)
+
+
+k = len(merged.groupby("Name"))
+plt.figure(figsize=(12, 0.50 * k))
+plt.rcParams['xtick.bottom'] = plt.rcParams['xtick.labelbottom'] = True
+plt.rcParams['xtick.top'] = plt.rcParams['xtick.labeltop'] = True
+sns.set_style("whitegrid")
+sns.set_palette("Set1")
+sns.barplot(data=merged,
+            x="Speedup",
+            y="Name",
+            color="tab:red",
+            capsize=0.15,
+            errcolor="k",
+            errwidth=1.25)
+plt.axvline(1.0, linestyle="--", color="k")
+plt.tight_layout()

 print("Writing tables/compare.png")
 plt.savefig("tables/compare.png", dpi=150)

 print("Writing tables/compare.csv")
-merged.to_csv("tables/compare.csv", index_label="Index")
+merged.loc[:, ["Group",
+               "Instance",
+               "Sample",
+               "A Time (s)",
+               "B Time (s)",
+               "Speedup",
+               "Time diff (s)",
+               "A Value",
+               "B Value",
+               "Value diff (%)",
+              ]
+          ].to_csv("tables/compare.csv", index_label="Index")
--- a/benchmark/scripts/table.py
+++ b/benchmark/scripts/table.py
@@ -6,13 +6,11 @@ from pathlib import Path
 import pandas as pd
 import re
 from tabulate import tabulate
-from colorama import init, Fore, Back, Style
-
-init()


 def process_all_log_files():
-    pathlist = list(Path(".").glob("results/**/*.log"))
+    pathlist = list(Path(".").glob('results/*/*/*.log'))
+    pathlist += list(Path(".").glob('results/*/*.log'))
    rows = []
    for path in pathlist:
        if ".ipy" in str(path):
@@ -24,13 +22,13 @@ def process_all_log_files():
    df.index = range(len(df))
    print("Writing tables/benchmark.csv")
    df.to_csv("tables/benchmark.csv", index_label="Index")
-
-
+        
+        
 def process(filename):
    parts = filename.replace(".log", "").split("/")
-    group_name = parts[1]
-    instance_name = "/".join(parts[2:-1])
-    sample_name = parts[-1]
+    group_name = "/".join(parts[1:-1])
+    instance_name = parts[-1]
+    instance_name, sample_name = instance_name.split(".")
    nodes = 0.0
    optimize_time = 0.0
    simplex_iterations = 0.0
@@ -47,75 +45,56 @@ def process(filename):
    read_time, model_time, isf_time, total_time = None, None, None, None
    cb_calls, cb_time = 0, 0.0
    transmission_count, transmission_time, transmission_calls = 0, 0.0, 0
-
+    
    # m = re.search("case([0-9]*)", instance_name)
    # n_buses = int(m.group(1))
    n_buses = 0
-    validation_errors = 0
-
+    
    with open(filename) as file:
        for line in file.readlines():
-            m = re.search(
-                r"Explored ([0-9.e+]*) nodes \(([0-9.e+]*) simplex iterations\) in ([0-9.e+]*) seconds",
-                line,
-            )
+            m = re.search(r"Explored ([0-9.e+]*) nodes \(([0-9.e+]*) simplex iterations\) in ([0-9.e+]*) seconds", line)
            if m is not None:
                nodes += int(m.group(1))
                simplex_iterations += int(m.group(2))
                optimize_time += float(m.group(3))
-
-            m = re.search(
-                r"Best objective ([0-9.e+]*), best bound ([0-9.e+]*), gap ([0-9.e+]*)\%",
-                line,
-            )
+                
+            m = re.search(r"Best objective ([0-9.e+]*), best bound ([0-9.e+]*), gap ([0-9.e+]*)\%", line)
            if m is not None:
                primal_bound = float(m.group(1))
                dual_bound = float(m.group(2))
                gap = round(float(m.group(3)), 3)
-
-            m = re.search(
-                r"Root relaxation: objective ([0-9.e+]*), ([0-9.e+]*) iterations, ([0-9.e+]*) seconds",
-                line,
-            )
+                
+            m = re.search(r"Root relaxation: objective ([0-9.e+]*), ([0-9.e+]*) iterations, ([0-9.e+]*) seconds", line)
            if m is not None:
                root_obj = float(m.group(1))
                root_iterations += int(m.group(2))
                root_time += float(m.group(3))
-
-            m = re.search(
-                r"Presolved: ([0-9.e+]*) rows, ([0-9.e+]*) columns, ([0-9.e+]*) nonzeros",
-                line,
-            )
+                
+            m = re.search(r"Presolved: ([0-9.e+]*) rows, ([0-9.e+]*) columns, ([0-9.e+]*) nonzeros", line)
            if m is not None:
                n_rows_presolved = int(m.group(1))
                n_cols_presolved = int(m.group(2))
                n_nz_presolved = int(m.group(3))
-
-            m = re.search(
-                r"Optimize a model with ([0-9.e+]*) rows, ([0-9.e+]*) columns and ([0-9.e+]*) nonzeros",
-                line,
-            )
+                
+            m = re.search(r"Optimize a model with ([0-9.e+]*) rows, ([0-9.e+]*) columns and ([0-9.e+]*) nonzeros", line)
            if m is not None:
                n_rows_orig = int(m.group(1))
                n_cols_orig = int(m.group(2))
                n_nz_orig = int(m.group(3))
-
-            m = re.search(
-                r"Variable types: ([0-9.e+]*) continuous, ([0-9.e+]*) integer \(([0-9.e+]*) binary\)",
-                line,
-            )
+                
+            m = re.search(r"Variable types: ([0-9.e+]*) continuous, ([0-9.e+]*) integer \(([0-9.e+]*) binary\)", line)
            if m is not None:
                n_cont_vars_presolved = int(m.group(1))
-                n_bin_vars_presolved = int(m.group(3))
-
+                n_bin_vars_presolved = int(m.group(3))  
+            
            m = re.search(r"Read problem in ([0-9.e+]*) seconds", line)
            if m is not None:
                read_time = float(m.group(1))
-
+            
            m = re.search(r"Computed ISF in ([0-9.e+]*) seconds", line)
            if m is not None:
                isf_time = float(m.group(1))
-
+            
            m = re.search(r"Built model in ([0-9.e+]*) seconds", line)
            if m is not None:
                model_time = float(m.group(1))
@@ -124,10 +103,7 @@ def process(filename):
            if m is not None:
                total_time = float(m.group(1))

-            m = re.search(
-                r"User-callback calls ([0-9.e+]*), time in user-callback ([0-9.e+]*) sec",
-                line,
-            )
+            m = re.search(r"User-callback calls ([0-9.e+]*), time in user-callback ([0-9.e+]*) sec", line)
            if m is not None:
                cb_calls = int(m.group(1))
                cb_time = float(m.group(2))
@@ -140,15 +116,7 @@ def process(filename):
            m = re.search(r".*MW overflow", line)
            if m is not None:
                transmission_count += 1
-
-            m = re.search(r".*Found ([0-9]*) validation errors", line)
-            if m is not None:
-                validation_errors += int(m.group(1))
-                print(
-                    f"{Fore.YELLOW}{Style.BRIGHT}Warning:{Style.RESET_ALL} {validation_errors:8d} "
-                    f"{Style.DIM}validation errors in {Style.RESET_ALL}{group_name}/{instance_name}/{sample_name}"
-                )
-
+                
    return {
        "Group": group_name,
        "Instance": instance_name,
@@ -180,51 +148,36 @@ def process(filename):
        "Transmission screening constraints": transmission_count,
        "Transmission screening time": transmission_time,
        "Transmission screening calls": transmission_calls,
-        "Validation errors": validation_errors,
    }

-
 def generate_chart():
    import pandas as pd
-    import matplotlib
    import matplotlib.pyplot as plt
    import seaborn as sns

-    matplotlib.use("Agg")
-    sns.set("talk")
-    sns.set_palette(
-        [
-            "#9b59b6",
-            "#3498db",
-            "#95a5a6",
-            "#e74c3c",
-            "#34495e",
-            "#2ecc71",
-        ]
-    )
-
    tables = []
    files = ["tables/benchmark.csv"]
    for f in files:
        table = pd.read_csv(f, index_col=0)
+        table.loc[:, "Instance"] = table.loc[:,"Group"] + "/" + table.loc[:,"Instance"]
        table.loc[:, "Filename"] = f
        tables += [table]
    benchmark = pd.concat(tables, sort=True)
-    benchmark = benchmark.sort_values(by=["Group", "Instance"])
-    k1 = len(benchmark.groupby("Instance"))
-    k2 = len(benchmark.groupby("Group"))
-    plt.figure(figsize=(12, 0.25 * k1 * k2))
-    sns.barplot(
-        y="Instance",
-        x="Total time (s)",
-        hue="Group",
-        errcolor="k",
-        errwidth=1.25,
-        data=benchmark,
-    )
+    benchmark = benchmark.sort_values(by="Instance")
+    k = len(benchmark.groupby("Instance"))
+    plt.figure(figsize=(12, 0.50 * k))
+    sns.set_style("whitegrid")
+    sns.set_palette("Set1")
+    sns.barplot(y="Instance",
+                x="Total time (s)",
+                color="tab:red",
+                capsize=0.15,
+                errcolor="k",
+                errwidth=1.25,
+                data=benchmark);
    plt.tight_layout()
    print("Writing tables/benchmark.png")
-    plt.savefig("tables/benchmark.png", dpi=150)
+    plt.savefig("tables/benchmark.png", dpi=150);


 if __name__ == "__main__":
--- a/docs/Project.toml
+++ b/docs/Project.toml
@@ -1,5 +0,0 @@
-[deps]
-Documenter = "e30172f5-a6a5-5a46-863b-614d45cd2de4"
-JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
-Revise = "295af30f-e4ad-537b-8983-00126c2a3abe"
-UnitCommitment = "64606440-39ea-11e9-0f29-3303a1d3d877"
--- a/docs/make.jl
+++ b/docs/make.jl
@@ -1,16 +0,0 @@
-using Documenter, UnitCommitment, JuMP
-
-makedocs(
-    sitename="UnitCommitment.jl",
-    pages=[
-        "Home" => "index.md",
-        "usage.md",
-        "format.md",
-        "instances.md",
-        "model.md",
-        "api.md",
-    ],
-    format = Documenter.HTML(
-        assets=["assets/custom.css"],
-    )
-)
--- a/docs/src/api.md
+++ b/docs/src/api.md
@@ -1,62 +0,0 @@
-# API Reference
-
-## Read data, build model & optimize
-
-```@docs
-UnitCommitment.read
-UnitCommitment.read_benchmark
-UnitCommitment.build_model
-UnitCommitment.optimize!
-UnitCommitment.solution
-UnitCommitment.validate
-UnitCommitment.write
-```
-
-## Locational Marginal Prices
-
-### Conventional LMPs
-```@docs
-UnitCommitment.compute_lmp(::JuMP.Model,::UnitCommitment.ConventionalLMP)
-```
-
-### Approximated Extended LMPs
-```@docs
-UnitCommitment.AELMP
-UnitCommitment.compute_lmp(::JuMP.Model,::UnitCommitment.AELMP)
-```
-
-
-## Modify instance
-
-```@docs
-UnitCommitment.slice
-UnitCommitment.randomize!(::UnitCommitment.UnitCommitmentInstance)
-UnitCommitment.generate_initial_conditions!
-```
-
-## Formulations
-
-```@docs
-UnitCommitment.Formulation
-UnitCommitment.ShiftFactorsFormulation
-UnitCommitment.ArrCon2000
-UnitCommitment.CarArr2006
-UnitCommitment.DamKucRajAta2016
-UnitCommitment.Gar1962
-UnitCommitment.KnuOstWat2018
-UnitCommitment.MorLatRam2013
-UnitCommitment.PanGua2016
-UnitCommitment.WanHob2016
-```
-
-## Solution Methods
-
-```@docs
-UnitCommitment.XavQiuWanThi2019.Method
-```
-
-## Randomization Methods
-
-```@docs
-UnitCommitment.XavQiuAhm2021.Randomization
-```
--- a/docs/src/assets/custom.css
+++ b/docs/src/assets/custom.css
@@ -1,36 +0,0 @@
-@media screen and (min-width: 1056px) {
-    #documenter .docs-main {
-      max-width: 65rem !important;
-    }
-}
-  
-
-tbody, thead, pre {
-    border: 1px solid rgba(0, 0, 0, 0.25);
-}
-
-table td, th {
-    padding: 8px;
-}
-
-table p {
-    margin-bottom: 0;
-}
-
-table td code {
-    white-space: nowrap;
-}
-
-table tr,
-table th {
-    border-bottom: 1px solid rgba(0, 0, 0, 0.1);
-}
-
-table tr:last-child {
-    border-bottom: 0;
-}
-
-code {
-    background-color: transparent;
-    color: rgb(232, 62, 140);
-}
--- a/docs/src/index.md
+++ b/docs/src/index.md
@@ -1,69 +0,0 @@
-# UnitCommitment.jl
-
-**UnitCommitment.jl** (UC.jl) is a Julia/JuMP optimization package for the Security-Constrained Unit Commitment Problem (SCUC), a fundamental optimization problem in power systems used, for example, to clear the day-ahead electricity markets. The package provides benchmark instances for the problem and Julia/JuMP implementations of state-of-the-art mixed-integer programming formulations.
-
-## Package Components
-
-* **Data Format:** The package proposes an extensible and fully-documented JSON-based data specification format for SCUC, developed in collaboration with Independent System Operators (ISOs), which describes the most important aspects of the problem. The format supports all the most common generator characteristics (including ramping, piecewise-linear production cost curves and time-dependent startup costs), as well as operating reserves, price-sensitive loads, transmission networks and contingencies.
-* **Benchmark Instances:** The package provides a diverse collection of large-scale benchmark instances collected from the literature, converted into a common data format, and extended using data-driven methods to make them more challenging and realistic.
-* **Model Implementation**: The package provides a Julia/JuMP implementations of state-of-the-art formulations and solution methods for SCUC, including multiple ramping formulations ([ArrCon2000](https://doi.org/10.1109/59.871739), [MorLatRam2013](https://doi.org/10.1109/TPWRS.2013.2251373), [DamKucRajAta2016](https://doi.org/10.1007/s10107-015-0919-9), [PanGua2016](https://doi.org/10.1287/opre.2016.1520)), multiple piecewise-linear costs formulations ([Gar1962](https://doi.org/10.1109/AIEEPAS.1962.4501405), [CarArr2006](https://doi.org/10.1109/TPWRS.2006.876672), [KnuOstWat2018](https://doi.org/10.1109/TPWRS.2017.2783850)) and contingency screening methods ([XavQiuWanThi2019](https://doi.org/10.1109/TPWRS.2019.2892620)). Our goal is to keep these implementations up-to-date as new methods are proposed in the literature.
-* **Benchmark Tools:** The package provides automated benchmark scripts to accurately evaluate the performance impact of proposed code changes.
-
-## Table of Contents
-
-```@contents
-Pages = ["usage.md", "format.md", "instances.md", "model.md", "api.md"]
-Depth = 3
-```
-
-## Authors
-* **Alinson S. Xavier** (Argonne National Laboratory)
-* **Aleksandr M. Kazachkov** (University of Florida)
-* **Ogün Yurdakul** (Technische Universität Berlin)
-* **Jun He** (Purdue University)
-* **Feng Qiu** (Argonne National Laboratory)
-
-## Acknowledgments
-
-* We would like to thank **Yonghong Chen** (Midcontinent Independent System Operator), **Feng Pan** (Pacific Northwest National Laboratory) for valuable feedback on early versions of this package.
-
-* Based upon work supported by **Laboratory Directed Research and Development** (LDRD) funding from Argonne National Laboratory, provided by the Director, Office of Science, of the U.S. Department of Energy under Contract No. DE-AC02-06CH11357
-
-* Based upon work supported by the **U.S. Department of Energy Advanced Grid Modeling Program** under Grant DE-OE0000875.
-
-## Citing
-
-If you use UnitCommitment.jl in your research (instances, models or algorithms), we kindly request that you cite the package as follows:
-
-* **Alinson S. Xavier, Aleksandr M. Kazachkov, Ogün Yurdakul, Feng Qiu**, "UnitCommitment.jl: A Julia/JuMP Optimization Package for Security-Constrained Unit Commitment (Version 0.3)". Zenodo (2022). [DOI: 10.5281/zenodo.4269874](https://doi.org/10.5281/zenodo.4269874).
-
-If you use the instances, we additionally request that you cite the original sources, as described in the [instances page](instances.md).
-
-## License
-
-```text
-UnitCommitment.jl: A Julia/JuMP Optimization Package for Security-Constrained Unit Commitment
-Copyright © 2020-2022, UChicago Argonne, LLC. All Rights Reserved.
-
-Redistribution and use in source and binary forms, with or without modification, are permitted
-provided that the following conditions are met:
-
-1. Redistributions of source code must retain the above copyright notice, this list of
-   conditions and the following disclaimer.
-2. Redistributions in binary form must reproduce the above copyright notice, this list of
-   conditions and the following disclaimer in the documentation and/or other materials provided
-   with the distribution.
-3. Neither the name of the copyright holder nor the names of its contributors may be used to
-   endorse or promote products derived from this software without specific prior written
-   permission.
-
-THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR
-IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY
-AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR
-CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR
-CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR
-SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY
-THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
-OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
-POSSIBILITY OF SUCH DAMAGE.
-```
--- a/docs/src/model.md
+++ b/docs/src/model.md
@@ -1,200 +0,0 @@
-JuMP Model
-==========
-
-In this page, we describe the JuMP optimization model produced by the function `UnitCommitment.build_model`. A detailed understanding of this model is not necessary if you are just interested in using the package to solve some standard unit commitment cases, but it may be useful, for example, if you need to solve a slightly different problem, with additional variables and constraints. The notation in this page generally follows [KnOsWa20].
-
-Decision variables
------------------
-
-### Generators
-
-#### Thermal Units
-
-Name | Symbol | Description | Unit
-:-----|:--------:|:-------------|:------:
-`is_on[g,t]` | $u_{g}(t)$ | True if generator `g` is on at time `t`. | Binary
-`switch_on[g,t]` | $v_{g}(t)$ | True is generator `g` switches on at time `t`. | Binary
-`switch_off[g,t]` | $w_{g}(t)$ | True if generator `g` switches off at time `t`. | Binary
-`prod_above[g,t]` |$p'_{g}(t)$ | Amount of power produced by generator `g` above its minimum power output at time `t`. For example, if the minimum power of generator `g` is 100 MW and `g` is producing 115 MW of power at time `t`, then `prod_above[g,t]` equals `15.0`. | MW
-`segprod[g,t,k]` | $p^k_g(t)$ | Amount of power from piecewise linear segment `k` produced by generator `g` at time `t`. For example, if cost curve for generator `g` is defined by the points `(100, 1400)`, `(110, 1600)`, `(130, 2200)` and `(135, 2400)`, and if the generator is producing 115 MW of power at time `t`, then `segprod[g,t,:]` equals `[10.0, 5.0, 0.0]`.| MW
-`reserve[r,g,t]` | $r_g(t)$ | Amount of reserve `r` provided by unit `g` at time `t`. | MW
-`startup[g,t,s]` | $\delta^s_g(t)$ | True if generator `g` switches on at time `t` incurring start-up costs from start-up category `s`. | Binary
-
-
-#### Profiled Units
-
-Name | Symbol | Description | Unit
-:-----|:------:|:-------------|:------:
-`prod_profiled[s,t]` | $p^{\dagger}_{g}(t)$ | Amount of power produced by profiled unit `g` at time `t`. | MW
-
-
-### Buses
-
-Name | Symbol | Description | Unit
-:-----|:------:|:-------------|:------:
-`net_injection[b,t]` | $n_b(t)$ | Net injection at bus `b` at time `t`. | MW
-`curtail[b,t]` | $s^+_b(t)$ | Amount of load curtailed at bus `b` at time `t` | MW
-
-
-### Price-sensitive loads
-
-Name | Symbol | Description | Unit
-:-----|:------:|:-------------|:------:
-`loads[s,t]` | $d_{s}(t)$ | Amount of power served to price-sensitive load `s` at time `t`. | MW
-
-### Transmission lines
-
-Name | Symbol | Description | Unit
-:-----|:------:|:-------------|:------:
-`flow[l,t]` | $f_l(t)$ | Power flow on line `l` at time `t`. | MW
-`overflow[l,t]` | $f^+_l(t)$ | Amount of flow above the limit for line `l` at time `t`. | MW
-
-!!! warning
-
-    Since transmission and N-1 security constraints are enforced in a lazy way, most of the `flow[l,t]` variables are never added to the model. Accessing `model[:flow][l,t]` without first checking that the variable exists will likely generate an error.
-
-Objective function
------------------
-
-TODO
-
-Constraints
-----------
-
-TODO
-
-
-Inspecting and modifying the model
----------------------------------
-
-### Accessing decision variables
-
-After building a model using `UnitCommitment.build_model`, it is possible to obtain a reference to the decision variables by calling `model[:varname][index]`. For example, `model[:is_on]["g1",1]` returns a direct reference to the JuMP variable indicating whether generator named "g1" is on at time 1. The script below illustrates how to build a model, solve it and display the solution without using the function `UnitCommitment.solution`.
-
-```julia
-using Cbc
-using Printf
-using JuMP
-using UnitCommitment
-
-# Load benchmark instance
-instance = UnitCommitment.read_benchmark("matpower/case118/2017-02-01")
-
-# Build JuMP model
-model = UnitCommitment.build_model(
-    instance=instance,
-    optimizer=Cbc.Optimizer,
-)
-
-# Solve the model
-UnitCommitment.optimize!(model)
-
-# Display commitment status
-for g in instance.units
-    for t in 1:instance.time
-        @printf(
-            "%-10s %5d %5.1f %5.1f %5.1f\n",
-            g.name,
-            t,
-            value(model[:is_on][g.name, t]),
-            value(model[:switch_on][g.name, t]),
-            value(model[:switch_off][g.name, t]),
-        )
-    end
-end
-```
-
-### Fixing variables, modifying objective function and adding constraints
-
-Since we now have a direct reference to the JuMP decision variables, it is possible to fix variables, change the coefficients in the objective function, or even add new constraints to the model before solving it. The script below shows how can this be accomplished. For more information on modifying an existing model, [see the JuMP documentation](https://jump.dev/JuMP.jl/stable/manual/variables/).
-
-```julia
-using Cbc
-using JuMP
-using UnitCommitment
-
-# Load benchmark instance
-instance = UnitCommitment.read_benchmark("matpower/case118/2017-02-01")
-
-# Construct JuMP model
-model = UnitCommitment.build_model(
-    instance=instance,
-    optimizer=Cbc.Optimizer,
-)
-
-# Fix a decision variable to 1.0
-JuMP.fix(
-    model[:is_on]["g1",1],
-    1.0,
-    force=true,
-)
-
-# Change the objective function
-JuMP.set_objective_coefficient(
-    model,
-    model[:switch_on]["g2",1],
-    1000.0,
-)
-
-# Create a new constraint
-@constraint(
-    model,
-    model[:is_on]["g3",1] + model[:is_on]["g4",1] <= 1,
-)
-
-# Solve the model
-UnitCommitment.optimize!(model)
-```
-
-### Adding new component to a bus
-
-The following snippet shows how to add a new grid component to a particular bus. For each time step, we create decision variables for the new grid component, add these variables to the objective function, then attach the component to a particular bus by modifying some existing model constraints. 
-
-```julia
-using Cbc
-using JuMP
-using UnitCommitment
-
-# Load instance and build base model
-instance = UnitCommitment.read_benchmark("matpower/case118/2017-02-01")
-model = UnitCommitment.build_model(
-    instance=instance,
-    optimizer=Cbc.Optimizer,
-)
-
-# Get the number of time steps in the original instance
-T = instance.time
-
-# Create decision variables for the new grid component.
-# In this example, we assume that the new component can
-# inject up to 10 MW of power at each time step, so we
-# create new continuous variables 0 ≤ x[t] ≤ 10.
-@variable(model, x[1:T], lower_bound=0.0, upper_bound=10.0)
-
-# For each time step
-for t in 1:T
-
-    # Add production costs to the objective function.
-    # In this example, we assume a cost of $5/MW.
-    set_objective_coefficient(model, x[t], 5.0)
-
-    # Attach the new component to bus b1, by modifying the
-    # constraint `eq_net_injection`.
-    set_normalized_coefficient(
-        model[:eq_net_injection]["b1", t],
-        x[t],
-        1.0,
-    )
-end
-
-# Solve the model
-UnitCommitment.optimize!(model)
-
-# Show optimal values for the x variables
-@show value.(x)
-```
-
-References
----------
-* [KnOsWa20] **Bernard Knueven, James Ostrowski and Jean-Paul Watson.** "On Mixed-Integer Programming Formulations for the Unit Commitment Problem". INFORMS Journal on Computing (2020). [DOI: 10.1287/ijoc.2019.0944](https://doi.org/10.1287/ijoc.2019.0944)
-
--- a/docs/src/usage.md
+++ b/docs/src/usage.md
@@ -1,226 +0,0 @@
-Usage
-=====
-
-Installation
------------
-
-UnitCommitment.jl was tested and developed with [Julia 1.7](https://julialang.org/). To install Julia, please follow the [installation guide on the official Julia website](https://julialang.org/downloads/). To install UnitCommitment.jl, run the Julia interpreter, type `]` to open the package manager, then type:
-
-```text
-pkg> add UnitCommitment@0.3
-```
-
-To test that the package has been correctly installed, run:
-
-```text
-pkg> test UnitCommitment
-```
-
-If all tests pass, the package should now be ready to be used by any Julia script on the machine.
-
-To solve the optimization models, a mixed-integer linear programming (MILP) solver is also required. Please see the [JuMP installation guide](https://jump.dev/JuMP.jl/stable/installation/) for more instructions on installing a solver. Typical open-source choices are [Cbc](https://github.com/JuliaOpt/Cbc.jl) and [GLPK](https://github.com/JuliaOpt/GLPK.jl). In the instructions below, Cbc will be used, but any other MILP solver listed in JuMP installation guide should also be compatible.
-
-Typical Usage
-------------
-
-### Solving user-provided instances
-
-The first step to use UC.jl is to construct a JSON file describing your unit commitment instance. See [Data Format](format.md) for a complete description of the data format UC.jl expects. The next steps, as shown below, are to: (1) read the instance from file; (2) construct the optimization model; (3) run the optimization; and (4) extract the optimal solution.
-
-```julia
-using Cbc
-using JSON
-using UnitCommitment
-
-# 1. Read instance
-instance = UnitCommitment.read("/path/to/input.json")
-
-# 2. Construct optimization model
-model = UnitCommitment.build_model(
-    instance=instance,
-    optimizer=Cbc.Optimizer,
-)
-
-# 3. Solve model
-UnitCommitment.optimize!(model)
-
-# 4. Write solution to a file
-solution = UnitCommitment.solution(model)
-UnitCommitment.write("/path/to/output.json", solution)
-```
-
-### Solving benchmark instances
-
-UnitCommitment.jl contains a large number of benchmark instances collected from the literature and converted into a common data format. To solve one of these instances individually, instead of constructing your own, the function `read_benchmark` can be used, as shown below. See [Instances](instances.md) for the complete list of available instances.
-
-```julia
-using UnitCommitment
-instance = UnitCommitment.read_benchmark("matpower/case3375wp/2017-02-01")
-```
-
-## Customizing the formulation
-
-By default, `build_model` uses a formulation that combines modeling components from different publications, and that has been carefully tested, using our own benchmark scripts, to provide good performance across a wide variety of instances. This default formulation is expected to change over time, as new methods are proposed in the literature. You can, however, construct your own formulation, based on the modeling components that you choose, as shown in the next example.
-
-```julia
-using Cbc
-using UnitCommitment
-
-import UnitCommitment:
-    Formulation,
-    KnuOstWat2018,
-    MorLatRam2013,
-    ShiftFactorsFormulation
-
-instance = UnitCommitment.read_benchmark(
-    "matpower/case118/2017-02-01",
-)
-
-model = UnitCommitment.build_model(
-    instance = instance,
-    optimizer = Cbc.Optimizer,
-    formulation = Formulation(
-        pwl_costs = KnuOstWat2018.PwlCosts(),
-        ramping = MorLatRam2013.Ramping(),
-        startup_costs = MorLatRam2013.StartupCosts(),
-        transmission = ShiftFactorsFormulation(
-            isf_cutoff = 0.005,
-            lodf_cutoff = 0.001,
-        ),
-    ),
-)
-```
-
-## Generating initial conditions
-
-When creating random unit commitment instances for benchmark purposes, it is often hard to compute, in advance, sensible initial conditions for all generators. Setting initial conditions naively (for example, making all generators initially off and producing no power) can easily cause the instance to become infeasible due to excessive ramping. Initial conditions can also make it hard to modify existing instances. For example, increasing the system load without carefully modifying the initial conditions may make the problem infeasible or unrealistically challenging to solve.
-
-To help with this issue, UC.jl provides a utility function which can generate feasible initial conditions by solving a single-period optimization problem, as shown below:
-
-```julia
-using Cbc
-using UnitCommitment
-
-# Read original instance
-instance = UnitCommitment.read("instance.json")
-
-# Generate initial conditions (in-place)
-UnitCommitment.generate_initial_conditions!(instance, Cbc.Optimizer)
-
-# Construct and solve optimization model
-model = UnitCommitment.build_model(
-    instance=instance,
-    optimizer=Cbc.Optimizer,
-)
-UnitCommitment.optimize!(model)
-```
-
-!!! warning
-
-    The function `generate_initial_conditions!` may return different initial conditions after each call, even if the same instance and the same optimizer is provided. The particular algorithm may also change in a future version of UC.jl. For these reasons, it is recommended that you generate initial conditions exactly once for each instance and store them for later use.
-    
-## Verifying solutions
-
-When developing new formulations, it is very easy to introduce subtle errors in the model that result in incorrect solutions. To help with this, UC.jl includes a utility function that verifies if a given solution is feasible, and, if not, prints all the validation errors it found. The implementation of this function is completely independent from the implementation of the optimization model, and therefore can be used to validate it. The function can also be used to verify solutions produced by other optimization packages, as long as they follow the [UC.jl data format](format.md).
-
-```julia
-using JSON
-using UnitCommitment
-
-# Read instance
-instance = UnitCommitment.read("instance.json")
-
-# Read solution (potentially produced by other packages) 
-solution = JSON.parsefile("solution.json")
-
-# Validate solution and print validation errors
-UnitCommitment.validate(instance, solution)
-```
-
-## Computing Locational Marginal Prices
-
-Locational marginal prices (LMPs) refer to the cost of supplying electricity at a particular location of the network. Multiple methods for computing LMPs have been proposed in the literature. UnitCommitment.jl implements two commonly-used methods: conventional LMPs and Approximated Extended LMPs (AELMPs). To compute LMPs for a given unit commitment instance, the `compute_lmp` function can be used, as shown in the examples below. The function accepts three arguments -- a solved SCUC model, an LMP method, and a linear optimizer -- and it returns a dictionary mapping `(bus_name, time)` to the marginal price.
-
-
-!!! warning
-
-    Most mixed-integer linear optimizers, such as `HiGHS`, `Gurobi` and `CPLEX` can be used with `compute_lmp`, with the notable exception of `Cbc`, which does not support dual value evaluations. If using `Cbc`, please provide `Clp` as the linear optimizer.
-
-### Conventional LMPs
-
-LMPs are conventionally computed by: (1) solving the SCUC model, (2) fixing all binary variables to their optimal values, and (3) re-solving the resulting linear programming model. In this approach, the LMPs are defined as the dual variables' values associated with the net injection constraints. The example below shows how to compute conventional LMPs for a given unit commitment instance. First, we build and optimize the SCUC model. Then, we call the `compute_lmp` function, providing as the second argument `ConventionalLMP()`.
-
-
-```julia
-using UnitCommitment
-using HiGHS
-
-import UnitCommitment: ConventionalLMP
-
-# Read benchmark instance
-instance = UnitCommitment.read_benchmark("matpower/case118/2018-01-01")
-
-# Build the model
-model = UnitCommitment.build_model(
-    instance = instance,
-    optimizer = HiGHS.Optimizer,
-)
-
-# Optimize the model
-UnitCommitment.optimize!(model)
-
-# Compute the LMPs using the conventional method
-lmp = UnitCommitment.compute_lmp(
-    model,
-    ConventionalLMP(),
-    optimizer = HiGHS.Optimizer,
-)
-
-# Access the LMPs
-# Example: "s1" is the scenario name, "b1" is the bus name, 1 is the first time slot
-@show lmp["s1","b1", 1]
-```
-
-### Approximate Extended LMPs
-
-Approximate Extended LMPs (AELMPs) are an alternative method to calculate locational marginal prices which attemps to minimize uplift payments. The method internally works by modifying the instance data in three ways: (1) it sets the minimum power output of each generator to zero, (2) it averages the start-up cost over the offer blocks for each generator, and (3) it relaxes all integrality constraints. To compute AELMPs, as shown in the example below, we call `compute_lmp` and provide `AELMP()` as the second argument.
-
-This method has two configurable parameters: `allow_offline_participation` and `consider_startup_costs`. If `allow_offline_participation = true`, then offline generators are allowed to participate in the pricing. If instead `allow_offline_participation = false`, offline generators are not allowed and therefore are excluded from the system. A solved UC model is optional if offline participation is allowed, but is required if not allowed. The method forces offline participation to be allowed if the UC model supplied by the user is not solved. For the second field, If `consider_startup_costs = true`, then start-up costs are integrated and averaged over each unit production; otherwise the production costs stay the same. By default, both fields are set to `true`.
-
-!!! warning
-
-    This approximation method is still under active research, and has several limitations. The implementation provided in the package is based on MISO Phase I only. It only supports fast start resources. More specifically, the minimum up/down time of all generators must be 1, the initial power of all generators must be 0, and the initial status of all generators must be negative. The method does not support time-varying start-up costs. The method does not support multiple scenarios. If offline participation is not allowed, AELMPs treats an asset to be  offline if it is never on throughout all time periods. 
-
-```julia
-using UnitCommitment
-using HiGHS
-
-import UnitCommitment: AELMP
-
-# Read benchmark instance
-instance = UnitCommitment.read_benchmark("matpower/case118/2017-02-01")
-
-# Build the model
-model = UnitCommitment.build_model(
-    instance = instance,
-    optimizer = HiGHS.Optimizer,
-)
-
-# Optimize the model
-UnitCommitment.optimize!(model)
-
-# Compute the AELMPs
-aelmp = UnitCommitment.compute_lmp(
-    model,
-    AELMP(
-        allow_offline_participation = false,
-        consider_startup_costs = true
-    ),
-    optimizer = HiGHS.Optimizer
-)
-
-# Access the AELMPs
-# Example: "s1" is the scenario name, "b1" is the bus name, 1 is the first time slot
-# Note: although scenario is supported, the query still keeps the scenario keys for consistency.
-@show aelmp["s1", "b1", 1]
-```
--- a/instances/README.md
+++ b/instances/README.md
@@ -0,0 +1,53 @@
+Instances
+=========
+
+UnitCommitment.jl provides a large collection of benchmark instances collected
+from the literature and converted to a common data format. If you use these instances in your research, we request that you cite UnitCommitment.jl, as well as the original sources, as listed below. [See documentation for more details](https://anl-ceeesa.github.io/UnitCommitment.jl/).
+
+References
+----------
+
+### UnitCommitment.jl
+
+* [UCJL] **Alinson S. Xavier, Feng Qiu.** "UnitCommitment.jl: A Julia/JuMP Optimization Package for Security-Constrained Unit Commitment". Zenodo (2020). [DOI: 10.5281/zenodo.4269874](https://doi.org/10.5281/zenodo.4269874)
+
+
+### MATPOWER
+
+* [MTPWR] **D. Zimmerman, C. E. Murillo-Sandnchez and R. J. Thomas.** "Matpower:  Steady-state  operations,  planning,  and  analysis  tools  forpower systems research and education", IEEE Transactions on PowerSystems, vol. 26, no. 1, pp. 12 –19, Feb. 2011. [DOI: 10.1109/TPWRS.2010.2051168](https://doi.org/10.1109/TPWRS.2010.2051168)
+
+* [PSTCA] **University of Washington, Dept. of Electrical Engineering.** "Power Systems Test Case Archive". Available at: <http://www.ee.washington.edu/research/pstca/> (Accessed: Nov 14, 2020)
+
+* [JoFlMa16] **C. Josz, S. Fliscounakis, J. Maeght, and P. Panciatici.** "AC Power Flow
+Data in MATPOWER and QCQP Format: iTesla, RTE Snapshots, and PEGASE". [ArXiv (2016)](https://arxiv.org/abs/1603.01533).
+
+* [FlPaCa13] **S. Fliscounakis, P. Panciatici, F. Capitanescu, and L. Wehenkel.**
+"Contingency ranking with respect to overloads in very large power
+systems taking into account uncertainty, preventive and corrective
+actions", Power Systems, IEEE Trans. on, (28)4:4909-4917, 2013.
+[DOI: 10.1109/TPWRS.2013.2251015](https://doi.org/10.1109/TPWRS.2013.2251015)
+
+
+### PGLIB-UC
+
+* [PGLIB] **Carleton Coffrin and Bernard Knueven.** "Power Grid Lib - Unit Commitment". Available at: <https://github.com/power-grid-lib/pglib-uc> (Accessed: Nov 14, 2020)
+
+* [KrHiOn12] **Eric Krall, Michael Higgins and Richard P. O’Neill.** "RTO unit commitment test system." Federal Energy Regulatory Commission. Available at: <https://www.ferc.gov/industries-data/electric/power-sales-and-markets/increasing-efficiency-through-improved-software-1> (Accessed: Nov 14, 2020)
+
+* [KnOsWa20] **Bernard Knueven, James Ostrowski and Jean-Paul Watson.** "On Mixed-Integer Programming Formulations for the Unit Commitment Problem". INFORMS Journal on Computing (2020). [DOI: 10.1287/ijoc.2019.0944](https://doi.org/10.1287/ijoc.2019.0944)
+
+### RTS-GMLC
+
+* https://github.com/GridMod/RTS-GMLC
+
+* [BaBlEh19] **Clayton Barrows, Aaron Bloom, Ali Ehlen, Jussi Ikaheimo, Jennie Jorgenson, Dheepak Krishnamurthy, Jessica Lau et al.** "The IEEE Reliability Test System: A Proposed 2019 Update." IEEE Transactions on Power Systems (2019). [DOI: 10.1109/TPWRS.2019.2925557](https://doi.org/10.1109/TPWRS.2019.2925557)
+
+### OR-LIB
+
+* [ORLIB] **J.E.Beasley.** "OR-Library: distributing test problems by electronic mail", Journal of the Operational Research Society 41(11) (1990). [DOI: 10.2307/2582903](https://doi.org/10.2307/2582903)
+
+* [FrGe06] **A. Frangioni, C. Gentile.** "Solving nonlinear single-unit commitment problems with ramping constraints" Operations Research 54(4), p. 767 - 775, 2006. [DOI: 10.1287/opre.1060.0309](https://doi.org/10.1287/opre.1060.0309)
+
+### Tejada19
+
+* [TeLuSa19] **D. A. Tejada-Arango, S. Lumbreras, P. Sanchez-Martin and A. Ramos.** "Which Unit-Commitment Formulation is Best? A Systematic Comparison," in IEEE Transactions on Power Systems. [DOI: 10.1109/TPWRS.2019.2962024](https://ieeexplore.ieee.org/document/8941313/).
--- a/instances/matpower/case118/2017-02-01.json.gz
+++ b/instances/matpower/case118/2017-02-01.json.gz
--- a/instances/matpower/case118/2017-08-01.json.gz
+++ b/instances/matpower/case118/2017-08-01.json.gz
--- a/instances/matpower/case1354pegase/2017-02-01.json.gz
+++ b/instances/matpower/case1354pegase/2017-02-01.json.gz
--- a/instances/matpower/case1354pegase/2017-08-01.json.gz
+++ b/instances/matpower/case1354pegase/2017-08-01.json.gz
--- a/instances/matpower/case13659pegase/2017-02-01.json.gz
+++ b/instances/matpower/case13659pegase/2017-02-01.json.gz
--- a/instances/matpower/case13659pegase/2017-08-01.json.gz
+++ b/instances/matpower/case13659pegase/2017-08-01.json.gz
--- a/instances/matpower/case14/2017-02-01.json.gz
+++ b/instances/matpower/case14/2017-02-01.json.gz
--- a/instances/matpower/case14/2017-08-01.json.gz
+++ b/instances/matpower/case14/2017-08-01.json.gz
--- a/instances/matpower/case1888rte/2017-02-01.json.gz
+++ b/instances/matpower/case1888rte/2017-02-01.json.gz
--- a/instances/matpower/case1888rte/2017-08-01.json.gz
+++ b/instances/matpower/case1888rte/2017-08-01.json.gz
--- a/instances/matpower/case1951rte/2017-02-01.json.gz
+++ b/instances/matpower/case1951rte/2017-02-01.json.gz
--- a/instances/matpower/case1951rte/2017-08-01.json.gz
+++ b/instances/matpower/case1951rte/2017-08-01.json.gz
--- a/instances/matpower/case2383wp/2017-02-01.json.gz
+++ b/instances/matpower/case2383wp/2017-02-01.json.gz
--- a/instances/matpower/case2383wp/2017-08-01.json.gz
+++ b/instances/matpower/case2383wp/2017-08-01.json.gz
--- a/instances/matpower/case2736sp/2017-02-01.json.gz
+++ b/instances/matpower/case2736sp/2017-02-01.json.gz
--- a/instances/matpower/case2736sp/2017-08-01.json.gz
+++ b/instances/matpower/case2736sp/2017-08-01.json.gz
--- a/instances/matpower/case2737sop/2017-02-01.json.gz
+++ b/instances/matpower/case2737sop/2017-02-01.json.gz
--- a/instances/matpower/case2737sop/2017-08-01.json.gz
+++ b/instances/matpower/case2737sop/2017-08-01.json.gz
--- a/instances/matpower/case2746wop/2017-02-01.json.gz
+++ b/instances/matpower/case2746wop/2017-02-01.json.gz
--- a/instances/matpower/case2746wop/2017-08-01.json.gz
+++ b/instances/matpower/case2746wop/2017-08-01.json.gz
--- a/instances/matpower/case2746wp/2017-02-01.json.gz
+++ b/instances/matpower/case2746wp/2017-02-01.json.gz
--- a/instances/matpower/case2746wp/2017-08-01.json.gz
+++ b/instances/matpower/case2746wp/2017-08-01.json.gz
--- a/instances/matpower/case2848rte/2017-02-01.json.gz
+++ b/instances/matpower/case2848rte/2017-02-01.json.gz
--- a/instances/matpower/case2848rte/2017-08-01.json.gz
+++ b/instances/matpower/case2848rte/2017-08-01.json.gz
--- a/instances/matpower/case2868rte/2017-02-01.json.gz
+++ b/instances/matpower/case2868rte/2017-02-01.json.gz
--- a/instances/matpower/case2868rte/2017-08-01.json.gz
+++ b/instances/matpower/case2868rte/2017-08-01.json.gz
--- a/instances/matpower/case2869pegase/2017-02-01.json.gz
+++ b/instances/matpower/case2869pegase/2017-02-01.json.gz
--- a/instances/matpower/case2869pegase/2017-08-01.json.gz
+++ b/instances/matpower/case2869pegase/2017-08-01.json.gz
--- a/instances/matpower/case30/2017-02-01.json.gz
+++ b/instances/matpower/case30/2017-02-01.json.gz
--- a/instances/matpower/case30/2017-08-01.json.gz
+++ b/instances/matpower/case30/2017-08-01.json.gz
--- a/instances/matpower/case300/2017-02-01.json.gz
+++ b/instances/matpower/case300/2017-02-01.json.gz
--- a/instances/matpower/case300/2017-08-01.json.gz
+++ b/instances/matpower/case300/2017-08-01.json.gz
--- a/instances/matpower/case3012wp/2017-02-01.json.gz
+++ b/instances/matpower/case3012wp/2017-02-01.json.gz
--- a/instances/matpower/case3012wp/2017-08-01.json.gz
+++ b/instances/matpower/case3012wp/2017-08-01.json.gz
--- a/instances/matpower/case3120sp/2017-02-01.json.gz
+++ b/instances/matpower/case3120sp/2017-02-01.json.gz
--- a/instances/matpower/case3120sp/2017-08-01.json.gz
+++ b/instances/matpower/case3120sp/2017-08-01.json.gz
--- a/instances/matpower/case3375wp/2017-02-01.json.gz
+++ b/instances/matpower/case3375wp/2017-02-01.json.gz
--- a/instances/matpower/case3375wp/2017-08-01.json.gz
+++ b/instances/matpower/case3375wp/2017-08-01.json.gz
--- a/instances/matpower/case57/2017-02-01.json.gz
+++ b/instances/matpower/case57/2017-02-01.json.gz
--- a/instances/matpower/case57/2017-08-01.json.gz
+++ b/instances/matpower/case57/2017-08-01.json.gz
--- a/instances/matpower/case6468rte/2017-02-01.json.gz
+++ b/instances/matpower/case6468rte/2017-02-01.json.gz
--- a/instances/matpower/case6468rte/2017-08-01.json.gz
+++ b/instances/matpower/case6468rte/2017-08-01.json.gz
--- a/instances/matpower/case6470rte/2017-02-01.json.gz
+++ b/instances/matpower/case6470rte/2017-02-01.json.gz
--- a/instances/matpower/case6470rte/2017-08-01.json.gz
+++ b/instances/matpower/case6470rte/2017-08-01.json.gz
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--- a/Show More
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Author	SHA1	Message	Date
Alinson S Xavier	675143967f	Fix some merge issues	2020-11-20 12:17:59 -06:00
Alinson S Xavier	ba9e086bea	Merge branch 'dev' into akazachk/formulations	2020-11-20 10:55:48 -06:00
Aleksandr Kazachkov	3baddf158a	Implement multiple formulations	2020-11-20 10:52:23 -06:00