Implement MIPLearn solution method

Project.toml

@@ -13,13 +13,15 @@ JSON = "682c06a0-de6a-54ab-a142-c8b1cf79cde6"
 JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 Logging = "56ddb016-857b-54e1-b83d-db4d58db5568"
+MPI = "da04e1cc-30fd-572f-bb4f-1f8673147195"
 MathOptInterface = "b8f27783-ece8-5eb3-8dc8-9495eed66fee"
 PackageCompiler = "9b87118b-4619-50d2-8e1e-99f35a4d4d9d"
 Printf = "de0858da-6303-5e67-8744-51eddeeeb8d7"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"
+Requires = "ae029012-a4dd-5104-9daa-d747884805df"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
+Suppressor = "fd094767-a336-5f1f-9728-57cf17d0bbfb"
 TimerOutputs = "a759f4b9-e2f1-59dc-863e-4aeb61b1ea8f"
-MPI = "da04e1cc-30fd-572f-bb4f-1f8673147195"
 
 [compat]
 DataStructures = "0.18"
@@ -27,8 +29,8 @@ Distributions = "0.25"
 GZip = "0.5"
 JSON = "0.21"
 JuMP = "1"
-MathOptInterface = "1"
 MPI = "0.20"
+MathOptInterface = "1"
 PackageCompiler = "1"
-julia = "1"
 TimerOutputs = "0.5"
+julia = "1"

src/UnitCommitment.jl

@@ -4,6 +4,8 @@
 
 module UnitCommitment
 
+using Requires
+
 using Base: String
 
 include("instance/structs.jl")
@@ -72,4 +74,11 @@ include("lmp/conventional.jl")
 include("lmp/aelmp.jl")
 include("market/market.jl")
 
+function __init__()
+    @require MIPLearn = "2b1277c3-b477-4c49-a15e-7ba350325c68" begin
+        include("solution/methods/MIPLearn/structs.jl")
+        include("solution/methods/MIPLearn/miplearn.jl")
+    end
+end
+
 end

src/solution/methods/MIPLearn/miplearn.jl

@@ -0,0 +1,71 @@
+# 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.
+
+using .MIPLearn
+using Suppressor
+using JuMP
+
+function _build_ucjl_model(instance, method)
+    if instance isa String
+        instance = UnitCommitment.read(instance)
+    end
+    model = UnitCommitment.build_model(
+        instance = instance,
+        optimizer = method.optimizer,
+        variable_names = true,
+    )
+    write_to_file(model, "/tmp/model.lp")
+    return JumpModel(model)
+end
+
+function _set_default_collectors!(method::MIPLearnMethod)
+    method.collectors = [BasicCollector()]
+    return
+end
+
+function _set_default_solver!(method::MIPLearnMethod)
+    KNN = MIPLearn.pyimport("sklearn.neighbors").KNeighborsClassifier
+    method.solver = LearningSolver(
+        components = [
+            MemorizingPrimalComponent(
+                clf = KNN(n_neighbors = 30),
+                extractor = H5FieldsExtractor(
+                    instance_fields = ["static_var_obj_coeffs"],
+                ),
+                constructor = MergeTopSolutions(30, [0.0, 1.0]),
+                action = FixVariables(),
+            ),
+        ],
+    )
+    return
+end
+
+function collect!(filenames::Vector, method::MIPLearnMethod)
+    build(x) = _build_ucjl_model(x, method)
+    if method.collectors === nothing
+        _set_default_collectors!(method)
+    end
+    for c in method.collectors
+        c.collect(filenames, build)
+    end
+end
+
+function fit!(filenames::Vector, method::MIPLearnMethod)
+    if method.solver === nothing
+        _set_default_solver!(method)
+    end
+    return method.solver.fit(filenames)
+end
+
+function optimize!(filename::AbstractString, method::MIPLearnMethod)
+    build(x) = _build_ucjl_model(x, method)
+    method.solver.optimize(filename, build)
+    return
+end
+
+function optimize!(instance::UnitCommitmentInstance, method::MIPLearnMethod)
+    model = _build_ucjl_model(instance, method)
+    method.solver.optimize(model)
+    return
+end

src/solution/methods/MIPLearn/structs.jl

@@ -0,0 +1,11 @@
+# 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.
+
+using Suppressor
+
+Base.@kwdef mutable struct MIPLearnMethod
+    optimizer::Any
+    collectors::Any = nothing
+    solver::Any = nothing
+end

test/Project.toml

@@ -13,6 +13,7 @@ JSON = "682c06a0-de6a-54ab-a142-c8b1cf79cde6"
 JuMP = "4076af6c-e467-56ae-b986-b466b2749572"
 JuliaFormatter = "98e50ef6-434e-11e9-1051-2b60c6c9e899"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
+MIPLearn = "2b1277c3-b477-4c49-a15e-7ba350325c68"
 MPI = "da04e1cc-30fd-572f-bb4f-1f8673147195"
 MathOptInterface = "b8f27783-ece8-5eb3-8dc8-9495eed66fee"
 Random = "9a3f8284-a2c9-5f02-9a11-845980a1fd5c"

test/src/UnitCommitmentT.jl

@@ -1,6 +1,7 @@
 module UnitCommitmentT
 
 using JuliaFormatter
+using MIPLearn
 using UnitCommitment
 using Test
 
@@ -16,6 +17,7 @@ include("solution/methods/ProgressiveHedging/usage_test.jl")
 include("solution/methods/TimeDecomposition/initial_status_test.jl")
 include("solution/methods/TimeDecomposition/optimize_test.jl")
 include("solution/methods/TimeDecomposition/update_solution_test.jl")
+include("solution/methods/MIPLearn/usage_test.jl")
 include("transform/initcond_test.jl")
 include("transform/slice_test.jl")
 include("transform/randomize/XavQiuAhm2021_test.jl")
@@ -46,6 +48,7 @@ function runtests()
         solution_methods_TimeDecomposition_initial_status_test()
         solution_methods_TimeDecomposition_optimize_test()
         solution_methods_TimeDecomposition_update_solution_test()
+        solution_methods_MIPLearn_usage_test()
         transform_initcond_test()
         transform_slice_test()
         transform_randomize_XavQiuAhm2021_test()

test/src/solution/methods/MIPLearn/usage_test.jl

@@ -0,0 +1,20 @@
+# 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.
+
+using HiGHS
+
+function solution_methods_MIPLearn_usage_test()
+    dirname = mktempdir()
+    cp(fixture("case14.json.gz"), "$dirname/case14.json.gz")
+    train_data = ["$dirname/case14.json.gz"]
+
+    method = UnitCommitment.MIPLearnMethod(optimizer = HiGHS.Optimizer)
+    UnitCommitment.collect!(train_data, method)
+    UnitCommitment.fit!(train_data, method)
+    UnitCommitment.optimize!(train_data[1], method)
+
+    instance = UnitCommitment.read(train_data[1])
+    UnitCommitment.optimize!(instance, method)
+    return
+end