Wrapper for the Mixed Integer Linear Minimization Oracle (#135)

examples/approx_planted_point.jl

@@ -9,21 +9,10 @@ using Distributions
 import MathOptInterface
 const MOI = MathOptInterface
 
-
 n = 20
 diffi = Random.rand(Bool, n) * 0.6 .+ 0.3
 
-@testset "Approximate planted point" begin
-    o = SCIP.Optimizer()
-    MOI.set(o, MOI.Silent(), true)
-    MOI.empty!(o)
-    x = MOI.add_variables(o, n)
-    for xi in x
-        MOI.add_constraint(o, xi, MOI.GreaterThan(0.0))
-        MOI.add_constraint(o, xi, MOI.LessThan(1.0))
-        MOI.add_constraint(o, xi, MOI.ZeroOne()) # or MOI.Integer()
-    end
-    lmo = FrankWolfe.MathOptLMO(o)
+@testset "Approximate planted point - Integer" begin
 
     function f(x)
         return 0.5 * sum((x[i] - diffi[i])^2 for i in eachindex(x))
@@ -32,8 +21,39 @@ diffi = Random.rand(Bool, n) * 0.6 .+ 0.3
         @. storage = x - diffi
     end
 
-    x, _, result = Boscia.solve(f, grad!, lmo, verbose=true)
+    @testset "Using SCIP" begin
+        o = SCIP.Optimizer()
+        MOI.set(o, MOI.Silent(), true)
+        MOI.empty!(o)
+        x = MOI.add_variables(o, n)
+        for xi in x
+            MOI.add_constraint(o, xi, MOI.GreaterThan(0.0))
+            MOI.add_constraint(o, xi, MOI.LessThan(1.0))
+            MOI.add_constraint(o, xi, MOI.ZeroOne()) # or MOI.Integer()
+        end
+        lmo = FrankWolfe.MathOptLMO(o)
+
+        x, _, result = Boscia.solve(f, grad!, lmo, verbose=true)
+
+        @test x == round.(diffi)
+        @test isapprox(f(x), f(result[:raw_solution]), atol=1e-6, rtol=1e-3)
+    end
 
-    @test x == round.(diffi)
-    @test isapprox(f(x), f(result[:raw_solution]), atol=1e-6, rtol=1e-3)
+    @testset "Using Cube LMO" begin
+        int_vars = []
+        bin_vars = collect(1:n)
+
+        bounds = Boscia.IntegerBounds()
+        for i in 1:n 
+            push!(bounds, (i, MOI.GreaterThan(0.0)))
+            push!(bounds, (i, MOI.LessThan(1.0)))
+        end
+        blmo = Boscia.CubeBLMO(n, int_vars, bin_vars, bounds)
+
+        x, _, result = Boscia.solve(f, grad!, blmo, verbose =true)
+
+        @test x == round.(diffi)
+        @test isapprox(f(x), f(result[:raw_solution]), atol=1e-6, rtol=1e-3)
+    end
 end
+

examples/birkhoff.jl

@@ -118,8 +118,9 @@ x, _, _ = Boscia.solve(f, grad!, lmo, verbose=true)
     x, _, result_baseline = Boscia.solve(f, grad!, lmo, verbose=true)
     @test f(x) <= f(result_baseline[:raw_solution]) + 1e-6
     lmo = build_birkhoff_lmo()
-    branching_strategy = Boscia.PartialStrongBranching(20, 1e-4, HiGHS.Optimizer())
-    MOI.set(branching_strategy.optimizer, MOI.Silent(), true)
+    blmo = Boscia.MathOptBLMO(HiGHS.Optimizer())
+    branching_strategy = Boscia.PartialStrongBranching(10, 1e-3, blmo)
+    MOI.set(branching_strategy.bounded_lmo.o, MOI.Silent(), true)
     x_strong, _, result_strong =
         Boscia.solve(f, grad!, lmo, verbose=true, branching_strategy=branching_strategy)
     @test f(x) ≈ f(x_strong)

examples/strong_branching_portfolio.jl

@@ -69,8 +69,9 @@ end
     @test dot(ai, x) <= bi + 1e-6
     @test f(x) <= f(result_baseline[:raw_solution]) + 1e-6
 
-    branching_strategy = Boscia.PartialStrongBranching(10, 1e-3, HiGHS.Optimizer())
-    MOI.set(branching_strategy.optimizer, MOI.Silent(), true)
+    blmo = Boscia.MathOptBLMO(HiGHS.Optimizer())
+    branching_strategy = Boscia.PartialStrongBranching(10, 1e-3, blmo)
+    MOI.set(branching_strategy.bounded_lmo.o, MOI.Silent(), true)
 
     lmo = prepare_portfolio_lmo()
     x, _, result_strong_branching =

src/Boscia.jl

@@ -1,6 +1,8 @@
 module Boscia
 
 using FrankWolfe
+import FrankWolfe: compute_extreme_point
+export compute_extreme_point
 using Random
 using SCIP
 import MathOptInterface
@@ -12,17 +14,20 @@ const MOIU = MOI.Utilities
 
 import MathOptSetDistances as MOD
 
+include("integer_bounds.jl")
+include("blmo_interface.jl")
 include("time_tracking_lmo.jl")
-include("bounds.jl")
 include("frank_wolfe_variants.jl")
+include("build_lmo.jl")
 include("node.jl")
 include("custom_bonobo.jl")
 include("callbacks.jl")
 include("problem.jl")
-include("infeasible_pairwise.jl")
 include("heuristics.jl")
 include("strong_branching.jl")
 include("utilities.jl")
 include("interface.jl")
+include("MOI_bounded_oracle.jl")
+include("cube_blmo.jl")
 
 end # module