Replay

test/Project.toml

@@ -4,7 +4,9 @@ authors = ["Alinson S. Xavier <git@axavier.org>"]
 version = "0.1.0"
 
 [deps]
+CSV = "336ed68f-0bac-5ca0-87d4-7b16caf5d00b"
 Clp = "e2554f3b-3117-50c0-817c-e040a3ddf72d"
+DataFrames = "a93c6f00-e57d-5684-b7b6-d8193f3e46c0"
 Glob = "c27321d9-0574-5035-807b-f59d2c89b15c"
 HDF5 = "f67ccb44-e63f-5c2f-98bd-6dc0ccc4ba2f"
 HiGHS = "87dc4568-4c63-4d18-b0c0-bb2238e4078b"

test/src/BB/test_bb.jl

@@ -10,9 +10,12 @@ using Test
 using MIPLearn.BB
 using MIPLearn
 
+using CSV
+using DataFrames
+
 basepath = @__DIR__
 
-function bb_run(optimizer_name, optimizer; large = true)
+function bb_run(optimizer_name, optimizer; large=true)
     @testset "Solve ($optimizer_name)" begin
         @testset "interface" begin
             filename = "$FIXTURES/danoint.mps.gz"
@@ -25,7 +28,7 @@ function bb_run(optimizer_name, optimizer; large = true)
 
             status, obj = BB.solve_relaxation!(mip)
             @test status == :Optimal
-            @test round(obj, digits = 6) == 62.637280
+            @test round(obj, digits=6) == 62.637280
 
             @test BB.name(mip, mip.int_vars[1]) == "xab"
             @test BB.name(mip, mip.int_vars[2]) == "xac"
@@ -35,26 +38,26 @@ function bb_run(optimizer_name, optimizer; large = true)
             @test mip.int_vars_ub[1] == 1.0
 
             vals = BB.values(mip, mip.int_vars)
-            @test round(vals[1], digits = 6) == 0.046933
-            @test round(vals[2], digits = 6) == 0.000841
-            @test round(vals[3], digits = 6) == 0.248696
+            @test round(vals[1], digits=6) == 0.046933
+            @test round(vals[2], digits=6) == 0.000841
+            @test round(vals[3], digits=6) == 0.248696
 
             # Probe (up and down are feasible)
             probe_up, probe_down = BB.probe(mip, mip.int_vars[1], 0.5, 0.0, 1.0, 1_000_000)
-            @test round(probe_down, digits = 6) == 62.690000
-            @test round(probe_up, digits = 6) == 62.714100
+            @test round(probe_down, digits=6) == 62.690000
+            @test round(probe_up, digits=6) == 62.714100
 
             # Fix one variable to zero
             BB.set_bounds!(mip, mip.int_vars[1:1], [0.0], [0.0])
             status, obj = BB.solve_relaxation!(mip)
             @test status == :Optimal
-            @test round(obj, digits = 6) == 62.690000
+            @test round(obj, digits=6) == 62.690000
 
             # Fix one variable to one and another variable variable to zero
             BB.set_bounds!(mip, mip.int_vars[1:2], [1.0, 0.0], [1.0, 0.0])
             status, obj = BB.solve_relaxation!(mip)
             @test status == :Optimal
-            @test round(obj, digits = 6) == 62.714777
+            @test round(obj, digits=6) == 62.714777
 
             # Fix all binary variables to one, making problem infeasible
             N = length(mip.int_vars)
@@ -68,7 +71,7 @@ function bb_run(optimizer_name, optimizer; large = true)
             BB.set_bounds!(mip, mip.int_vars, zeros(N), ones(N))
             status, obj = BB.solve_relaxation!(mip)
             @test status == :Optimal
-            @test round(obj, digits = 6) == 62.637280
+            @test round(obj, digits=6) == 62.637280
         end
 
         @testset "varbranch" begin
@@ -82,8 +85,8 @@ function bb_run(optimizer_name, optimizer; large = true)
                     BB.StrongBranching(),
                     BB.ReliabilityBranching(),
                     BB.HybridBranching(),
-                    BB.StrongBranching(aggregation = :min),
-                    BB.ReliabilityBranching(aggregation = :min, collect = true),
+                    BB.StrongBranching(aggregation=:min),
+                    BB.ReliabilityBranching(aggregation=:min, collect=true),
                 ]
                     h5 = H5File("$FIXTURES/$instance.h5")
                     mip_lower_bound = h5.get_scalar("mip_lower_bound")
@@ -98,23 +101,23 @@ function bb_run(optimizer_name, optimizer; large = true)
                     @info optimizer_name, branch_rule, instance
                     @time BB.solve!(
                         mip,
-                        initial_primal_bound = mip_primal_bound,
-                        print_interval = 1,
-                        node_limit = 25,
-                        branch_rule = branch_rule,
+                        initial_primal_bound=mip_primal_bound,
+                        print_interval=1,
+                        node_limit=25,
+                        branch_rule=branch_rule,
                     )
                 end
             end
         end
 
         @testset "collect" begin
-            rule = BB.ReliabilityBranching(collect = true)
+            rule = BB.ReliabilityBranching(collect=true)
             BB.collect!(
                 optimizer,
                 "$FIXTURES/bell5.mps.gz",
-                node_limit = 100,
-                print_interval = 10,
-                branch_rule = rule,
+                node_limit=100,
+                print_interval=10,
+                branch_rule=rule,
             )
             n_sb = rule.stats.num_strong_branch_calls
             h5 = H5File("$FIXTURES/bell5.h5")
@@ -132,3 +135,67 @@ function test_bb()
     @time bb_run("HiGHS", optimizer_with_attributes(HiGHS.Optimizer))
     # @time bb_run("CPLEX", optimizer_with_attributes(CPLEX.Optimizer, "CPXPARAM_Threads" => 1))
 end
+
+function test_bb_replay()
+    rule_sb = BB.StrongBranching()
+    rule_rb = BB.ReliabilityBranching()
+    optimizer = optimizer_with_attributes(HiGHS.Optimizer)
+    filenames = [replace(f, ".h5" => "") for f in glob("test/fixtures/stab/*.h5")]
+    results_filename = "tmp.csv"
+
+    lk = ReentrantLock()
+    results = []
+
+    function push_result(r)
+        lock(lk) do
+            push!(results, r)
+            df = DataFrame()
+            for row in results
+                push!(df, row, cols=:union)
+            end
+            CSV.write(results_filename, df)
+        end
+    end
+
+    function solve(filename; replay=nothing, skip=false, rule)
+        has_replay = (replay !== nothing)
+        h5 = H5File("$filename.h5", "r")
+        mip_obj_bound = h5.get_scalar("mip_obj_bound")
+        @show filename
+        @show has_replay
+        h5.file.close()
+        mip = BB.init(optimizer)
+        BB.read!(mip, "$filename.mps.gz")
+        time_solve = @elapsed begin
+            pool, replay = BB.solve!(
+                mip,
+                initial_primal_bound=mip_obj_bound,
+                print_interval=100,
+                node_limit=1_000,
+                branch_rule=rule,
+                replay=replay,
+            )
+        end
+        if !skip
+            push_result(
+                Dict(
+                    "Filename" => filename,
+                    "Replay?" => has_replay,
+                    "Solve time (s)" => time_solve,
+                    "Relative MIP gap (%)" => round(pool.gap * 100, digits=3)
+                )
+            )
+        end
+        return replay
+    end
+
+    # Solve reference instance
+    replay = solve(filenames[1], skip=true, rule=rule_sb)
+
+    # Solve perturbations
+    for i in 2:6
+        solve(filenames[i], rule=rule_rb, replay=nothing)
+        solve(filenames[i], rule=rule_rb, replay=deepcopy(replay))
+    end
+    return
+end