Merge pull request #16 from fontanf/bugfix/onedimensional-not-anytime

Bugfix/onedimensional not anytime
fontanf · Apr 19, 2024 · a7f09f0 · a7f09f0
2 parents b95d82f + ad93e85
commit a7f09f0
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Showing 26 changed files with 225 additions and 21 deletions.
diff --git a/data/onedimensional/BUILD b/data/onedimensional/BUILD
@@ -0,0 +1,6 @@
+filegroup(
+        name = "onedimensional",
+        srcs = glob(["**/*.csv"]),
+        visibility = ["//visibility:public"],
+)
+
diff --git a/data/onedimensional/users/2023-08-01_bins.csv b/data/onedimensional/users/2023-08-01_bins.csv
@@ -0,0 +1,4 @@
+ID,X,COST,COPIES
+0,3000,3000,10000
+1,7000,8008,10000
+2,10000,10000,10000
diff --git a/data/onedimensional/users/2023-08-01_items.csv b/data/onedimensional/users/2023-08-01_items.csv
@@ -0,0 +1,11 @@
+ID,X,COPIES
+0,9809,236
+1,739,4
+2,4624,241
+3,3589,884
+4,8369,48
+5,3236,348
+6,3470,302
+7,732,299
+8,365,613
+9,2056,299
diff --git a/data/onedimensional/users/2024-04-06_t0_bins.csv b/data/onedimensional/users/2024-04-06_t0_bins.csv
@@ -0,0 +1,3 @@
+ID,X,COST,COPIES
+0,3000,3000,3000
+1,7000,7000,5000
diff --git a/data/onedimensional/users/2024-04-06_t0_items.csv b/data/onedimensional/users/2024-04-06_t0_items.csv
@@ -0,0 +1,5 @@
+ID,X,COPIES,NESTING_LENGTH
+0,290,1,-5
+1,1496,2,-5
+2,2751,2,-5
+3,3351,2,-5
diff --git a/data/onedimensional/users/2024-04-06_t1_bins.csv b/data/onedimensional/users/2024-04-06_t1_bins.csv
@@ -0,0 +1,9 @@
+ID,X,COST,COPIES
+0,1400,1400,30000
+1,3900,3900,30000
+2,900,900,30000
+3,4500,4500,30000
+4,2900,2900,30000
+5,3400,3400,30000
+6,1900,1900,30000
+7,2400,2400,30000
diff --git a/data/onedimensional/users/2024-04-06_t1_items.csv b/data/onedimensional/users/2024-04-06_t1_items.csv
@@ -0,0 +1,7 @@
+ID,X,COPIES,NESTING_LENGTH
+0,1768,3,-4
+1,1764,5,-4
+2,964,2,-4
+3,864,1,-4
+4,1774,1,-4
+5,764,1,-4
diff --git a/data/onedimensional/users/2024-04-06_t2_bins.csv b/data/onedimensional/users/2024-04-06_t2_bins.csv
@@ -0,0 +1,9 @@
+ID,X,COST,COPIES
+0,3900,3900,5000
+1,1900,1900,5000
+2,2400,2400,5000
+3,3400,3400,5000
+4,4500,4500,5000
+5,900,900,5000
+6,1400,1400,5000
+7,2900,2900,5000
diff --git a/data/onedimensional/users/2024-04-06_t2_items.csv b/data/onedimensional/users/2024-04-06_t2_items.csv
@@ -0,0 +1,3 @@
+ID,X,COPIES,NESTING_LENGTH
+0,2379,1,-4
+1,1164,1,-4
diff --git a/data/onedimensional/users/2024-04-06_t3_bins.csv b/data/onedimensional/users/2024-04-06_t3_bins.csv
@@ -0,0 +1,2 @@
+ID,X,COST,COPIES
+0,4000,4000,32767
diff --git a/data/onedimensional/users/2024-04-06_t3_items.csv b/data/onedimensional/users/2024-04-06_t3_items.csv
@@ -0,0 +1,17 @@
+ID,X,COPIES,NESTING_LENGTH
+0,1022,1,-4
+1,1022,1,-4
+2,922,3,-4
+3,512,3,-4
+4,920,5,-4
+5,510,5,-4
+6,415,1,-4
+7,415,1,-4
+8,315,2,-4
+9,315,2,-4
+10,265,1,-4
+11,265,1,-4
+12,925,1,-4
+13,515,1,-4
+14,215,1,-4
+15,215,1,-4
diff --git a/data/onedimensional/users/2024-04-07_bins.csv b/data/onedimensional/users/2024-04-07_bins.csv
@@ -0,0 +1,3 @@
+ID,X,COST,COPIES
+0,3000,3000,3000
+1,7000,7000,5000
diff --git a/data/onedimensional/users/2024-04-07_items.csv b/data/onedimensional/users/2024-04-07_items.csv
@@ -0,0 +1,5 @@
+ID,X,COPIES,NESTING_LENGTH
+0,290,1,-5
+1,1496,2,-5
+2,2751,2,-5
+3,3351,2,-5
diff --git a/data/onedimensional/users/2024-04-09_bins.csv b/data/onedimensional/users/2024-04-09_bins.csv
@@ -0,0 +1,3 @@
+ID,X,COST,COPIES
+0,6950,6950,8
+1,7000,3500,2
diff --git a/data/onedimensional/users/2024-04-09_items.csv b/data/onedimensional/users/2024-04-09_items.csv
@@ -0,0 +1,2 @@
+ID,X,COPIES,NESTING_LENGTH
+0,2408,8,-4
diff --git a/packingsolver/algorithms/column_generation.hpp b/packingsolver/algorithms/column_generation.hpp
@@ -1,8 +1,8 @@
 /**
- * Column Generation algorithm
+ * Column generation algorithm
  *
- * Algorithm for Variable-sized Bin Packing, Bin Packing and (Multiple)
- * Knapsack Problems.
+ * Algorithm for variable-sized bin packing, bin packing and (multiple)
+ * knapsack problems.
  *
  * Input:
  * - m bin types with lower bounds lᵢ, upper bounds uᵢ and costs cᵢ (i = 0..m)

diff --git a/packingsolver/algorithms/sequential_value_correction.hpp b/packingsolver/algorithms/sequential_value_correction.hpp
@@ -1,23 +1,23 @@
 /**
- * Sequential Value Correction algorithm
+ * Sequential value correction algorithm
  *
- * Algorithm for Multiple Knapsack, Bin Packing and Variable-sized Bin Packing
+ * Algorithm for multiple knapsack, bin packing and variable-sized bin packing
  * problems.
  *
- * For Variable-sized Bin Packing, it doesn't handle the minimum number of
+ * For variable-sized bin packing, it doesn't handle the minimum number of
  * copies of each bin type to use.
  *
- * The algorithm solves a Single Knapsack subproblem for each bin until either
+ * The algorithm solves a single knapsack subproblem for each bin until either
  * all items are packed, or there is no bin left.
  * Then, it restarts but increases the profits of the items that where packed
  * in bins with high waste, such that they get packed earlier and hopefully
  * generate less waste.
  *
- * For Variable-sized Bin Packing, this algorithm should require less
+ * For Variable-sized bin packing, this algorithm should require less
  * computational effort to find a good solution than the other algorithms for
  * this objective.
- * For Multiple Knapsck and Bin Packing, it is useful for boxstacks problem
- * type since, in this case, Tree Search might not be applied directly to get a
+ * For multiple knapsck and bin packing, it is useful for boxstacks problem
+ * type since, in this case, tree search might not be applied directly to get a
  * good solution.
  *
  * Some references from which this implementation is inspired:
@@ -109,7 +109,9 @@ SequentialValueCorrectionOutput<Instance, Solution> sequential_value_correction(
     }
 
     for (output.number_of_iterations = 0;; output.number_of_iterations++) {
-        //std::cout << "it " << output.number_of_iterations << std::endl;
+        //std::cout << "it " << output.number_of_iterations
+        //    << " / " << parameters.maximum_number_of_iterations
+        //    << std::endl;
 
         // Check maximum number of iterations.
         if (parameters.maximum_number_of_iterations != -1

diff --git a/packingsolver/onedimensional/BUILD b/packingsolver/onedimensional/BUILD
@@ -58,7 +58,7 @@ cc_test(
                 "@boost//:filesystem",
         ],
         copts = STDCPP,
-        #data = ["//data/onedimensional:onedimensional"],
+        data = ["//data/onedimensional:onedimensional"],
         timeout = "short",
 )
 
diff --git a/packingsolver/onedimensional/main.cpp b/packingsolver/onedimensional/main.cpp
@@ -83,7 +83,10 @@ int main(int argc, char *argv[])
         ("sequential-value-correction-subproblem-queue-size,", po::value<NodeId>(), "set sequential value correction subproblem queue size")
         ("sequential-value-correction-number-of-iterations,", po::value<Counter>(), "set sequential value correction number of iterations")
         ("column-generation-subproblem-queue-size,", po::value<NodeId>(), "set column generation subproblem queue size")
+        ("not-anytime-tree-search-queue-size,", po::value<Counter>(), "")
+        ("not-anytime-sequential-single-knapsack-subproblem-queue-size,", po::value<Counter>(), "")
         ("not-anytime-sequential-value-correction-number-of-iterations,", po::value<Counter>(), "")
+        ("not-anytime-dichotomic-search-subproblem-queue-size,", po::value<Counter>(), "")
         ;
     po::variables_map vm;
     po::store(po::parse_command_line(argc, argv, desc), vm);
@@ -133,6 +136,8 @@ int main(int argc, char *argv[])
 
     OptimizeParameters parameters;
     read_args(parameters, vm);
+    if (vm.count("optimization-mode"))
+        parameters.optimization_mode = vm["optimization-mode"].as<OptimizationMode>();
 
     if (vm.count("use-tree-search"))
         parameters.use_tree_search = vm["use-tree-search"].as<bool>();
@@ -149,8 +154,14 @@ int main(int argc, char *argv[])
         parameters.sequential_value_correction_subproblem_queue_size = vm["sequential-value-correction-subproblem-queue-size"].as<NodeId>();
     if (vm.count("column-generation-subproblem-queue-size"))
         parameters.column_generation_subproblem_queue_size = vm["column-generation-subproblem-queue-size"].as<NodeId>();
+    if (vm.count("not-anytime-tree-search-queue-size"))
+        parameters.not_anytime_tree_search_queue_size = vm["not-anytime-tree-search-queue-size"].as<Counter>();
+    if (vm.count("not-anytime-sequential-single-knapsack-subproblem-queue-size"))
+        parameters.not_anytime_sequential_single_knapsack_subproblem_queue_size = vm["not-anytime-sequential-single-knapsack-subproblem-queue-size"].as<Counter>();
     if (vm.count("not-anytime-sequential-value-correction-number-of-iterations"))
         parameters.not_anytime_sequential_value_correction_number_of_iterations = vm["not-anytime-sequential-value-correction-number-of-iterations"].as<Counter>();
+    if (vm.count("not-anytime-dichotomic-search-subproblem-queue-size"))
+        parameters.not_anytime_dichotomic_search_subproblem_queue_size = vm["not-anytime-dichotomic-search-subproblem-queue-size"].as<Counter>();
     const onedimensional::Output output = optimize(instance, parameters);
 
     if (vm.count("certificate"))

diff --git a/packingsolver/onedimensional/onedimensional_test.cpp b/packingsolver/onedimensional/onedimensional_test.cpp
@@ -19,3 +19,105 @@ TEST(OneDimensional, BinCopies)
     EXPECT_EQ(solution.number_of_bins(), 2);
     EXPECT_EQ(solution.bin_copies(0), 2);
 }
+
+TEST(OneDimensional, Users_2023_08_01)
+{
+    InstanceBuilder instance_builder;
+    instance_builder.set_objective(packingsolver::Objective::VariableSizedBinPacking);
+    fs::path directory = fs::path("data") / "onedimensional" / "users";
+    instance_builder.read_item_types((directory / "2023-08-01_items.csv").string());
+    instance_builder.read_bin_types((directory / "2023-08-01_bins.csv").string());
+    Instance instance = instance_builder.build();
+
+    OptimizeParameters optimize_parameters;
+    optimize_parameters.optimization_mode = packingsolver::OptimizationMode::NotAnytime;
+    optimize_parameters.use_column_generation = 1;
+    Output output = optimize(instance, optimize_parameters);
+
+    EXPECT_EQ(output.solution_pool.best().cost(), 1020 * 10000 + 65 * 8008);
+}
+
+TEST(OneDimensional, Users_2024_04_06_t1)
+{
+    InstanceBuilder instance_builder;
+    instance_builder.set_objective(packingsolver::Objective::VariableSizedBinPacking);
+    fs::path directory = fs::path("data") / "onedimensional" / "users";
+    instance_builder.read_item_types((directory / "2024-04-06_t1_items.csv").string());
+    instance_builder.read_bin_types((directory / "2024-04-06_t1_bins.csv").string());
+    Instance instance = instance_builder.build();
+
+    OptimizeParameters optimize_parameters;
+    optimize_parameters.optimization_mode = packingsolver::OptimizationMode::NotAnytime;
+    optimize_parameters.use_column_generation = 1;
+    Output output = optimize(instance, optimize_parameters);
+
+    EXPECT_EQ(output.solution_pool.best().cost(), 19900);
+}
+
+TEST(OneDimensional, Users_2024_04_06_t2)
+{
+    InstanceBuilder instance_builder;
+    instance_builder.set_objective(packingsolver::Objective::VariableSizedBinPacking);
+    fs::path directory = fs::path("data") / "onedimensional" / "users";
+    instance_builder.read_item_types((directory / "2024-04-06_t2_items.csv").string());
+    instance_builder.read_bin_types((directory / "2024-04-06_t2_bins.csv").string());
+    Instance instance = instance_builder.build();
+
+    OptimizeParameters optimize_parameters;
+    optimize_parameters.optimization_mode = packingsolver::OptimizationMode::NotAnytime;
+    optimize_parameters.use_column_generation = 1;
+    Output output = optimize(instance, optimize_parameters);
+
+    EXPECT_EQ(output.solution_pool.best().cost(), 3800);
+}
+
+TEST(OneDimensional, Users_2024_04_06_t3)
+{
+    InstanceBuilder instance_builder;
+    instance_builder.set_objective(packingsolver::Objective::VariableSizedBinPacking);
+    fs::path directory = fs::path("data") / "onedimensional" / "users";
+    instance_builder.read_item_types((directory / "2024-04-06_t3_items.csv").string());
+    instance_builder.read_bin_types((directory / "2024-04-06_t3_bins.csv").string());
+    Instance instance = instance_builder.build();
+
+    OptimizeParameters optimize_parameters;
+    optimize_parameters.optimization_mode = packingsolver::OptimizationMode::NotAnytime;
+    optimize_parameters.use_tree_search = 1;
+    Output output = optimize(instance, optimize_parameters);
+
+    EXPECT_EQ(output.solution_pool.best().cost(), 20000);
+}
+
+TEST(OneDimensional, Users_2024_04_07)
+{
+    InstanceBuilder instance_builder;
+    instance_builder.set_objective(packingsolver::Objective::VariableSizedBinPacking);
+    fs::path directory = fs::path("data") / "onedimensional" / "users";
+    instance_builder.read_item_types((directory / "2024-04-07_items.csv").string());
+    instance_builder.read_bin_types((directory / "2024-04-07_bins.csv").string());
+    Instance instance = instance_builder.build();
+
+    OptimizeParameters optimize_parameters;
+    optimize_parameters.optimization_mode = packingsolver::OptimizationMode::NotAnytime;
+    optimize_parameters.use_dichotomic_search = 1;
+    Output output = optimize(instance, optimize_parameters);
+
+    EXPECT_EQ(output.solution_pool.best().cost(), 19000);
+}
+
+TEST(OneDimensional, Users_2024_04_09)
+{
+    InstanceBuilder instance_builder;
+    instance_builder.set_objective(packingsolver::Objective::VariableSizedBinPacking);
+    fs::path directory = fs::path("data") / "onedimensional" / "users";
+    instance_builder.read_item_types((directory / "2024-04-09_items.csv").string());
+    instance_builder.read_bin_types((directory / "2024-04-09_bins.csv").string());
+    Instance instance = instance_builder.build();
+
+    OptimizeParameters optimize_parameters;
+    optimize_parameters.optimization_mode = packingsolver::OptimizationMode::NotAnytime;
+    optimize_parameters.use_sequential_value_correction = 1;
+    Output output = optimize(instance, optimize_parameters);
+
+    EXPECT_EQ(output.solution_pool.best().cost(), 20900);
+}
diff --git a/packingsolver/onedimensional/optimize.cpp b/packingsolver/onedimensional/optimize.cpp
@@ -121,7 +121,7 @@ void optimize_sequential_single_knapsack(
     for (Counter queue_size = 1;;) {
 
         if (parameters.optimization_mode != OptimizationMode::Anytime)
-            queue_size = parameters.not_anytime_dichotomic_search_subproblem_beam_size;
+            queue_size = parameters.not_anytime_dichotomic_search_subproblem_queue_size;
 
         SequentialValueCorrectionFunction<Instance, Solution> kp_solve
             = [&parameters, &queue_size](const Instance& kp_instance)
@@ -212,7 +212,7 @@ void optimize_dichotomic_search(
     for (Counter queue_size = 1;;) {
 
         if (parameters.optimization_mode != OptimizationMode::Anytime)
-            queue_size = parameters.not_anytime_dichotomic_search_subproblem_beam_size;
+            queue_size = parameters.not_anytime_dichotomic_search_subproblem_queue_size;
 
         DichotomicSearchFunction<Instance, Solution> bpp_solve
             = [&parameters, &queue_size](const Instance& bpp_instance)

diff --git a/packingsolver/onedimensional/optimize.hpp b/packingsolver/onedimensional/optimize.hpp
@@ -85,7 +85,7 @@ struct OptimizeParameters: packingsolver::Parameters<Instance, Solution>
      * Size of the queue in the bin packing subproblem of the dichotomic search
      * algorithm.
      */
-    NodeId not_anytime_dichotomic_search_subproblem_beam_size = 256;
+    NodeId not_anytime_dichotomic_search_subproblem_queue_size = 256;
 };
 
 const Output optimize(

diff --git a/packingsolver/rectangle/optimize.cpp b/packingsolver/rectangle/optimize.cpp
@@ -144,7 +144,7 @@ void optimize_sequential_single_knapsack(
     for (Counter queue_size = 1;;) {
 
         if (parameters.optimization_mode != OptimizationMode::Anytime)
-            queue_size = parameters.not_anytime_dichotomic_search_subproblem_beam_size;
+            queue_size = parameters.not_anytime_dichotomic_search_subproblem_queue_size;
 
         SequentialValueCorrectionFunction<Instance, Solution> kp_solve
             = [&parameters, &queue_size](const Instance& kp_instance)
@@ -235,7 +235,7 @@ void optimize_dichotomic_search(
     for (Counter queue_size = 1;;) {
 
         if (parameters.optimization_mode != OptimizationMode::Anytime)
-            queue_size = parameters.not_anytime_dichotomic_search_subproblem_beam_size;
+            queue_size = parameters.not_anytime_dichotomic_search_subproblem_queue_size;
 
         DichotomicSearchFunction<Instance, Solution> bpp_solve
             = [&parameters, &queue_size](const Instance& bpp_instance)

diff --git a/packingsolver/rectangle/optimize.hpp b/packingsolver/rectangle/optimize.hpp
@@ -88,7 +88,7 @@ struct OptimizeParameters: packingsolver::Parameters<Instance, Solution>
      * Size of the queue in the bin packing subproblem of the dichotomic search
      * algorithm.
      */
-    NodeId not_anytime_dichotomic_search_subproblem_beam_size = 1024;
+    NodeId not_anytime_dichotomic_search_subproblem_queue_size = 1024;
 };
 
 const Output optimize(

diff --git a/packingsolver/rectangleguillotine/optimize.cpp b/packingsolver/rectangleguillotine/optimize.cpp
@@ -130,7 +130,7 @@ void optimize_sequential_single_knapsack(
     for (Counter queue_size = 1;;) {
 
         if (parameters.optimization_mode != OptimizationMode::Anytime)
-            queue_size = parameters.not_anytime_dichotomic_search_subproblem_beam_size;
+            queue_size = parameters.not_anytime_dichotomic_search_subproblem_queue_size;
 
         SequentialValueCorrectionFunction<Instance, Solution> kp_solve
             = [&parameters, &queue_size](const Instance& kp_instance)
@@ -221,7 +221,7 @@ void optimize_dichotomic_search(
     for (Counter queue_size = 1;;) {
 
         if (parameters.optimization_mode != OptimizationMode::Anytime)
-            queue_size = parameters.not_anytime_dichotomic_search_subproblem_beam_size;
+            queue_size = parameters.not_anytime_dichotomic_search_subproblem_queue_size;
 
         DichotomicSearchFunction<Instance, Solution> bpp_solve
             = [&parameters, &queue_size](const Instance& bpp_instance)

diff --git a/packingsolver/rectangleguillotine/optimize.hpp b/packingsolver/rectangleguillotine/optimize.hpp
@@ -85,7 +85,7 @@ struct OptimizeParameters: packingsolver::Parameters<Instance, Solution>
      * Size of the queue in the bin packing subproblem of the dichotomic search
      * algorithm.
      */
-    NodeId not_anytime_dichotomic_search_subproblem_beam_size = 256;
+    NodeId not_anytime_dichotomic_search_subproblem_queue_size = 256;
 };
 
 const Output optimize(