// Copyright 2010-2022 Google LLC // Licensed under the Apache License, Version 2.0 (the "License"); // you may not use this file except in compliance with the License. // You may obtain a copy of the License at // // http://www.apache.org/licenses/LICENSE-2.0 // // Unless required by applicable law or agreed to in writing, software // distributed under the License is distributed on an "AS IS" BASIS, // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. // See the License for the specific language governing permissions and // limitations under the License. // This file solves a 2D Bin Packing problem. // It loads the size of the main rectangle, all available items (rectangles // too), and tries to fit all rectangles in the minimum numbers of bins (they // have the size of the main rectangle.) #include #include #include #include #include "absl/container/btree_set.h" #include "absl/flags/flag.h" #include "absl/log/check.h" #include "absl/strings/str_cat.h" #include "google/protobuf/text_format.h" #include "ortools/base/init_google.h" #include "ortools/base/logging.h" #include "ortools/base/path.h" #include "ortools/packing/binpacking_2d_parser.h" #include "ortools/packing/multiple_dimensions_bin_packing.pb.h" #include "ortools/sat/cp_model.h" #include "ortools/sat/cp_model.pb.h" #include "ortools/sat/cp_model_solver.h" #include "ortools/sat/sat_parameters.pb.h" #include "ortools/sat/util.h" ABSL_FLAG(std::string, input, "", "Input file."); ABSL_FLAG(int, instance, -1, "Instance number if the file."); ABSL_FLAG(std::string, params, "", "Sat parameters in text proto format."); ABSL_FLAG(int, max_bins, 0, "Maximum number of bins. The 0 default value implies the code will " "use some heuristics to compute this number."); ABSL_FLAG(bool, symmetry_breaking, true, "Use symmetry breaking constraints"); ABSL_FLAG(bool, use_global_cumulative, true, "Use a globalcumulative relaxation"); namespace operations_research { namespace sat { // Load a 2D bin packing problem and solve it. void LoadAndSolve(const std::string& file_name, int instance) { packing::BinPacking2dParser parser; if (!parser.Load2BPFile(file_name, instance)) { LOG(FATAL) << "Cannot read instance " << instance << " from file '" << file_name << "'"; } packing::MultipleDimensionsBinPackingProblem problem = parser.problem(); LOG(INFO) << "Successfully loaded instance " << instance << " from file '" << file_name << "'"; LOG(INFO) << "Instance has " << problem.items_size() << " items"; const auto box_dimensions = problem.box_shape().dimensions(); const int num_dimensions = box_dimensions.size(); const int num_items = problem.items_size(); // Non overlapping. if (num_dimensions == 1) { LOG(FATAL) << "One dimension is not supported."; } else if (num_dimensions != 2) { LOG(FATAL) << num_dimensions << " dimensions not supported."; } const int64_t area_of_one_bin = box_dimensions[0] * box_dimensions[1]; int64_t sum_of_items_area = 0; for (const auto& item : problem.items()) { CHECK_EQ(1, item.shapes_size()); const auto& shape = item.shapes(0); CHECK_EQ(2, shape.dimensions_size()); sum_of_items_area += shape.dimensions(0) * shape.dimensions(1); } const int64_t trivial_lb = CeilOfRatio(sum_of_items_area, area_of_one_bin); LOG(INFO) << "Trivial lower bound of the number of bins = " << trivial_lb; const int max_bins = absl::GetFlag(FLAGS_max_bins) == 0 ? trivial_lb * 2 : absl::GetFlag(FLAGS_max_bins); if (absl::GetFlag(FLAGS_max_bins) == 0) { LOG(INFO) << "Setting max_bins to " << max_bins; } CpModelBuilder cp_model; cp_model.SetName(absl::StrCat( "binpacking_2d_", file::Stem(absl::GetFlag(FLAGS_input)), "_", instance)); // We do not support multiple shapes per item. for (int item = 0; item < num_items; ++item) { const int num_shapes = problem.items(item).shapes_size(); CHECK_EQ(1, num_shapes); } // Create one Boolean variable per item and per bin. std::vector> item_to_bin(num_items); for (int item = 0; item < num_items; ++item) { item_to_bin[item].resize(max_bins); for (int b = 0; b < max_bins; ++b) { item_to_bin[item][b] = cp_model.NewBoolVar(); } } // Exactly one bin is selected for each item. for (int item = 0; item < num_items; ++item) { cp_model.AddExactlyOne(item_to_bin[item]); } absl::btree_set fixed_items; // We start by fixing big pairwise incompatible items. Each to its own bin. // See https://arxiv.org/pdf/1909.06835.pdf. for (int i = 0; i < num_items; ++i) { if (2 * problem.items(i).shapes(0).dimensions(0) > box_dimensions[0] && 2 * problem.items(i).shapes(0).dimensions(1) > box_dimensions[1]) { // Big items are pairwise incompatible. Just fix them in different bins. fixed_items.insert(i); } } auto items_are_incompatible = [&problem, &box_dimensions](int i1, int i2) { return (problem.items(i1).shapes(0).dimensions(0) + problem.items(i2).shapes(0).dimensions(0) > box_dimensions[0]) && (problem.items(i1).shapes(0).dimensions(1) + problem.items(i2).shapes(0).dimensions(1) > box_dimensions[1]); }; // This loop looks redundant with the loop above but the order we add the // items to fixed_items is important. for (int i = 0; i < num_items; ++i) { if (fixed_items.contains(i)) { continue; } bool incompatible_with_all = true; for (int item : fixed_items) { if (!items_are_incompatible(item, i)) { incompatible_with_all = false; break; } } if (incompatible_with_all) { fixed_items.insert(i); } } if (!fixed_items.empty()) { LOG(INFO) << fixed_items.size() << " items are pairwise incompatible"; } // Detect incompatible pairs of items and add conflict at the bin level. int num_incompatible_pairs = 0; for (int i1 = 0; i1 + 1 < num_items; ++i1) { for (int i2 = i1 + 1; i2 < num_items; ++i2) { if (fixed_items.contains(i1) && fixed_items.contains(i2)) { // Both are already fixed to different bins. continue; } if (!items_are_incompatible(i1, i2)) { continue; } if (num_incompatible_pairs == 0 && fixed_items.empty()) { // If nothing is already fixed, fix the first incompatible pair to break // symmetry. fixed_items.insert(i1); fixed_items.insert(i2); } num_incompatible_pairs++; for (int b = 0; b < max_bins; ++b) { cp_model.AddAtMostOne({item_to_bin[i1][b], item_to_bin[i2][b]}); } } } if (num_incompatible_pairs > 0) { LOG(INFO) << num_incompatible_pairs << " incompatible pairs of items"; } // Fix the fixed_items to the first fixed_items.size() bins. CHECK_LT(fixed_items.size(), max_bins) << "Infeasible problem, increase max_bins"; int count = 0; for (const int item : fixed_items) { cp_model.FixVariable(item_to_bin[item][count], true); ++count; } // Manages positions and sizes for each item. std::vector>> interval_by_item_bin_dimension(num_items); std::vector> starts_by_dimension(num_items); for (int item = 0; item < num_items; ++item) { interval_by_item_bin_dimension[item].resize(max_bins); starts_by_dimension[item].resize(num_dimensions); for (int b = 0; b < max_bins; ++b) { interval_by_item_bin_dimension[item][b].resize(num_dimensions); for (int dim = 0; dim < num_dimensions; ++dim) { const int64_t dimension = box_dimensions[dim]; const int64_t size = problem.items(item).shapes(0).dimensions(dim); IntVar start; if (b == 0) { start = cp_model.NewIntVar({0, dimension - size}); starts_by_dimension[item][dim] = start; } else { start = starts_by_dimension[item][dim]; } interval_by_item_bin_dimension[item][b][dim] = cp_model.NewOptionalFixedSizeIntervalVar(start, size, item_to_bin[item][b]); } } } // Non overlapping. LOG(INFO) << "Box size: " << box_dimensions[0] << "*" << box_dimensions[1]; for (int b = 0; b < max_bins; ++b) { NoOverlap2DConstraint no_overlap_2d = cp_model.AddNoOverlap2D(); for (int item = 0; item < num_items; ++item) { no_overlap_2d.AddRectangle(interval_by_item_bin_dimension[item][b][0], interval_by_item_bin_dimension[item][b][1]); } } // Objective variable. const IntVar obj = cp_model.NewIntVar({trivial_lb, max_bins}); // Global cumulative. if (absl::GetFlag(FLAGS_use_global_cumulative)) { DCHECK_EQ(num_dimensions, 2); for (int dim = 0; dim < num_dimensions; ++dim) { const int other_size = box_dimensions[1 - dim]; CumulativeConstraint cumul = cp_model.AddCumulative(obj * other_size); for (int item = 0; item < num_items; ++item) { const int size = problem.items(item).shapes(0).dimensions(dim); const int demand = problem.items(item).shapes(0).dimensions(1 - dim); cumul.AddDemand(cp_model.NewFixedSizeIntervalVar( starts_by_dimension[item][dim], size), demand); } } } // Maintain one Boolean variable per bin that indicates if the bin is used // or not. std::vector bin_is_used(max_bins); for (int b = 0; b < max_bins; ++b) { bin_is_used[b] = cp_model.NewBoolVar(); // Link bin_is_used[i] with the items in bin i. std::vector all_items_in_bin; for (int item = 0; item < num_items; ++item) { cp_model.AddImplication(item_to_bin[item][b], bin_is_used[b]); all_items_in_bin.push_back(item_to_bin[item][b]); } cp_model.AddBoolOr(all_items_in_bin).OnlyEnforceIf(bin_is_used[b]); } // Objective definition. cp_model.Minimize(obj); for (int b = trivial_lb; b + 1 < max_bins; ++b) { cp_model.AddGreaterOrEqual(obj, b + 1).OnlyEnforceIf(bin_is_used[b]); cp_model.AddImplication(bin_is_used[b + 1], bin_is_used[b]); } if (absl::GetFlag(FLAGS_symmetry_breaking)) { // First sort the items not yet fixed by area. std::vector not_placed_items; for (int item = 0; item < num_items; ++item) { if (!fixed_items.contains(item)) { not_placed_items.push_back(item); } } std::sort(not_placed_items.begin(), not_placed_items.end(), [&problem](int a, int b) { return problem.items(a).shapes(0).dimensions(0) * problem.items(a).shapes(0).dimensions(1) > problem.items(b).shapes(0).dimensions(0) * problem.items(b).shapes(0).dimensions(1); }); // Symmetry breaking: i-th biggest item is in bin <= i for the first // max_bins items. int first_empty_bin = fixed_items.size(); for (const int item : not_placed_items) { if (first_empty_bin + 1 >= max_bins) break; for (int b = first_empty_bin + 1; b < max_bins; ++b) { cp_model.FixVariable(item_to_bin[item][b], false); } ++first_empty_bin; } } // Setup parameters. SatParameters parameters; parameters.set_log_search_progress(true); // Parse the --params flag. if (!absl::GetFlag(FLAGS_params).empty()) { CHECK(google::protobuf::TextFormat::MergeFromString( absl::GetFlag(FLAGS_params), ¶meters)) << absl::GetFlag(FLAGS_params); } // If number of workers is >= 16 and < 24, we prefer replacing // objective_lb_search by objective_shaving_search. if (parameters.num_workers() >= 16 && parameters.num_workers() < 24) { parameters.add_ignore_subsolvers("objective_lb_search"); parameters.add_extra_subsolvers("objective_shaving_search"); } // We rely on the solver default logging to log the number of bins. const CpSolverResponse response = SolveWithParameters(cp_model.Build(), parameters); } } // namespace sat } // namespace operations_research int main(int argc, char** argv) { absl::SetFlag(&FLAGS_stderrthreshold, 0); InitGoogle(argv[0], &argc, &argv, true); if (absl::GetFlag(FLAGS_input).empty()) { LOG(FATAL) << "Please supply a data file with --input="; } if (absl::GetFlag(FLAGS_instance) == -1) { LOG(FATAL) << "Please supply a valid instance number with --instance="; } operations_research::sat::LoadAndSolve(absl::GetFlag(FLAGS_input), absl::GetFlag(FLAGS_instance)); return EXIT_SUCCESS; }