96 lines
3.4 KiB
C++
96 lines
3.4 KiB
C++
// Copyright 2010-2018 Google LLC
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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// Integer programming example that shows how to use the API.
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#include "ortools/base/commandlineflags.h"
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#include "ortools/base/logging.h"
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#include "ortools/linear_solver/linear_solver.h"
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namespace operations_research {
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void RunIntegerProgrammingExample(const std::string& solver_id) {
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LOG(INFO) << "---- Integer programming example with " << solver_id << " ----";
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MPSolver::OptimizationProblemType problem_type;
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if (!MPSolver::ParseSolverType(solver_id, &problem_type)) {
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LOG(INFO) << "Solver id " << solver_id << " not recognized";
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return;
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}
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if (!MPSolver::SupportsProblemType(problem_type)) {
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LOG(INFO) << "Supports for solver " << solver_id << " not linked in.";
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return;
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}
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MPSolver solver("IntegerProgrammingExample", problem_type);
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const double infinity = solver.infinity();
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// x and y are integer non-negative variables.
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MPVariable* const x = solver.MakeIntVar(0.0, infinity, "x");
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MPVariable* const y = solver.MakeIntVar(0.0, infinity, "y");
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// Maximize x + 10 * y.
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MPObjective* const objective = solver.MutableObjective();
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objective->SetCoefficient(x, 1);
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objective->SetCoefficient(y, 10);
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objective->SetMaximization();
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// x + 7 * y <= 17.5.
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MPConstraint* const c0 = solver.MakeRowConstraint(-infinity, 17.5);
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c0->SetCoefficient(x, 1);
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c0->SetCoefficient(y, 7);
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// x <= 3.5
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MPConstraint* const c1 = solver.MakeRowConstraint(-infinity, 3.5);
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c1->SetCoefficient(x, 1);
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c1->SetCoefficient(y, 0);
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LOG(INFO) << "Number of variables = " << solver.NumVariables();
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LOG(INFO) << "Number of constraints = " << solver.NumConstraints();
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const MPSolver::ResultStatus result_status = solver.Solve();
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// Check that the problem has an optimal solution.
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if (result_status != MPSolver::OPTIMAL) {
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LOG(FATAL) << "The problem does not have an optimal solution!";
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}
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LOG(INFO) << "Solution:";
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LOG(INFO) << "x = " << x->solution_value();
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LOG(INFO) << "y = " << y->solution_value();
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LOG(INFO) << "Optimal objective value = " << objective->Value();
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LOG(INFO) << "";
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LOG(INFO) << "Advanced usage:";
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LOG(INFO) << "Problem solved in " << solver.wall_time() << " milliseconds";
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LOG(INFO) << "Problem solved in " << solver.iterations() << " iterations";
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LOG(INFO) << "Problem solved in " << solver.nodes()
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<< " branch-and-bound nodes";
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}
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void RunAllExamples() {
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RunIntegerProgrammingExample("CBC");
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RunIntegerProgrammingExample("SAT");
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RunIntegerProgrammingExample("SCIP");
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RunIntegerProgrammingExample("GUROBI");
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RunIntegerProgrammingExample("GLPK");
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RunIntegerProgrammingExample("CPLEX");
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}
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} // namespace operations_research
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int main(int argc, char** argv) {
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google::InitGoogleLogging(argv[0]);
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absl::SetFlag(&FLAGS_logtostderr, true);
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absl::SetFlag(&FLAGS_log_prefix, false);
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gflags::ParseCommandLineFlags(&argc, &argv, true);
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operations_research::RunAllExamples();
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return 0;
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}
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