// Copyright 2010-2021 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. // Simple linear programming example #include #include #include #include #include "absl/flags/parse.h" #include "absl/flags/usage.h" #include "ortools/base/logging.h" #include "absl/status/statusor.h" #include "absl/strings/str_cat.h" #include "absl/strings/str_join.h" #include "absl/time/time.h" #include "ortools/math_opt/cpp/math_opt.h" namespace { using ::operations_research::math_opt::LinearConstraint; using ::operations_research::math_opt::LinearExpression; using ::operations_research::math_opt::MathOpt; using ::operations_research::math_opt::Result; using ::operations_research::math_opt::SolveParametersProto; using ::operations_research::math_opt::SOLVER_TYPE_GLOP; using ::operations_research::math_opt::SolveResultProto; using ::operations_research::math_opt::SolveStatsProto; using ::operations_research::math_opt::Sum; using ::operations_research::math_opt::Variable; constexpr double kInf = std::numeric_limits::infinity(); // Model and solve the problem: // max 10 * x0 + 6 * x1 + 4 * x2 // s.t. 10 * x0 + 4 * x1 + 5 * x2 <= 600 // 2 * x0 + 2 * x1 + 6 * x2 <= 300 // x0 + x1 + x2 <= 100 // x0 in [0, infinity) // x1 in [0, infinity) // x2 in [0, infinity) // void SolveSimpleLp() { MathOpt optimizer(SOLVER_TYPE_GLOP, "Linear programming example"); // Variables std::vector x; for (int j = 0; j < 3; j++) { x.push_back( optimizer.AddContinuousVariable(0.0, kInf, absl::StrCat("x", j))); } // Constraints std::vector constraints; constraints.push_back(optimizer.AddLinearConstraint( 10 * x[0] + 4 * x[1] + 5 * x[2] <= 600, "c1")); constraints.push_back(optimizer.AddLinearConstraint( 2 * x[0] + 2 * x[1] + 6 * x[2] <= 300, "c2")); // sum(x[i]) <= 100 constraints.push_back(optimizer.AddLinearConstraint(Sum(x) <= 100, "c3")); // Objective optimizer.objective().Maximize(10 * x[0] + 6 * x[1] + 4 * x[2]); std::cout << "Num variables: " << optimizer.num_variables() << std::endl; std::cout << "Num constraints: " << optimizer.num_linear_constraints() << std::endl; const Result result = optimizer.Solve(SolveParametersProto()).value(); // Check for warnings. for (const auto& warning : result.warnings) { LOG(ERROR) << "Solver warning: " << warning << std::endl; } // Check that the problem has an optimal solution. QCHECK_EQ(result.termination_reason, SolveResultProto::OPTIMAL) << "Failed to find an optimal solution: " << result.termination_detail; std::cout << "Problem solved in " << result.solve_time() << std::endl; std::cout << "Objective value: " << result.objective_value() << std::endl; std::cout << "Variable values: [" << absl::StrJoin(result.variable_values().Values(x), ", ") << "]" << std::endl; std::cout << "Constraint duals: [" << absl::StrJoin(result.dual_values().Values(constraints), ", ") << "]" << std::endl; std::cout << "Reduced costs: [" << absl::StrJoin(result.reduced_costs().Values(x), ", ") << "]" << std::endl; const SolveStatsProto& stat = result.solve_stats; std::cout << "Simplex iterations: " << stat.simplex_iterations() << std::endl; std::cout << "Barrier iterations: " << stat.barrier_iterations() << std::endl; // TODO(user): add basis statuses when they are included in Result } } // namespace int main(int argc, char** argv) { google::InitGoogleLogging(argv[0]); absl::ParseCommandLine(argc, argv); SolveSimpleLp(); return 0; }