94 lines
3.3 KiB
C++
94 lines
3.3 KiB
C++
// Copyright 2010-2021 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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// Simple linear programming example
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#include <iostream>
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#include <limits>
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#include "absl/flags/parse.h"
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#include "absl/flags/usage.h"
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#include "absl/status/statusor.h"
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#include "absl/time/time.h"
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#include "ortools/base/logging.h"
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#include "ortools/math_opt/cpp/math_opt.h"
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namespace {
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using ::operations_research::math_opt::MathOpt;
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using ::operations_research::math_opt::Result;
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using ::operations_research::math_opt::SolveParametersProto;
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using ::operations_research::math_opt::SOLVER_TYPE_GSCIP;
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using ::operations_research::math_opt::SolveResultProto;
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using ::operations_research::math_opt::SolveStatsProto;
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using ::operations_research::math_opt::Variable;
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using ::operations_research::math_opt::VariableMap;
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constexpr double kInf = std::numeric_limits<double>::infinity();
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// Model and solve the problem:
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// max x + 10 * y
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// s.t. x + 7 * y <= 17.5
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// x <= 3.5
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// x in {0.0, 1.0, 2.0, ...,
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// y in {0.0, 1.0, 2.0, ...,
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//
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void SolveSimpleMIP() {
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MathOpt optimizer(SOLVER_TYPE_GSCIP, "Integer programming example");
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// Variables
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const Variable x = optimizer.AddIntegerVariable(0.0, kInf, "x");
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const Variable y = optimizer.AddIntegerVariable(0.0, kInf, "y");
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// Constraints
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optimizer.AddLinearConstraint(x + 7 * y <= 17.5, "c1");
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optimizer.AddLinearConstraint(x <= 3.5, "c2");
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// Objective
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optimizer.objective().Maximize(x + 10 * y);
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std::cout << "Num variables: " << optimizer.num_variables() << std::endl;
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std::cout << "Num constraints: " << optimizer.num_linear_constraints()
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<< std::endl;
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const Result result = optimizer.Solve(SolveParametersProto()).value();
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// Check for warnings.
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for (const auto& warning : result.warnings) {
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LOG(ERROR) << "Solver warning: " << warning << std::endl;
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}
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// Check that the problem has an optimal solution.
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QCHECK_EQ(result.termination_reason, SolveResultProto::OPTIMAL)
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<< "Failed to find an optimal solution: " << result.termination_detail;
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std::cout << "Problem solved in " << result.solve_time() << std::endl;
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std::cout << "Objective value: " << result.objective_value() << std::endl;
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const double x_val = result.variable_values().at(x);
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const double y_val = result.variable_values().at(y);
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std::cout << "Variable values: [x=" << x_val << ", y=" << y_val << "]"
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<< std::endl;
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const SolveStatsProto& stat = result.solve_stats;
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std::cout << "Simplex iterations: " << stat.simplex_iterations() << std::endl;
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std::cout << "Barrier iterations: " << stat.barrier_iterations() << std::endl;
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std::cout << "Branch and bound nodes: " << stat.node_count() << std::endl;
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}
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} // namespace
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int main(int argc, char** argv) {
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google::InitGoogleLogging(argv[0]);
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absl::ParseCommandLine(argc, argv);
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SolveSimpleMIP();
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return 0;
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}
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