Files
ortools-clone/ortools/math_opt/examples/linear_programming.cc
2021-04-11 12:05:38 +02:00

115 lines
4.1 KiB
C++

// 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 <iostream>
#include <limits>
#include <string>
#include <vector>
#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<double>::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<Variable> x;
for (int j = 0; j < 3; j++) {
x.push_back(
optimizer.AddContinuousVariable(0.0, kInf, absl::StrCat("x", j)));
}
// Constraints
std::vector<LinearConstraint> 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;
}