87 lines
2.7 KiB
C++
87 lines
2.7 KiB
C++
// Copyright 2010-2022 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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// [START program]
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// [START import]
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#include <iostream>
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#include "ortools/linear_solver/linear_solver.h"
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// [END import]
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namespace operations_research {
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void LinearProgrammingExample() {
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// [START solver]
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std::unique_ptr<MPSolver> solver(MPSolver::CreateSolver("SCIP"));
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if (!solver) {
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LOG(WARNING) << "SCIP solver unavailable.";
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return;
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}
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// [END solver]
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// [START variables]
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const double infinity = solver->infinity();
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// x and y are non-negative variables.
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MPVariable* const x = solver->MakeNumVar(0.0, infinity, "x");
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MPVariable* const y = solver->MakeNumVar(0.0, infinity, "y");
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LOG(INFO) << "Number of variables = " << solver->NumVariables();
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// [END variables]
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// [START constraints]
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// x + 2*y <= 14.
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MPConstraint* const c0 = solver->MakeRowConstraint(-infinity, 14.0);
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c0->SetCoefficient(x, 1);
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c0->SetCoefficient(y, 2);
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// 3*x - y >= 0.
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MPConstraint* const c1 = solver->MakeRowConstraint(0.0, infinity);
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c1->SetCoefficient(x, 3);
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c1->SetCoefficient(y, -1);
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// x - y <= 2.
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MPConstraint* const c2 = solver->MakeRowConstraint(-infinity, 2.0);
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c2->SetCoefficient(x, 1);
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c2->SetCoefficient(y, -1);
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LOG(INFO) << "Number of constraints = " << solver->NumConstraints();
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// [END constraints]
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// [START objective]
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// Objective function: 3x + 4y.
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MPObjective* const objective = solver->MutableObjective();
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objective->SetCoefficient(x, 3);
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objective->SetCoefficient(y, 4);
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objective->SetMaximization();
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// [END objective]
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// [START solve]
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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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// [END solve]
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// [START print_solution]
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LOG(INFO) << "Solution:";
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LOG(INFO) << "Optimal objective value = " << objective->Value();
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LOG(INFO) << x->name() << " = " << x->solution_value();
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LOG(INFO) << y->name() << " = " << y->solution_value();
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// [END print_solution]
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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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operations_research::LinearProgrammingExample();
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return EXIT_SUCCESS;
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}
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// [END program]
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