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[GLOP] honor the MPSolver enable/suppress output

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Laurent Perron
2020-12-18 10:04:45 +01:00
parent 0496845d0c
commit 5a77249409
16 changed files with 243 additions and 133 deletions
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ortools/glop/samples/simple_glop_program.cc
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@@ -1,54 +1,75 @@
// Copyright 2010-2018 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.
// Minimal example to call the GLOP solver.
// [START program]
// [START import]
#include <iostream>
#include "ortools/glop/lp_solver.h"
#include "ortools/lp_data/lp_data.h"
#include "ortools/lp_data/lp_types.h"
// [END import]
namespace operations_research::glop {
int RunLinearExample() {
LinearProgram linear_program;
// Create the variables x and y.
ColIndex col_x = linear_program.FindOrCreateVariable("x");
linear_program.SetVariableBounds(col_x, 0.0, 1.0);
ColIndex col_y = linear_program.FindOrCreateVariable("y");
linear_program.SetVariableBounds(col_y, 0.0, 2.0);
int RunLinearExample() {
LinearProgram lp;
// Create the variables x and y.
ColIndex col_x = lp.FindOrCreateVariable("x");
lp.SetVariableBounds(col_x, 0.0, 1.0);
ColIndex col_y = lp.FindOrCreateVariable("y");
lp.SetVariableBounds(col_y, 0.0, 2.0);
// Create linear constraint: 0 <= x + y <= 2.
RowIndex row_r1 = linear_program.FindOrCreateConstraint("r1");
linear_program.SetConstraintBounds(row_r1, 0.0, 2.0);
linear_program.SetCoefficient(row_r1, col_x, 1);
linear_program.SetCoefficient(row_r1, col_y, 1);
// Create linear constraint: 0 <= x + y <= 2.
RowIndex row_r1 = lp.FindOrCreateConstraint("r1");
lp.SetConstraintBounds(row_r1, 0.0, 2.0);
lp.SetCoefficient(row_r1, col_x, 1);
lp.SetCoefficient(row_r1, col_y, 1);
// Create objective function: 3 * x + y.
linear_program.SetObjectiveCoefficient(col_x, 3);
linear_program.SetObjectiveCoefficient(col_y, 1);
linear_program.SetMaximizationProblem(true);
// Create objective function: 3 * x + y.
lp.SetObjectiveCoefficient(col_x, 3);
lp.SetObjectiveCoefficient(col_y, 1);
lp.SetMaximizationProblem(true);
linear_program.CleanUp();
lp.CleanUp();
std::cout << "Number of variables = " << linear_program.num_variables() << std::endl;
std::cout << "Number of constraints = " << linear_program.num_constraints() << std::endl;
std::cout << "Number of variables = " << lp.num_variables() << std::endl;
std::cout << "Number of constraints = " << lp.num_constraints() << std::endl;
LPSolver solver;
GlopParameters parameters;
parameters.set_provide_strong_optimal_guarantee(true);
solver.SetParameters(parameters);
LPSolver solver;
GlopParameters parameters;
parameters.set_provide_strong_optimal_guarantee(true);
solver.SetParameters(parameters);
ProblemStatus status = solver.Solve(linear_program);
if (status == ProblemStatus::OPTIMAL) {
std::cout << "Optimal solution found !" << std::endl;
// The objective value of the solution.
std::cout << "Optimal objective value = " << solver.GetObjectiveValue() << std::endl;
// The value of each variable in the solution.
const DenseRow& values = solver.variable_values();
std::cout << "Solution:" << std::endl
<< "x = " << values[col_x] << std::endl
<< ", y = " << values[col_y] << std::endl;
return 0;
} else
return 1;
ProblemStatus status = solver.Solve(lp);
if (status == ProblemStatus::OPTIMAL) {
std::cout << "Optimal solution found !" << std::endl;
// The objective value of the solution.
std::cout << "Optimal objective value = " << solver.GetObjectiveValue()
<< std::endl;
// The value of each variable in the solution.
const DenseRow& values = solver.variable_values();
std::cout << "Solution:" << std::endl
<< "x = " << values[col_x] << std::endl
<< ", y = " << values[col_y] << std::endl;
return EXIT_SUCCESS;
} else {
return EXIT_FAILURE;
}
}
} // namespace operations_research::glop
int main(int argc, char** argv) {
return operations_research::glop::RunLinearExample();
}
// [END program]