Add a glop sample
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54
ortools/glop/samples/simple_glop_program.cc
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54
ortools/glop/samples/simple_glop_program.cc
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#include <iostream>
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#include "ortools/glop/lp_solver.h"
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#include "ortools/lp_data/lp_data.h"
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#include "ortools/lp_data/lp_types.h"
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namespace operations_research::glop {
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int RunLinearExample() {
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LinearProgram linear_program;
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// Create the variables x and y.
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ColIndex col_x = linear_program.FindOrCreateVariable("x");
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linear_program.SetVariableBounds(col_x, 0.0, 1.0);
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ColIndex col_y = linear_program.FindOrCreateVariable("y");
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linear_program.SetVariableBounds(col_y, 0.0, 2.0);
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// Create linear constraint: 0 <= x + y <= 2.
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RowIndex row_r1 = linear_program.FindOrCreateConstraint("r1");
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linear_program.SetConstraintBounds(row_r1, 0.0, 2.0);
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linear_program.SetCoefficient(row_r1, col_x, 1);
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linear_program.SetCoefficient(row_r1, col_y, 1);
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// Create objective function: 3 * x + y.
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linear_program.SetObjectiveCoefficient(col_x, 3);
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linear_program.SetObjectiveCoefficient(col_y, 1);
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linear_program.SetMaximizationProblem(true);
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linear_program.CleanUp();
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std::cout << "Number of variables = " << linear_program.num_variables() << std::endl;
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std::cout << "Number of constraints = " << linear_program.num_constraints() << std::endl;
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LPSolver solver;
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GlopParameters parameters;
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parameters.set_provide_strong_optimal_guarantee(true);
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solver.SetParameters(parameters);
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ProblemStatus status = solver.Solve(linear_program);
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if (status == ProblemStatus::OPTIMAL) {
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std::cout << "Optimal solution found !" << std::endl;
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// The objective value of the solution.
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std::cout << "Optimal objective value = " << solver.GetObjectiveValue() << std::endl;
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// The value of each variable in the solution.
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const DenseRow& values = solver.variable_values();
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std::cout << "Solution:" << std::endl
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<< "x = " << values[col_x] << std::endl
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<< ", y = " << values[col_y] << std::endl;
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return 0;
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} else
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return 1;
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}
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} // namespace operations_research::glop
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int main(int argc, char** argv) {
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return operations_research::glop::RunLinearExample();
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}
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