#include <iostream>
#include <ortools/glop/lp_solver.h>
#include <ortools/lp_data/lp_data.h>
#include <ortools/lp_data/lp_types.h>

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);

    // 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 objective function: 3 * x + y.
    linear_program.SetObjectiveCoefficient(col_x, 3);
    linear_program.SetObjectiveCoefficient(col_y, 1);
    linear_program.SetMaximizationProblem(true);

    linear_program.CleanUp();

    std::cout << "Number of variables = " << linear_program.num_variables() << std::endl;
    std::cout << "Number of constraints = " << linear_program.num_constraints() << std::endl;

    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;
  }
}  // namespace operations_research::glop

int main(int argc, char** argv) {
  return operations_research::glop::RunLinearExample();
}