ortools-clone/examples/dotnet/cslinearprogramming.cs

// 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.

using System;
using Google.OrTools.LinearSolver;

public class CsLinearProgramming
{
    private static void RunLinearProgrammingExample(String solverType)
    {
        Console.WriteLine($"---- Linear programming example with {solverType} ----");

        Solver solver = Solver.CreateSolver(solverType);
        if (solver == null)
        {
            Console.WriteLine("Could not create solver " + solverType);
            return;
        }
        // x1, x2 and x3 are continuous non-negative variables.
        Variable x1 = solver.MakeNumVar(0.0, double.PositiveInfinity, "x1");
        Variable x2 = solver.MakeNumVar(0.0, double.PositiveInfinity, "x2");
        Variable x3 = solver.MakeNumVar(0.0, double.PositiveInfinity, "x3");

        // Maximize 10 * x1 + 6 * x2 + 4 * x3.
        Objective objective = solver.Objective();
        objective.SetCoefficient(x1, 10);
        objective.SetCoefficient(x2, 6);
        objective.SetCoefficient(x3, 4);
        objective.SetMaximization();

        // x1 + x2 + x3 <= 100.
        Constraint c0 = solver.MakeConstraint(double.NegativeInfinity, 100.0);
        c0.SetCoefficient(x1, 1);
        c0.SetCoefficient(x2, 1);
        c0.SetCoefficient(x3, 1);

        // 10 * x1 + 4 * x2 + 5 * x3 <= 600.
        Constraint c1 = solver.MakeConstraint(double.NegativeInfinity, 600.0);
        c1.SetCoefficient(x1, 10);
        c1.SetCoefficient(x2, 4);
        c1.SetCoefficient(x3, 5);

        // 2 * x1 + 2 * x2 + 6 * x3 <= 300.
        Constraint c2 = solver.MakeConstraint(double.NegativeInfinity, 300.0);
        c2.SetCoefficient(x1, 2);
        c2.SetCoefficient(x2, 2);
        c2.SetCoefficient(x3, 6);

        Console.WriteLine("Number of variables = " + solver.NumVariables());
        Console.WriteLine("Number of constraints = " + solver.NumConstraints());

        Solver.ResultStatus resultStatus = solver.Solve();

        // Check that the problem has an optimal solution.
        if (resultStatus != Solver.ResultStatus.OPTIMAL)
        {
            Console.WriteLine("The problem does not have an optimal solution!");
            return;
        }

        Console.WriteLine("Problem solved in " + solver.WallTime() + " milliseconds");

        // The objective value of the solution.
        Console.WriteLine("Optimal objective value = " + solver.Objective().Value());

        // The value of each variable in the solution.
        Console.WriteLine("x1 = " + x1.SolutionValue());
        Console.WriteLine("x2 = " + x2.SolutionValue());
        Console.WriteLine("x3 = " + x3.SolutionValue());

        Console.WriteLine("Advanced usage:");
        double[] activities = solver.ComputeConstraintActivities();

        Console.WriteLine("Problem solved in " + solver.Iterations() + " iterations");
        Console.WriteLine("x1: reduced cost = " + x1.ReducedCost());
        Console.WriteLine("x2: reduced cost = " + x2.ReducedCost());
        Console.WriteLine("x3: reduced cost = " + x3.ReducedCost());
        Console.WriteLine("c0: dual value = " + c0.DualValue());
        Console.WriteLine("    activity = " + activities[c0.Index()]);
        Console.WriteLine("c1: dual value = " + c1.DualValue());
        Console.WriteLine("    activity = " + activities[c1.Index()]);
        Console.WriteLine("c2: dual value = " + c2.DualValue());
        Console.WriteLine("    activity = " + activities[c2.Index()]);
    }

    private static void RunLinearProgrammingExampleNaturalApi(String solverType, bool printModel)
    {
        Console.WriteLine($"---- Linear programming example (Natural API) with {solverType} ----");

        Solver solver = Solver.CreateSolver(solverType);
        if (solver == null)
        {
            Console.WriteLine("Could not create solver " + solverType);
            return;
        }
        // x1, x2 and x3 are continuous non-negative variables.
        Variable x1 = solver.MakeNumVar(0.0, double.PositiveInfinity, "x1");
        Variable x2 = solver.MakeNumVar(0.0, double.PositiveInfinity, "x2");
        Variable x3 = solver.MakeNumVar(0.0, double.PositiveInfinity, "x3");

        solver.Maximize(10 * x1 + 6 * x2 + 4 * x3);
        Constraint c0 = solver.Add(x1 + x2 + x3 <= 100);
        Constraint c1 = solver.Add(10 * x1 + x2 * 4 + 5 * x3 <= 600);
        Constraint c2 = solver.Add(2 * x1 + 2 * x2 + 6 * x3 <= 300);

        Console.WriteLine("Number of variables = " + solver.NumVariables());
        Console.WriteLine("Number of constraints = " + solver.NumConstraints());

        if (printModel)
        {
            string model = solver.ExportModelAsLpFormat(false);
            Console.WriteLine(model);
        }

        Solver.ResultStatus resultStatus = solver.Solve();

        // Check that the problem has an optimal solution.
        if (resultStatus != Solver.ResultStatus.OPTIMAL)
        {
            Console.WriteLine("The problem does not have an optimal solution!");
            return;
        }

        Console.WriteLine("Problem solved in " + solver.WallTime() + " milliseconds");

        // The objective value of the solution.
        Console.WriteLine("Optimal objective value = " + solver.Objective().Value());

        // The value of each variable in the solution.
        Console.WriteLine("x1 = " + x1.SolutionValue());
        Console.WriteLine("x2 = " + x2.SolutionValue());
        Console.WriteLine("x3 = " + x3.SolutionValue());

        Console.WriteLine("Advanced usage:");
        double[] activities = solver.ComputeConstraintActivities();
        Console.WriteLine("Problem solved in " + solver.Iterations() + " iterations");
        Console.WriteLine("x1: reduced cost = " + x1.ReducedCost());
        Console.WriteLine("x2: reduced cost = " + x2.ReducedCost());
        Console.WriteLine("x3: reduced cost = " + x3.ReducedCost());
        Console.WriteLine("c0: dual value = " + c0.DualValue());
        Console.WriteLine("    activity = " + activities[c0.Index()]);
        Console.WriteLine("c1: dual value = " + c1.DualValue());
        Console.WriteLine("    activity = " + activities[c1.Index()]);
        Console.WriteLine("c2: dual value = " + c2.DualValue());
        Console.WriteLine("    activity = " + activities[c2.Index()]);
    }

    static void Main()
    {
        RunLinearProgrammingExample("GLOP");
        RunLinearProgrammingExample("GLPK_LP");
        RunLinearProgrammingExample("CLP");

        RunLinearProgrammingExampleNaturalApi("GLOP", true);
        RunLinearProgrammingExampleNaturalApi("GLPK_LP", false);
        RunLinearProgrammingExampleNaturalApi("CLP", false);
    }
}