101 lines
3.8 KiB
C#
101 lines
3.8 KiB
C#
// Copyright 2010-2011 Google
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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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using System;
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using Google.OrTools.LinearSolver;
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public class CsLinearProgramming
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{
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private static void RunLinearProgrammingExample(String solverType)
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{
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MPSolver solver = MPSolver.CreateSolver("IntegerProgramming", solverType);
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if (solver == null)
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{
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Console.WriteLine("Could not create solver " + solverType);
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return;
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}
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double infinity = MPSolver.Infinity();
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// x1, x2 and x3 are continuous non-negative variables.
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MPVariable x1 = solver.MakeNumVar(0.0, infinity, "x1");
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MPVariable x2 = solver.MakeNumVar(0.0, infinity, "x2");
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MPVariable x3 = solver.MakeNumVar(0.0, infinity, "x3");
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// Maximize 10 * x1 + 6 * x2 + 4 * x3.
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solver.SetObjectiveCoefficient(x1, 10);
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solver.SetObjectiveCoefficient(x2, 6);
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solver.SetObjectiveCoefficient(x3, 4);
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solver.SetMaximization();
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// x1 + x2 + x3 <= 100.
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MPConstraint c0 = solver.MakeConstraint(-infinity, 100.0);
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c0.SetCoefficient(x1, 1);
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c0.SetCoefficient(x2, 1);
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c0.SetCoefficient(x3, 1);
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// 10 * x1 + 4 * x2 + 5 * x3 <= 600.
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MPConstraint c1 = solver.MakeConstraint(-infinity, 600.0);
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c1.SetCoefficient(x1, 10);
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c1.SetCoefficient(x2, 4);
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c1.SetCoefficient(x3, 5);
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// 2 * x1 + 2 * x2 + 6 * x3 <= 300.
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MPConstraint c2 = solver.MakeConstraint(-infinity, 300.0);
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c2.SetCoefficient(x1, 2);
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c2.SetCoefficient(x2, 2);
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c2.SetCoefficient(x3, 6);
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Console.WriteLine("Number of variables = " + solver.NumVariables());
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Console.WriteLine("Number of constraints = " + solver.NumConstraints());
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int resultStatus = solver.Solve();
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// Check that the problem has an optimal solution.
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if (resultStatus != MPSolver.OPTIMAL) {
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Console.WriteLine("The problem does not have an optimal solution!");
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return;
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}
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Console.WriteLine("Problem solved in " + solver.WallTime() +
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" milliseconds");
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// The objective value of the solution.
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Console.WriteLine("Optimal objective value = " + solver.ObjectiveValue());
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// The value of each variable in the solution.
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Console.WriteLine("x1 = " + x1.SolutionValue());
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Console.WriteLine("x2 = " + x2.SolutionValue());
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Console.WriteLine("x3 = " + x3.SolutionValue());
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Console.WriteLine("Advanced usage:");
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Console.WriteLine("Problem solved in " + solver.Iterations() +
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" iterations");
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Console.WriteLine("x1: reduced cost = " + x1.ReducedCost());
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Console.WriteLine("x2: reduced cost = " + x2.ReducedCost());
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Console.WriteLine("x3: reduced cost = " + x3.ReducedCost());
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Console.WriteLine("c0: dual value = " + c0.DualValue());
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Console.WriteLine(" activity = " + c0.Activity());
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Console.WriteLine("c1: dual value = " + c1.DualValue());
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Console.WriteLine(" activity = " + c1.Activity());
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Console.WriteLine("c2: dual value = " + c2.DualValue());
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Console.WriteLine(" activity = " + c2.Activity());
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}
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static void Main()
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{
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Console.WriteLine("---- Linear programming example with GLPK ----");
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RunLinearProgrammingExample("GLPK_LINEAR_PROGRAMMING");
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Console.WriteLine("---- Linear programming example with CLP ----");
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RunLinearProgrammingExample("CLP_LINEAR_PROGRAMMING");
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}
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}
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