2018-11-26 17:30:10 +01:00
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// Copyright 2010-2018 Google LLC
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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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// [START program]
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2020-05-26 09:30:42 +02:00
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package com.google.ortools.linearsolver.samples;
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2018-11-26 17:30:10 +01:00
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import com.google.ortools.linearsolver.MPConstraint;
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import com.google.ortools.linearsolver.MPObjective;
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import com.google.ortools.linearsolver.MPSolver;
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import com.google.ortools.linearsolver.MPVariable;
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/** Simple linear programming example.*/
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public class LinearProgrammingExample {
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static {
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System.loadLibrary("jniortools");
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}
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public static void main(String[] args) throws Exception {
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// [START solver]
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MPSolver solver = new MPSolver(
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"LinearProgrammingExample", MPSolver.OptimizationProblemType.GLOP_LINEAR_PROGRAMMING);
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// [END solver]
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// [START variables]
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2019-02-02 17:40:11 +01:00
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double infinity = java.lang.Double.POSITIVE_INFINITY;
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2018-11-26 17:30:10 +01:00
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// x and y are continuous non-negative variables.
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MPVariable x = solver.makeNumVar(0.0, infinity, "x");
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MPVariable y = solver.makeNumVar(0.0, infinity, "y");
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System.out.println("Number of variables = " + solver.numVariables());
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// [END variables]
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// [START constraints]
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// x + 2*y <= 14.
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MPConstraint c0 = solver.makeConstraint(-infinity, 14.0, "c0");
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c0.setCoefficient(x, 1);
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c0.setCoefficient(y, 2);
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// 3*x - y >= 0.
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MPConstraint c1 = solver.makeConstraint(0.0, infinity, "c1");
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c1.setCoefficient(x, 3);
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c1.setCoefficient(y, -1);
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// x - y <= 2.
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MPConstraint c2 = solver.makeConstraint(-infinity, 2.0, "c2");
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c2.setCoefficient(x, 1);
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c2.setCoefficient(y, -1);
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System.out.println("Number of constraints = " + solver.numConstraints());
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// [END constraints]
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// [START objective]
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// Maximize 3 * x + 4 * y.
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MPObjective objective = solver.objective();
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objective.setCoefficient(x, 3);
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objective.setCoefficient(y, 4);
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objective.setMaximization();
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// [END objective]
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// [START solve]
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final MPSolver.ResultStatus resultStatus = solver.solve();
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// Check that the problem has an optimal solution.
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if (resultStatus != MPSolver.ResultStatus.OPTIMAL) {
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System.err.println("The problem does not have an optimal solution!");
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return;
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}
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// [END solve]
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// [START print_solution]
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// The value of each variable in the solution.
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System.out.println("Solution");
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System.out.println("x = " + x.solutionValue());
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System.out.println("y = " + y.solutionValue());
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// The objective value of the solution.
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System.out.println("Optimal objective value = " + solver.objective().value());
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// [END print_solution]
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}
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}
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// [END program]
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