113 lines
3.8 KiB
Java
113 lines
3.8 KiB
Java
// Copyright 2010-2022 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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// MIP example that uses a variable array.
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// [START program]
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package com.google.ortools.linearsolver.samples;
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// [START import]
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import com.google.ortools.Loader;
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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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// [END import]
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// [START program_part1]
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/** MIP example with a variable array. */
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public class MipVarArray {
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// [START data_model]
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static class DataModel {
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public final double[][] constraintCoeffs = {
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{5, 7, 9, 2, 1},
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{18, 4, -9, 10, 12},
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{4, 7, 3, 8, 5},
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{5, 13, 16, 3, -7},
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};
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public final double[] bounds = {250, 285, 211, 315};
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public final double[] objCoeffs = {7, 8, 2, 9, 6};
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public final int numVars = 5;
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public final int numConstraints = 4;
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}
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// [END data_model]
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public static void main(String[] args) throws Exception {
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Loader.loadNativeLibraries();
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// [START data]
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final DataModel data = new DataModel();
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// [END data]
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// [END program_part1]
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// [START solver]
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// Create the linear solver with the SCIP backend.
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MPSolver solver = MPSolver.createSolver("SCIP");
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if (solver == null) {
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System.out.println("Could not create solver SCIP");
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return;
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}
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// [END solver]
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// [START program_part2]
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// [START variables]
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double infinity = java.lang.Double.POSITIVE_INFINITY;
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MPVariable[] x = new MPVariable[data.numVars];
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for (int j = 0; j < data.numVars; ++j) {
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x[j] = solver.makeIntVar(0.0, infinity, "");
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}
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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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// Create the constraints.
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for (int i = 0; i < data.numConstraints; ++i) {
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MPConstraint constraint = solver.makeConstraint(0, data.bounds[i], "");
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for (int j = 0; j < data.numVars; ++j) {
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constraint.setCoefficient(x[j], data.constraintCoeffs[i][j]);
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}
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}
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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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MPObjective objective = solver.objective();
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for (int j = 0; j < data.numVars; ++j) {
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objective.setCoefficient(x[j], data.objCoeffs[j]);
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}
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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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// [END solve]
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// [START print_solution]
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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.out.println("Objective value = " + objective.value());
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for (int j = 0; j < data.numVars; ++j) {
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System.out.println("x[" + j + "] = " + x[j].solutionValue());
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}
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System.out.println();
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System.out.println("Problem solved in " + solver.wallTime() + " milliseconds");
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System.out.println("Problem solved in " + solver.iterations() + " iterations");
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System.out.println("Problem solved in " + solver.nodes() + " branch-and-bound nodes");
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} else {
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System.err.println("The problem does not have an optimal solution.");
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}
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// [END print_solution]
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}
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private MipVarArray() {}
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}
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// [END program_part2]
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// [END program]
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