94 lines
2.9 KiB
Java
Executable File
94 lines
2.9 KiB
Java
Executable File
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/*
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* Copyright 2017 Darian Sastre darian.sastre@minimaxlabs.com
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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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*
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* ************************************************************************
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*
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* This model was created by Hakan Kjellerstrand (hakank@gmail.com)
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*/
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package com.google.ortools.contrib;
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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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public class DietMIP {
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static {
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System.loadLibrary("jniortools");
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}
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private static MPSolver createSolver(String solverType) {
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try {
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return new MPSolver("MIPDiet", MPSolver.OptimizationProblemType.valueOf(solverType));
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} catch (java.lang.IllegalArgumentException e) {
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System.err.println("Bad solver type: " + e);
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return null;
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}
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}
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private static void solve(String solverType) {
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MPSolver solver = createSolver(solverType);
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double infinity = MPSolver.infinity();
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int n = 4; // variables number
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int m = 4; // constraints number
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int[] price = { 50, 20, 30, 80 };
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int[] limits = { 500, 6, 10, 8 };
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int[] calories = { 400, 200, 150, 500 };
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int[] chocolate = { 3, 2, 0, 0 };
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int[] sugar = { 2, 2, 4, 4 };
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int[] fat = { 2, 4, 1, 5 };
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int[][] values = { calories, chocolate, sugar, fat };
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MPVariable[] x = solver.makeIntVarArray(n, 0, 100, "x");
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MPObjective objective = solver.objective();
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MPConstraint[] targets = new MPConstraint[4];
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for (int i = 0; i < n; i++) {
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objective.setCoefficient(x[i], price[i]);
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// constraints
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targets[i] = solver.makeConstraint(limits[i], infinity);
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for (int j = 0; j < m; j++) {
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targets[i].setCoefficient(x[j], values[i][j]);
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}
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}
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final MPSolver.ResultStatus resultStatus = solver.solve();
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/** printing */
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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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} else {
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System.out.println("Optimal objective value = " + solver.objective().value());
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System.out.print("Item quantities: ");
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System.out.print((int) x[0].solutionValue() + " ");
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System.out.print((int) x[1].solutionValue() + " ");
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System.out.print((int) x[2].solutionValue() + " ");
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System.out.print((int) x[3].solutionValue() + " ");
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}
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}
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public static void main(String[] args) throws Exception {
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solve("CBC_MIXED_INTEGER_PROGRAMMING");
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}
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}
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