Java tutorial
package org.um.feri.ears.problems.constrained; import java.util.ArrayList; import java.util.Arrays; import java.util.Collections; import java.util.List; import org.apache.commons.lang3.ArrayUtils; import org.um.feri.ears.problems.DoubleSolution; import org.um.feri.ears.problems.Problem; import org.um.feri.ears.util.Util; /** * Problem function! * <p> * * @author Matej Crepinsek * @version 1 * * <h3>License</h3> * * Copyright (c) 2011 by Matej Crepinsek. <br> * All rights reserved. <br> * * <p> * Redistribution and use in source and binary forms, with or without * modification, are permitted provided that the following conditions * are met: * <ul> * <li>Redistributions of source code must retain the above copyright * notice, this list of conditions and the following disclaimer. * <li>Redistributions in binary form must reproduce the above * copyright notice, this list of conditions and the following * disclaimer in the documentation and/or other materials provided with * the distribution. * <li>Neither the name of the copyright owners, their employers, nor * the names of its contributors may be used to endorse or promote * products derived from this software without specific prior written * permission. * </ul> * <p> * THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS * "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT * LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS * FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE * COPYRIGHT OWNERS OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, * INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, * BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; * LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER * CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT * LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN * ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE * POSSIBILITY OF SUCH DAMAGE. * */ public class TLBOBenchmarkFunction1 extends Problem { // http://www-optima.amp.i.kyoto-u.ac.jp/member/student/hedar/Hedar_files/TestGO_files/Page506.htm public final static double best_x[] = { 1, 1, 1, 1, 1, 1, 1, 1, 1, 3, 3, 3, 1 }; public TLBOBenchmarkFunction1() { super(13, 9); minimum = true; max_constraints = new Double[numberOfConstraints]; min_constraints = new Double[numberOfConstraints]; count_constraints = new Double[numberOfConstraints]; sum_constraints = new Double[numberOfConstraints]; normalization_constraints_factor = new Double[numberOfConstraints]; upperLimit = new ArrayList<Double>(Collections.nCopies(numberOfDimensions, 0.0)); lowerLimit = new ArrayList<Double>(Collections.nCopies(numberOfDimensions, 0.0)); for (int i = 0; i < 9; i++) { lowerLimit.set(i, 0.0); upperLimit.set(i, 1.0); } for (int i = 9; i < 12; i++) { lowerLimit.set(i, 0.0); upperLimit.set(i, 100.0); } lowerLimit.set(12, 0.0); upperLimit.set(12, 1.0); name = "TLBOBenchmarkFunction1 (TP7) cec-g01"; // System.out.println(Arrays.toString(interval)+"\n"+Arrays.toString(intervalL)); } public double eval(double x[]) { double v = 0; v = 5.0 * (x[0] + x[1] + x[2] + x[3]) - 5.0 * (x[0] * x[0] + x[1] * x[1] + x[2] * x[2] + x[3] * x[3]); for (int j = 4; j < 13; j++) { v = v - x[j]; } return v; } public double[] calc_constrains(double x[]) { double[] g = new double[numberOfConstraints]; g[0] = 2.0 * x[0] + 2.0 * x[1] + x[9] + x[10] - 10.; g[1] = 2.0 * x[0] + 2.0 * x[2] + x[9] + x[11] - 10.; g[2] = 2.0 * x[1] + 2.0 * x[2] + x[10] + x[11] - 10.; g[3] = -8.0 * x[0] + x[9]; g[4] = -8.0 * x[1] + x[10]; g[5] = -8.0 * x[2] + x[11]; g[6] = -2.0 * x[3] - x[4] + x[9]; g[7] = -2.0 * x[5] - x[6] + x[10]; g[8] = -2.0 * x[7] - x[8] + x[11]; return g; } public double[] calc_constrains2(double x[]) { double[] g = new double[numberOfConstraints]; g[0] = 2.0 * x[0] + 2.0 * x[1] + x[9] + x[10] - 10.; g[1] = 2.0 * x[0] + 2.0 * x[2] + x[9] + x[11] - 10.; g[2] = 2.0 * x[1] + 2.0 * x[2] + x[10] + x[11] - 10.; g[3] = -2.0 * x[3] - x[4] + x[9]; g[4] = -2.0 * x[5] - x[6] + x[10]; g[5] = -2.0 * x[7] - x[8] + x[11]; return g; } public double getOptimumEval() { return -15; } @Override public double eval(Double[] ds) { return eval(ArrayUtils.toPrimitive(ds)); } }