michalewicz_g1.java

用JAVA语言编写

/**
 * Description: Benchmark function (Michalewicz's G1).
 * X*(Optimal point):
 * X1~X9, X13: 1
 * X10~X12: 3
 * Y*(Optimal value)
 * Y1=15
 *
 * @ Author        Create/Modi     Note
 * Xiaofeng Xie    Dec 28, 2001
 * Xiaofeng Xie    Mar 01, 2003
 * Xiaofeng Xie    May 11, 2004
 *
 * This library is free software; you can redistribute it and/or
 * modify it under the terms of the GNU Lesser General Public
 * License as published by the Free Software Foundation; either
 * version 2.1 of the License, or (at your option) any later version.
 *
 * This library is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
 * Lesser General Public License for more details.
 *
 * Please acknowledge the author(s) if you use this code in any way.
 *
 * @version 1.0
 * @Since MAOS1.0
 *
 * @References:
 * [1] Floundas C, Pardalos P. A Collection of Test Problems for Constrained
 * Global Optimization. Springer-Verlag, LNCS, 1987, 455
 * [2] Koziel S, Michalewicz Z. Evolutionary algorithms, homomorphous
 * mappings, and constrained parameter optimization. Evolutionary Computation,
 * 1999, 7: 19-44
 */

package problem.constrained;

import problem.*;
import Global.*;

public class Michalewicz_G1 extends ProblemEncoder {
  public Michalewicz_G1() throws Exception {
    super(13, 10); //13: number of varibles; 10: number of objectives (include constraints)
    for(int i=0; i<9; i++) {
      setDefaultXAt(i, 0, 1);     //Parameter range: [0, 1]
    }
    for(int i=9; i<12; i++) {
      setDefaultXAt(i, 0, 100);   //Parameter range: [0, 100]
    }
    setDefaultXAt(12, 0, 1);      //Parameter range: [0, 1]

    setDefaultYAt(0, BasicBound.MINDOUBLE, BasicBound.MINDOUBLE); // Minimize Objective
    for(int i=1; i<4; i++) {
      setDefaultYAt(i, BasicBound.MINDOUBLE, 10); //Lessthan constraints (<10)
    }
    for(int i=4; i<10; i++) {
      setDefaultYAt(i, BasicBound.MINDOUBLE, 0);   //Lessthan constraints (<0)
    }
  }
  protected double calcTargetAt(int index, double[] VX) {
    double value = 0;
    switch(index) {
    case 0:
      value = 5*(VX[0]+VX[1]+VX[2]+VX[3])-5*(VX[0]*VX[0]+VX[1]*VX[1]+VX[2]*VX[2]+VX[3]*VX[3])-(VX[4]+VX[5]+VX[6]+VX[7]+VX[8]+VX[9]+VX[10]+VX[11]+VX[12]);
      break;
    case 1:
      value = 2*VX[0]+2*VX[1]+VX[9]+VX[10]-10;
      break;
    case 2:
      value = 2*VX[0]+2*VX[2]+VX[9]+VX[11]-10;
      break;
    case 3:
      value = 2*VX[1]+2*VX[2]+VX[10]+VX[11]-10;
      break;
    case 4:
      value = -8*VX[0]+VX[9];
      break;
    case 5:
      value = -8*VX[1]+VX[10];
      break;
    case 6:
      value = -8*VX[2]+VX[11];
      break;
    case 7:
      value = -2*VX[3]-VX[4]+VX[9];
      break;
    case 8:
      value = -2*VX[5]-VX[6]+VX[10];
      break;
    case 9:
      value = -2*VX[7]-VX[8]+VX[11];
      break;
    default:
      return Double.NaN;
    }
    return value;
  }
}