mofitnessevaluator.java

多目标进化计算算法在JGAP包上的实现。程序演示了多目标进化中fitness function和search operator的实现。

/*
 * This file is part of JGAP.
 *
 * JGAP offers a dual license model containing the LGPL as well as the MPL.
 *
 * For licensing information please see the file license.txt included with JGAP
 * or have a look at the top of class org.jgap.Chromosome which representatively
 * includes the JGAP license policy applicable for any file delivered with JGAP.
 */
package examples.multiobjective;

import java.util.*;
import org.jgap.*;
import org.jgap.impl.*;

/**
 * Fitness evaluator for multi objectives example. Determines which of two
 * vectors with multiobjective values is fitter. In our example, the fitter
 * vector is the one for which the sum of the values is smaller.
 *
 * @author Klaus Meffert
 * @since 2.6
 */
public class MOFitnessEvaluator
    implements FitnessEvaluator {
  /** String containing the CVS revision. Read out via reflection!*/
  private final static String CVS_REVISION = "$Revision: 1.4 $";

  /**
   * Not to be called in multi-objectives context! Instead, oOther method below
   * applies for multi-objectives.
   *
   * @param a_fitness_value1 ignored
   * @param a_fitness_value2 ignored
   * @return always a RuntimeException
   *
   * @author Klaus Meffert
   * @since 2.6
   */
  public boolean isFitter(final double a_fitness_value1,
                          final double a_fitness_value2) {
    throw new RuntimeException("Not supported for multi-objectives!");
  }

  public boolean isFitter(IChromosome a_chrom1, IChromosome a_chrom2) {
    // Evaluate values and fill vector of multiobjectives with them.
    // -------------------------------------------------------------
    DoubleGene g1 = (DoubleGene) a_chrom1.getGene(0);
    double d = g1.doubleValue();
    double y1 = MultiObjectiveFitnessFunction.formula(1, d);
    List l1 = new Vector();
    l1.add(new Double(y1));
    double y2 = MultiObjectiveFitnessFunction.formula(2, d);
    l1.add(new Double(y2));
    List l2 = new Vector();
    g1 = (DoubleGene) a_chrom2.getGene(0);
    d = g1.doubleValue();
    y1 = MultiObjectiveFitnessFunction.formula(1, d);
    l2.add(new Double(y1));
    y2 = MultiObjectiveFitnessFunction.formula(2, d);
    l2.add(new Double(y2));
    int size = l1.size();
    if (size != l2.size()) {
      throw new RuntimeException("Size of objectives inconsistent!");
    }
    double d1Total = 0;
    double d2Total = 0;
    for (int i = 0; i < size; i++) {
      double d1 = ( (Double) l1.get(i)).doubleValue();
      double d2 = ( (Double) l2.get(i)).doubleValue();
      d1Total += d1;
      d2Total += d2;
    }
    if (d1Total < d2Total) {
      return true;
    }
    else {
      return false;
    }
  }
}