withoutsupergenesample.java

jgap3.2 遗传算法工具包,嘿嘿,笨鸟先飞哦

/*
 * This file is part of JGAP.
 *
 * JGAP offers a dual license model containing the LGPL as well as the MPL.
 *
 * For licencing 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.supergene;

import org.jgap.*;
import org.jgap.impl.*;

/**
 * Computes the optimal change with the same condition as
 * SupergeneTest, but without using supergenes. Implemented
 * to compare the performance.
 * To test the Supergene, we created the "makechange" version with
 * additional condition: the number of nickels and pennies must be
 * both even or both odd. The supergene encloses two genes
 * (nickels and pennies) and is valid if the condition above is
 * satisfied.
 */
class WithoutSupergeneSample
    extends SupergeneSample {
  /** String containing the CVS revision. Read out via reflection!*/
  private final static String CVS_REVISION = "0.0.0 alpha explosive";

  /**
   * Executes the genetic algorithm to determine the minimum number of
   * coins necessary to make up the given target amount of change. The
   * solution will then be written to System.out.
   *
   * @param a_targetChangeAmount The target amount of change for which this
   * method is attempting to produce the minimum number of coins
   * @return absolute difference between the required and computed change
   * @throws Exception
   */
  public int makeChangeForAmount(int a_targetChangeAmount)
      throws Exception {
    // Start with a DefaultConfiguration, which comes setup with the
    // most common settings.
    // -------------------------------------------------------------
    Configuration conf = new DefaultConfiguration();
    // Set the fitness function we want to use. We construct it with
    // the target amount of change passed in to this method.
    // ---------------------------------------------------------
    WithoutSupergeneChangeFitFuncForTest fitnessFunction =
        new WithoutSupergeneChangeFitFuncForTest(a_targetChangeAmount);
    conf.setFitnessFunction(fitnessFunction);
    // Now we need to tell the Configuration object how we want our
    // Chromosomes to be setup. We do that by actually creating a
    // sample Chromosome and then setting it on the Configuration
    // object. As mentioned earlier, we want our Chromosomes to each
    // have four genes, one for each of the coin types. We want the
    // values (alleles) of those genes to be integers, which represent
    // how many coins of that type we have. We therefore use the
    // IntegerGene class to represent each of the genes. That class
    // also lets us specify a lower and upper bound, which we set
    // to sensible values for each coin type.
    // --------------------------------------------------------------
    Gene[] sampleGenes = new Gene[4];
    sampleGenes[DIMES] = getDimesGene(conf); // Dimes
    sampleGenes[NICKELS] = getNickelsGene(conf); // Nickels
    sampleGenes[QUARTERS] = getQuartersGene(conf); // Quarters
    sampleGenes[PENNIES] = getPenniesGene(conf); // Pennies
    int s = solve(conf, a_targetChangeAmount, fitnessFunction, sampleGenes);
    return s;
  }

  public static void main(String[] args) {
    WithoutSupergeneSample test = new WithoutSupergeneSample();
    test.test();
    System.exit(0);
  }
}