greedycrossovertest.java

用java语言写的遗传算法库

/*
 * 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 org.jgap.impl;

import java.util.*;

import org.jgap.*;

import junit.framework.*;

/**
 * Test class for GreedyCrossover class
 *
 * @author Klaus Meffert
 * @since 2.1
 */
public class GreedyCrossoverTest
    extends TestCase {

  /** String containing the CVS revision. Read out via reflection!*/
  private static final String CVS_REVISION = "$Revision: 1.9 $";

  public GreedyCrossoverTest() {
  }

  public void setUp() {
    Genotype.setConfiguration(null);
  }

  public static Test suite() {
    TestSuite suite = new TestSuite(GreedyCrossoverTest.class);
    return suite;
  }

  /**
   * @throws Exception
   *
   * @author Klaus Meffert
   * @since 2.1
   */
  public void testOperate_0()
      throws Exception {
    DefaultConfiguration conf = new DefaultConfiguration();
    Genotype.setConfiguration(conf);
    RandomGeneratorForTest rand = new RandomGeneratorForTest();
    rand.setNextIntSequence(new int[] {
                            0, 1, 0, 1, 2});
    conf.setRandomGenerator(rand);
    conf.setFitnessFunction(new TestFitnessFunction());
    Gene sampleGene = new IntegerGene(1, 10);
    Chromosome chrom = new Chromosome(sampleGene, 3);
    conf.setSampleChromosome(chrom);
    conf.setPopulationSize(6);
    GreedyCrossover op = new GreedyCrossover();
    op.ASSERTIONS = true;
    op.setStartOffset(0);
    Gene cgene1 = new IntegerGene(1, 10);
    cgene1.setAllele(new Integer(6));
    Gene cgene2 = new IntegerGene(1, 10);
    cgene2.setAllele(new Integer(8));
    Gene[] genes1 = new Gene[] {
        cgene1, cgene2};
    Chromosome chrom1 = new Chromosome(genes1);
    Gene[] genes2 = new Gene[] {
        cgene2, cgene1};
    Chromosome chrom2 = new Chromosome(genes2);
    Chromosome[] population = new Chromosome[] {
        chrom1, chrom2};
    List chroms = new Vector();
    Gene gene1 = new IntegerGene(1, 10);
    gene1.setAllele(new Integer(5));
    chroms.add(gene1);
    Gene gene2 = new IntegerGene(1, 10);
    gene2.setAllele(new Integer(7));
    chroms.add(gene2);
    Gene gene3 = new IntegerGene(1, 10);
    gene3.setAllele(new Integer(4));
    chroms.add(gene3);
    op.operate(new Population(population), chroms);
    assertEquals(5, chroms.size());
    Chromosome target = (Chromosome) chroms.get(4);
    assertEquals(8, ( (Integer) target.getGene(0).getAllele()).intValue());
    target = (Chromosome) chroms.get(3);
    assertEquals(6, ( (Integer) target.getGene(0).getAllele()).intValue());
  }

  /**
   * Same as testOperate_0 except op.setStartOffset(1) instead of 0
   * @throws Exception
   *
   * @author Klaus Meffert
   * @since 2.1
   */
  public void testOperate_1()
      throws Exception {
    DefaultConfiguration conf = new DefaultConfiguration();
    Genotype.setConfiguration(conf);
    RandomGeneratorForTest rand = new RandomGeneratorForTest();
    rand.setNextIntSequence(new int[] {
                            0, 1, 0, 1, 2});
    conf.setRandomGenerator(rand);
    conf.setFitnessFunction(new TestFitnessFunction());
    Gene sampleGene = new IntegerGene(1, 10);
    Chromosome chrom = new Chromosome(sampleGene, 3);
    conf.setSampleChromosome(chrom);
    conf.setPopulationSize(6);

    GreedyCrossover op = new GreedyCrossover();
    op.ASSERTIONS = true;
    op.setStartOffset(1);

    Gene cgene1 = new IntegerGene(1, 10);
    cgene1.setAllele(new Integer(6));
    Gene cgene2 = new IntegerGene(1, 10);
    cgene2.setAllele(new Integer(8));
    Gene[] genes1 = new Gene[] {
        cgene1, cgene2};
    Chromosome chrom1 = new Chromosome(genes1);
    Gene[] genes2 = new Gene[] {
        cgene2, cgene1};
    Chromosome chrom2 = new Chromosome(genes2);
    Chromosome[] population = new Chromosome[] {
        chrom1, chrom2};
    List chroms = new Vector();
    Gene gene1 = new IntegerGene(1, 10);
    gene1.setAllele(new Integer(5));
    chroms.add(gene1);
    Gene gene2 = new IntegerGene(1, 10);
    gene2.setAllele(new Integer(7));
    chroms.add(gene2);
    try {
      op.operate(new Population(population), chroms);
      fail();
    }catch (Error e) {
      ;//this is OK
    }
  }

  /**
   * Test with CompositeGene
   * @throws Exception
   *
   * @author Klaus Meffert
   * @since 2.1
   */
  public void testOperate_2()
      throws Exception {
    DefaultConfiguration conf = new DefaultConfiguration();
    Genotype.setConfiguration(conf);
    RandomGeneratorForTest rand = new RandomGeneratorForTest();
    rand.setNextIntSequence(new int[] {
                            0, 1, 0, 1, 2});
    conf.setRandomGenerator(rand);
    conf.setFitnessFunction(new TestFitnessFunction());
    GreedyCrossover op = new GreedyCrossover();
    op.ASSERTIONS = true;

    Gene sampleGene = new IntegerGene(1, 10);
    Chromosome chrom = new Chromosome(sampleGene, 3);
    conf.setSampleChromosome(chrom);
    conf.setPopulationSize(6);
    Gene cgene1 = new IntegerGene(1, 10);
    cgene1.setAllele(new Integer(6));
    CompositeGene compGene = new CompositeGene ();
    compGene.addGene(cgene1);
    Gene cgene2 = new IntegerGene(1, 10);
    cgene2.setAllele(new Integer(8));
    Gene[] genes1 = new Gene[] {
        cgene1, cgene2};
    Chromosome chrom1 = new Chromosome(genes1);

    Gene[] genes2 = new Gene[] {
        cgene1, cgene2, cgene1};

    Chromosome chrom2 = new Chromosome(genes2);
    Chromosome[] population = new Chromosome[] {
        chrom1, chrom2};
    List chroms = new Vector();
    Gene gene1 = new IntegerGene(1, 10);
    gene1.setAllele(new Integer(5));
    chroms.add(gene1);
    try {
      op.operate(new Population(population), chroms);
      fail();
    } catch (Error e) {
      ;//this is OK
    }
  }

  /**
   * Test with CompositeGene and two identical Genes in a Chromosome
   * @throws Exception
   *
   * @author Klaus Meffert
   * @since 2.1
   */
  public void testOperate_3()
      throws Exception {
    DefaultConfiguration conf = new DefaultConfiguration();
    Genotype.setConfiguration(conf);
    RandomGeneratorForTest rand = new RandomGeneratorForTest();
    rand.setNextIntSequence(new int[] {
                            0, 1, 0, 1, 2});
    conf.setRandomGenerator(rand);
    conf.setFitnessFunction(new TestFitnessFunction());
    GreedyCrossover op = new GreedyCrossover();
    op.ASSERTIONS = true;
    op.setStartOffset(0);

    Gene sampleGene = new IntegerGene(1, 10);
    Chromosome chrom = new Chromosome(sampleGene, 3);
    conf.setSampleChromosome(chrom);
    conf.setPopulationSize(6);
    Gene cgene1 = new IntegerGene(1, 10);
    cgene1.setAllele(new Integer(6));
    CompositeGene compGene = new CompositeGene ();
    compGene.addGene(cgene1);
    Gene cgene2 = new IntegerGene(1, 10);
    cgene2.setAllele(new Integer(8));
    Gene[] genes1 = new Gene[] {
        compGene, cgene1, cgene1};
    Chromosome chrom1 = new Chromosome(genes1);

    Gene[] genes2 = new Gene[] {
        compGene, cgene1, cgene1};
    Chromosome chrom2 = new Chromosome(genes2);
    Chromosome[] population = new Chromosome[] {
        chrom1, chrom2};
    List chroms = new Vector();
    Gene gene1 = new IntegerGene(1, 10);
    gene1.setAllele(new Integer(5));
    chroms.add(gene1);
    Gene gene2 = new IntegerGene(1, 10);
    gene2.setAllele(new Integer(7));
    chroms.add(gene2);
    Gene gene3 = new IntegerGene(1, 10);
    gene3.setAllele(new Integer(4));
    chroms.add(gene3);
    try {
      op.operate(new Population(population), chroms);
      fail();
    } catch (Error e) {
      ;//this is OK
    }
  }

  /**
   * Test the example from the literature.
   * This test tests the crossover main algorithm, not the whole operator.
   * @throws Exception
   *
   * @author Audrius Meskauskas
   * @since 2.1
   */
  public void testOperate_4()
      throws Exception {
    Configuration conf = new DefaultConfiguration();
    conf.setFitnessFunction(new TestFitnessFunction());
    Genotype.setConfiguration(conf);
    GreedyCrossover cross = new GreedyCrossover() {
      /* Computes the distances how it was described in the
         literature example */
      public double distance(Object a_from, Object a_to) {
        IntegerGene from = (IntegerGene) a_from;
        IntegerGene to = (IntegerGene) a_to;

        int a = from.intValue();
        int b = to.intValue();

        if (a > b) {
          int t = a;
          a = b;
          b = t;
        }
        ;

        // 4,1 is shorter than 4,5
        if (a == 1 && b == 4)return 1;
        if (a == 4 && b == 5)return 2;

        // 1,2 is shorter that 1,3
        if (a == 1 && b == 2)return 10;
        if (a == 1 && b == 3)return 20;

        // 2,0 is shorter than 2,3
        if (a == 0 && b == 2)return 100;
        if (a == 2 && b == 3)return 200;

        throw new Error
            ("These two should not be compared: " + a + " and " + b);
      }
    };

    cross.ASSERTIONS = true;
    cross.setStartOffset(0);

    Chromosome a =
        chromosome(new int[] {1, 2, 3, 4, 5, 0});

    Chromosome b =
        chromosome(new int[] {4, 1, 3, 2, 0, 5});

    // in the literature example it was 1, 2, 0, 5, 4, 3, but the random
    // choice is involved in the last step. In this implementation
    // the choice is not random and the last two genes are always
    // returned as 3, 4.
    // -----------------------------------------------------------------
    Chromosome must_a = chromosome(new int[] {1, 2, 0, 5, 3, 4});

    // this is same as in the literature, the random choice is not involved.
    // ---------------------------------------------------------------------
    Chromosome must_b = chromosome(new int[] {4, 1, 2, 0, 5, 3});

    cross.operate(b, a);

    assertEquals(a, must_a);
    assertEquals(b, must_b);
  }

  /**
   * Tests if population size grows expectedly after two consecutive calls.
   * @throws Exception
   *
   * @author Klaus Meffert
   * @since 2.1
   */
  public void testOperate_5()
      throws Exception {
    DefaultConfiguration conf = new DefaultConfiguration();
    GreedyCrossover op = new GreedyCrossover();
    op.ASSERTIONS = true;
    conf.addGeneticOperator(op);
    Genotype.setConfiguration(conf);
    RandomGeneratorForTest rand = new RandomGeneratorForTest();
    rand.setNextDouble(0.45d);
    rand.setNextInt(0);
    op.setStartOffset(0);
    conf.setRandomGenerator(rand);
    conf.setFitnessFunction(new TestFitnessFunction());
    Gene sampleGene = new IntegerGene(1, 10);
    Chromosome chrom = new Chromosome(sampleGene, 3);
    conf.setSampleChromosome(chrom);
    conf.setPopulationSize(6);
    Gene cgene1 = new IntegerGene(1, 10);
    cgene1.setAllele(new Integer(6));
    Gene[] genes1 = new Gene[] {
        cgene1};
    Chromosome chrom1 = new Chromosome(genes1);
    Gene cgene2 = new IntegerGene(1, 10);
    cgene2.setAllele(new Integer(9));
    Gene[] genes2 = new Gene[] {
        cgene2};
    Chromosome chrom2 = new Chromosome(genes2);
    Chromosome[] population = new Chromosome[] {
        chrom1, chrom2};
    List chroms = new Vector();
    Gene gene1 = new IntegerGene(1, 10);
    gene1.setAllele(new Integer(5));
    chroms.add(gene1);
    Gene gene2 = new IntegerGene(1, 10);
    gene2.setAllele(new Integer(7));
    chroms.add(gene2);
    Gene gene3 = new IntegerGene(1, 10);
    gene3.setAllele(new Integer(4));
    chroms.add(gene3);
    assertEquals(3, chroms.size());
    Population pop = new Population(population);
    op.operate(pop, chroms);
    assertEquals(2, pop.size());
    assertEquals(3+2, chroms.size());
    op.operate(pop, chroms);
    assertEquals(2, pop.size());
    assertEquals(3+2+2, chroms.size());
  }

  /**
   * Make a chromosome from the array of integer genes.
   * @param genes input genes
   * @return chromosome containing input genes
   * @throws Exception
   *
   * @author Audrius Meskauskas
   * @since 2.1
   */
  private Chromosome chromosome ( int [] genes ) throws Exception
  {
      IntegerGene [] ig = new IntegerGene [genes.length];
      for (int i = 0; i < ig.length; i++) {
          ig [i] = new IntegerGene (0,5);
          ig [i].setAllele( new Integer (genes [i] ));
      }
      return new Chromosome (ig);
  }

  /**
   * @author Klaus Meffert
   * @since 2.2
   */
  public void testStartoffset_0() {
    GreedyCrossover op = new GreedyCrossover();
    assertEquals(1,op.getStartOffset());
    op.setStartOffset(2);
    assertEquals(2,op.getStartOffset());
    op.setStartOffset(1);
    assertEquals(1,op.getStartOffset());
    op.setStartOffset(0);
    assertEquals(0,op.getStartOffset());

  }
}