greedycrossovertest.java

一个开源的用java开发的遗传算法的封装好的工程

        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(conf);
    op.ASSERTIONS = true;
    conf.addGeneticOperator(op);
    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(conf, 1, 10);
    Chromosome chrom = new Chromosome(conf, sampleGene, 3);
    conf.setSampleChromosome(chrom);
    conf.setPopulationSize(6);
    Gene cgene1 = new IntegerGene(conf, 1, 10);
    cgene1.setAllele(new Integer(6));
    Gene cgene1_2 = new IntegerGene(conf, 1, 150);
    cgene1.setAllele(new Integer(99));
    Gene[] genes1 = new Gene[] {
        cgene1, cgene1_2};
    Chromosome chrom1 = new Chromosome(conf, genes1);
    Gene cgene2 = new IntegerGene(conf, 1, 10);
    cgene2.setAllele(new Integer(9));
    Gene cgene2_2 = new IntegerGene(conf, 1, 10);
    cgene2.setAllele(new Integer(1));
    Gene[] genes2 = new Gene[] {
        cgene2, cgene2_2};
    Chromosome chrom2 = new Chromosome(conf, genes2);
    Chromosome[] population = new Chromosome[] {
        chrom1, chrom2};
    List chroms = new Vector();
    Gene gene1 = new IntegerGene(conf, 1, 10);
    gene1.setAllele(new Integer(5));
    chroms.add(gene1);
    Gene gene2 = new IntegerGene(conf, 1, 10);
    gene2.setAllele(new Integer(7));
    chroms.add(gene2);
    Gene gene3 = new IntegerGene(conf, 1, 10);
    gene3.setAllele(new Integer(4));
    chroms.add(gene3);
    assertEquals(3, chroms.size());
    Population pop = new Population(conf, 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());
  }

  /**
   * Tests if error thrown because of wrong length of gene.
   * @throws Exception
   *
   * @author Klaus Meffert
   * @since 2.4
   */
  public void testOperate_6()
      throws Exception {
    DefaultConfiguration conf = new DefaultConfiguration();
    GreedyCrossover op = new GreedyCrossover(conf);
    op.ASSERTIONS = true;
    conf.addGeneticOperator(op);
    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(conf, 1, 10);
    Chromosome chrom = new Chromosome(conf, sampleGene, 3);
    conf.setSampleChromosome(chrom);
    conf.setPopulationSize(6);
    Gene cgene1 = new IntegerGene(conf, 1, 10);
    cgene1.setAllele(new Integer(6));
    Gene[] genes1 = new Gene[] {
        cgene1};
    Chromosome chrom1 = new Chromosome(conf, genes1);
    Gene cgene2 = new IntegerGene(conf, 1, 10);
    cgene2.setAllele(new Integer(9));
    Gene[] genes2 = new Gene[] {
        cgene2};
    Chromosome chrom2 = new Chromosome(conf, genes2);
    Chromosome[] population = new Chromosome[] {
        chrom1, chrom2};
    List chroms = new Vector();
    Gene gene1 = new IntegerGene(conf, 1, 10);
    gene1.setAllele(new Integer(5));
    chroms.add(gene1);
    Gene gene2 = new IntegerGene(conf, 1, 10);
    gene2.setAllele(new Integer(7));
    chroms.add(gene2);
    Gene gene3 = new IntegerGene(conf, 1, 10);
    gene3.setAllele(new Integer(4));
    chroms.add(gene3);
    assertEquals(3, chroms.size());
    Population pop = new Population(conf, population);
    try {
      op.operate(pop, chroms);
      fail();
    }
    catch (Error e) {
      ; //this is OK
    }
  }

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

  /**
   * @throws Exception
   *
   * @author Klaus Meffert
   * @since 2.2
   */
  public void testStartoffset_0()
      throws Exception {
    GreedyCrossover op = new GreedyCrossover(conf);
    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());
  }

  /**
   * Ensures the operator is implementing Serializable
   * @throws Exception
   *
   * @author Klaus Meffert
   * @since 2.6
   */
  public void testIsSerializable_0()
      throws Exception {
    GreedyCrossover op = new GreedyCrossover(conf);
    assertTrue(isSerializable(op));
  }

  /**
   * Ensures that the operator and all objects contained implement Serializable
   * @throws Exception
   *
   * @author Klaus Meffert
   * @since 2.6
   */
  public void testDoSerialize_0()
      throws Exception {
    // construct object to be serialized
    GreedyCrossover op = new GreedyCrossover(conf);
    GreedyCrossover o = (GreedyCrossover) doSerialize(op);
    assertEquals(o, op);
  }

  /**
   * Test equals with classcast object.
   * @throws Exception
   *
   * @author Klaus Meffert
   * @since 2.6
   */
  public void testEquals_0()
      throws Exception {
    GeneticOperator op = new GreedyCrossover(conf);
    assertFalse(op.equals(new Chromosome(conf)));
  }

  /**
   * @throws Exception
   *
   * @author Klaus Meffert
   * @since 2.6
   */
  public void testCompareTo_0()
      throws Exception {
    GreedyCrossover op = new GreedyCrossover(conf);
    assertEquals(1, op.compareTo(null));
    GreedyCrossover op2 = new GreedyCrossover(conf);
    assertEquals(0, op.compareTo(op2));
    op.setStartOffset(2);
    assertEquals( -1, op.compareTo(op2));
    assertEquals(1, op2.compareTo(op));
  }
}