SupergeneSample


1   /*
2    * This file is part of JGAP.
3    *
4    * JGAP offers a dual license model containing the LGPL as well as the MPL.
5    *
6    * For licencing information please see the file license.txt included with JGAP
7    * or have a look at the top of class org.jgap.Chromosome which representatively
8    * includes the JGAP license policy applicable for any file delivered with JGAP.
9    */
10  package examples.supergene;
11  
12  import org.jgap.*;
13  import org.jgap.impl.*;
14  
15  /**
16   * To test the Supergene, we created the "make change" version with
17   * additional condition: the number of nickels and pennies must be
18   * both even or both odd. The supergene encloses two genes
19   * (nickels and pennies) and is valid if the condition above is
20   * satisfied.
21   *
22   * @author Neil Rotstan
23   * @author Klaus Meffert
24   * @author Audrius Meskauskas (subsequent adaptation)
25   * @since 2.0
26   */
27  public class SupergeneSample
28      extends AbstractSupergeneTest {
29    /** String containing the CVS revision. Read out via reflection!*/
30    private final static String   CVS_REVISION = "$Revision: 1.2 $";
31  
32    /**
33     * Executes the genetic algorithm to determine the minimum number of
34     * coins necessary to make up the given target amount of change. The
35     * solution will then be written to System.out.
36     *
37     * @param a_targetChangeAmount the target amount of change for which this
38     * method is attempting to produce the minimum number of coins
39     *
40     * @throws Exception
41     * @return absolute difference between the required and computed change
42     * amount
43     */
44    public int makeChangeForAmount(int a_targetChangeAmount)
45        throws Exception   {
46      // Start with a DefaultConfiguration, which comes setup with the
47      // most common settings.
48      // -------------------------------------------------------------
49      Configuration conf = new DefaultConfiguration();
50      // Set the fitness function we want to use, which is our
51      // MinimizingMakeChangeFitnessFunction. We construct it with
52      // the target amount of change passed in to this method.
53      // ---------------------------------------------------------
54      SupergeneChangeFitnessFunction fitnessFunction =
55          new SupergeneChangeFitnessFunction(a_targetChangeAmount);
56      conf.setFitnessFunction(fitnessFunction);
57      conf.setKeepPopulationSizeConstant(false);
58      // Now we need to tell the Configuration object how we want our
59      // Chromosomes to be setup. We do that by actually creating a
60      // sample Chromosome and then setting it on the Configuration
61      // object. As mentioned earlier, we want our Chromosomes to each
62      // have four genes, one for each of the coin types. We want the
63      // values (alleles) of those genes to be integers, which represent
64      // how many coins of that type we have. We therefore use the
65      // IntegerGene class to represent each of the genes. That class
66      // also lets us specify a lower and upper bound, which we set
67      // to sensible values for each coin type.
68      // --------------------------------------------------------------
69      Gene[] sampleGenes = new Gene[3];
70      sampleGenes[DIMES] = getDimesGene(conf);
71      sampleGenes[QUARTERS] = getQuartersGene(conf);
72      sampleGenes[2] = new NickelsPenniesSupergene(conf, new Gene[] {
73          getNickelsGene(conf),
74          getPenniesGene(conf),
75      });
76      int s = solve(conf, a_targetChangeAmount, fitnessFunction, sampleGenes);
77      return s;
78    }
79  
80    public static void main(String  [] args) {
81      SupergeneSample test = new SupergeneSample();
82      test.test();
83    }
84  }
85
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