WithoutSupergeneSample


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   * Computes the optimal change with the same condition as
17   * SupergeneTest, but without using supergenes. Implemented
18   * to compare the performance.
19   * To test the Supergene, we created the "makechange" version with
20   * additional condition: the number of nickels and pennies must be
21   * both even or both odd. The supergene encloses two genes
22   * (nickels and pennies) and is valid if the condition above is
23   * satisfied.
24   */
25  class WithoutSupergeneSample
26      extends SupergeneSample {
27    /** String containing the CVS revision. Read out via reflection!*/
28    private final static String   CVS_REVISION = "0.0.0 alpha explosive";
29  
30    /**
31     * Executes the genetic algorithm to determine the minimum number of
32     * coins necessary to make up the given target amount of change. The
33     * solution will then be written to System.out.
34     *
35     * @param a_targetChangeAmount The target amount of change for which this
36     * method is attempting to produce the minimum number of coins
37     * @return absolute difference between the required and computed change
38     * @throws Exception
39     */
40    public int makeChangeForAmount(int a_targetChangeAmount)
41        throws Exception   {
42      // Start with a DefaultConfiguration, which comes setup with the
43      // most common settings.
44      // -------------------------------------------------------------
45      Configuration conf = new DefaultConfiguration();
46      // Set the fitness function we want to use. We construct it with
47      // the target amount of change passed in to this method.
48      // ---------------------------------------------------------
49      WithoutSupergeneChangeFitFuncForTest fitnessFunction =
50          new WithoutSupergeneChangeFitFuncForTest(a_targetChangeAmount);
51      conf.setFitnessFunction(fitnessFunction);
52      // Now we need to tell the Configuration object how we want our
53      // Chromosomes to be setup. We do that by actually creating a
54      // sample Chromosome and then setting it on the Configuration
55      // object. As mentioned earlier, we want our Chromosomes to each
56      // have four genes, one for each of the coin types. We want the
57      // values (alleles) of those genes to be integers, which represent
58      // how many coins of that type we have. We therefore use the
59      // IntegerGene class to represent each of the genes. That class
60      // also lets us specify a lower and upper bound, which we set
61      // to sensible values for each coin type.
62      // --------------------------------------------------------------
63      Gene[] sampleGenes = new Gene[4];
64      sampleGenes[DIMES] = getDimesGene(conf); // Dimes
65      sampleGenes[NICKELS] = getNickelsGene(conf); // Nickels
66      sampleGenes[QUARTERS] = getQuartersGene(conf); // Quarters
67      sampleGenes[PENNIES] = getPenniesGene(conf); // Pennies
68      int s = solve(conf, a_targetChangeAmount, fitnessFunction, sampleGenes);
69      return s;
70    }
71  
72    public static void main(String  [] args) {
73      WithoutSupergeneSample test = new WithoutSupergeneSample();
74      test.test();
75      System.exit(0);
76    }
77  }
78
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