MainClass


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.equalDistribution;
11  
12  import java.util.*;
13  import org.jgap.*;
14  import org.jgap.impl.*;
15  
16  /**
17   * Given 64 vents with different weights. Try to make 8 group with each
18   * groups having (nearly) the same weight as the other groups.<p>
19   * Here, each vent has a similar weight with a small deviation. But the
20   * deviation could also be significant (then, good solutions are harder to
21   * find).<p>
22   * The proposed way of solving this problem is quite easy in its structure.
23   * There is potential for optimzations!
24   *
25   * @author Klaus Meffert
26   * @since 3.2
27   */
28  public class MainClass {
29    /** String containing the CVS revision. Read out via reflection!*/
30    private final static String   CVS_REVISION = "$Revision: 1.1 $";
31  
32    /**
33     * Holds the available vents, each with a specific weight
34     */
35    private Vent[] m_vents;
36  
37    private int m_numEvolutions;
38  
39    /**
40     * Constructor.
41     *
42     * @throws Exception
43     *
44     * @author Klaus Meffert
45     * @since 3.2
46     */
47    public MainClass()
48        throws Exception   {
49      makeVents();
50      Genotype genotype = configureJGAP();
51      doEvolution(genotype);
52    }
53  
54    /**
55     * Sets up the configuration for the problem.
56     *
57     * @throws Exception
58     *
59     * @author Klaus Meffert
60     * @since 3.2
61     */
62    protected Genotype configureJGAP()
63        throws Exception   {
64      m_numEvolutions = 50;
65      Configuration gaConf = new DefaultConfiguration();
66      gaConf.resetProperty(Configuration.PROPERTY_FITEVAL_INST);
67      gaConf.setFitnessEvaluator(new DeltaFitnessEvaluator());
68      // Just use a swapping operator instead of mutation and others.
69      // ------------------------------------------------------------
70      gaConf.getGeneticOperators().clear();
71      SwappingMutationOperator swapper = new SwappingMutationOperator(gaConf);
72      gaConf.addGeneticOperator(swapper);
73      // Setup some other parameters.
74      // ----------------------------
75      gaConf.setPreservFittestIndividual(true);
76      gaConf.setKeepPopulationSizeConstant(false);
77      // Set number of individuals (=tries) per generation.
78      // --------------------------------------------------
79      gaConf.setPopulationSize(50);
80      int chromeSize = m_vents.length;
81      Genotype genotype = null;
82      try {
83        // Setup the structure with which to evolve the
84        // solution of the problem.
85        // --------------------------------------------
86        IChromosome sampleChromosome = new Chromosome(gaConf,
87            new IntegerGene(gaConf), chromeSize);
88        gaConf.setSampleChromosome(sampleChromosome);
89        // Setup the important fitness function!
90        // -------------------------------------
91        gaConf.setFitnessFunction(new SampleFitnessFunction(m_vents));
92        //
93        genotype = Genotype.randomInitialGenotype(gaConf);
94        // Now ensure that each number from 1..64 (representing the
95        // indices of the vents) is represented by exactly one gene.
96        // --> Suboptimal here, as randomized initialization becomes
97        //     obsolete (other solution would be more complicated).
98        // ---------------------------------------------------------
99        List chromosomes = genotype.getPopulation().getChromosomes();
100       for (int i = 0; i < chromosomes.size(); i++) {
101         IChromosome chrom = (IChromosome) chromosomes.get(i);
102         for (int j = 0; j < chrom.size(); j++) {
103           Gene gene = (Gene) chrom.getGene(j);
104           gene.setAllele(new Integer  (j));
105         }
106       }
107     } catch (InvalidConfigurationException e) {
108       e.printStackTrace();
109       System.exit( -2);
110     }
111     return genotype;
112   }
113 
114   /**
115    * Does the evolution until finished.
116    *
117    * @author Klaus Meffert
118    * @since 3.2
119    */
120   public void doEvolution(Genotype genotype) {
121     int progress = 0;
122     int percentEvolution = m_numEvolutions / 100;
123     for (int i = 0; i < m_numEvolutions; i++) {
124       genotype.evolve();
125       // Print progress.
126       // ---------------
127       if (percentEvolution > 0 && i % percentEvolution == 0) {
128         progress++;
129         IChromosome fittest = genotype.getFittestChromosome();
130         double fitness = fittest.getFitnessValue();
131         System.out.println("Currently best solution has fitness " +
132                            fitness);
133         printSolution(fittest);
134       }
135     }
136     // Print summary.
137     // --------------
138     IChromosome fittest = genotype.getFittestChromosome();
139     System.out.println("Best solution has fitness " +
140                        fittest.getFitnessValue());
141     printSolution(fittest);
142   }
143 
144   /**
145    * @param a_solution a solution to print to the console
146    *
147    * @author Klaus Meffert
148    * @since 3.2
149    */
150   public void printSolution(IChromosome a_solution) {
151     double groupWeights = 0.0d;
152     for (int i = 0; i < 8; i++) {
153       System.out.println("\nGroup " + i);
154       System.out.println("-------");
155       double groupWeight = 0.0d;
156       for (int j = 0; j < 8; j++) {
157         IntegerGene ventIndex = (IntegerGene) a_solution.getGene( (i * 8 + j));
158         Vent vent = (Vent) m_vents[ventIndex.intValue()];
159         double weight = vent.getWeight();
160         groupWeight += weight;
161         System.out.println("  Vent at index "
162                            + ventIndex.intValue()
163                            + " with weight "
164                            + weight);
165       }
166       groupWeights += groupWeight;
167       System.out.println("  --> Group weight: " + groupWeight);
168     }
169     System.out.println("\n Average group weight: " + groupWeights / 8);
170   }
171 
172   /**
173    * Create vents with different weights.
174    *
175    * @author Klaus Meffert
176    * @since 3.2
177    */
178   public void makeVents() {
179     m_vents = new Vent[64];
180     for (int i = 0; i < m_vents.length; i++) {
181       // Set a weight between 290 and 310
182       double weight = 290 + Math.random() * 20;
183       Vent vent = new Vent(weight);
184       m_vents[i] = vent;
185     }
186   }
187 
188   /**
189    * Start the example
190    * @param args ignored
191    *
192    * @author Klaus Meffert
193    * @since 3.2
194    */
195   public static void main(String  [] args) {
196     try {
197       new MainClass();
198     } catch (Throwable   t) {
199       t.printStackTrace();
200       System.exit(1);
201     }
202   }
203 }
204
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