Source Code Cross Referenced for MaxFunction.java in  » Development » jgap » examples » simpleBoolean » Java Source Code / Java DocumentationJava Source Code and Java Documentation

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Java Source Code / Java Documentation » Development » jgap » examples.simpleBoolean 
Source Cross Referenced  Class Diagram Java Document (Java Doc) 


01:        /*
02:         * This file is part of JGAP.
03:         *
04:         * JGAP offers a dual license model containing the LGPL as well as the MPL.
05:         *
06:         * For licencing information please see the file license.txt included with JGAP
07:         * or have a look at the top of class org.jgap.Chromosome which representatively
08:         * includes the JGAP license policy applicable for any file delivered with JGAP.
09:         */
10:        package examples.simpleBoolean;
11:
12:        import org.jgap.*;
13:        import org.jgap.impl.*;
14:
15:        /**
16:         * Fitness function for our example. See evaluate(...) method for details.
17:         *
18:         * @author Neil Rotstan
19:         * @author Klaus Meffert
20:         * @since 2.0
21:         */
22:        public class MaxFunction extends FitnessFunction {
23:            /** String containing the CVS revision. Read out via reflection!*/
24:            private final static String CVS_REVISION = "$Revision: 1.5 $";
25:
26:            /**
27:             * This example implementation calculates the fitness value of Chromosomes
28:             * using BooleanAllele implementations. It simply returns a fitness value
29:             * equal to the numeric binary value of the bits. In other words, it
30:             * optimizes the numeric value of the genes interpreted as bits. It should
31:             * be noted that, for clarity, this function literally returns the binary
32:             * value of the Chromosome's genes interpreted as bits. However, it would
33:             * be better to return the value raised to a fixed power to exaggerate the
34:             * difference between the higher values. For example, the difference
35:             * between 254 and 255 is only about .04%, which isn't much incentive for
36:             * the selector to choose 255 over 254. However, if you square the values,
37:             * you then get 64516 and 65025, which is a difference of 0.8% -- twice
38:             * as much and, therefore, twice the incentive to select the higher
39:             * value.
40:             *
41:             * @param a_subject the Chromosome to be evaluated
42:             * @return defect rate of our problem
43:             *
44:             * @author Neil Rotstan
45:             * @author Klaus Meffert
46:             * @since 2.0
47:             */
48:            public double evaluate(IChromosome a_subject) {
49:                int total = 0;
50:
51:                for (int i = 0; i < a_subject.size(); i++) {
52:                    BooleanGene value = (BooleanGene) a_subject
53:                            .getGene(a_subject.size() - (i + 1));
54:                    if (value.booleanValue()) {
55:                        total += Math.pow(2.0, (double) i);
56:                    }
57:                }
58:
59:                return total;
60:            }
61:        }
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