001    package org.jaga.fitnessEvaluation.largerNumbers;
002    
003    import org.jaga.individualRepresentation.greycodedNumbers.NDecimalsIndividual;
004    import org.jaga.definitions.*;
005    import org.jaga.selection.*;
006    
007    /**
008     * TODO: Complete these comments.
009     *
010     * <p><u>Project:</u> JAGA - Java API for Genetic Algorithms.</p>
011     *
012     * <p><u>Company:</u> University College London and JAGA.Org
013     *    (<a href="http://www.jaga.org" target="_blank">http://www.jaga.org</a>).
014     * </p>
015     *
016     * <p><u>Copyright:</u> (c) 2004 by G. Paperin.<br/>
017     *    This program is free software; you can redistribute it and/or modify
018     *    it under the terms of the GNU General Public License as published by
019     *    the Free Software Foundation, ONLY if you include a note of the original
020     *    author(s) in any redistributed/modified copy.<br/>
021     *    This program is distributed in the hope that it will be useful,
022     *    but WITHOUT ANY WARRANTY; without even the implied warranty of
023     *    MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
024     *    GNU General Public License for more details.<br/>
025     *    You should have received a copy of the GNU General Public License
026     *    along with this program; if not, write to the Free Software
027     *    Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA  02111-1307  USA
028     *    or see http://www.gnu.org/licenses/gpl.html</p>
029     *
030     * @author Greg Paperin (greg@jaga.org)
031     *
032     * @version JAGA public release 1.0 beta
033     */
034    
035    public class LargerDecimals implements FitnessEvaluationAlgorithm {
036    
037            public LargerDecimals() {
038            }
039    
040            public Class getApplicableClass() {
041                    return NDecimalsIndividual.class;
042            }
043    
044            public Fitness evaluateFitness(Individual individual, int age, Population population, GAParameterSet params) {
045                    double x = ((NDecimalsIndividual) individual).getDoubleValue(0);
046                    Fitness fit = new AbsoluteFitness(x);
047                    return fit;
048            }
049    
050    }