generatinggeneticalgorithm.java

著名的开源仿真软件yale

/*
 *  YALE - Yet Another Learning Environment
 *  Copyright (C) 2002, 2003
 *      Simon Fischer, Ralf Klinkenberg, Ingo Mierswa, 
 *          Katharina Morik, Oliver Ritthoff
 *      Artificial Intelligence Unit
 *      Computer Science Department
 *      University of Dortmund
 *      44221 Dortmund,  Germany
 *  email: [e-mail]
 *  web:   http://yale.cs.uni-dortmund.de/
 *
 *  This program is free software; you can redistribute it and/or
 *  modify it under the terms of the GNU General Public License as 
 *  published by the Free Software Foundation; either version 2 of the
 *  License, or (at your option) any later version. 
 *
 *  This program is distributed in the hope that it will be useful, but
 *  WITHOUT ANY WARRANTY; without even the implied warranty of
 *  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
 *  General Public License for more details.
 *
 *  You should have received a copy of the GNU General Public License
 *  along with this program; if not, write to the Free Software
 *  Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307
 *  USA.
 */
package edu.udo.cs.yale.operator.features.ga;

import edu.udo.cs.yale.operator.parameter.*;
import edu.udo.cs.yale.operator.OperatorException;
import edu.udo.cs.yale.generator.*;
import edu.udo.cs.yale.operator.features.*;
import edu.udo.cs.yale.tools.LogService;

import java.util.ArrayList;
import java.util.List;

/** In contrast to its superclass {@link GeneticAlgorithm}, the {@link GeneratingGeneticAlgorithm}
 *  generates new attributes and thus can change the length of an individual. Therfore specialized mutation
 *  and crossover operators are being applied. Generators are chosen at random from a list of generators
 *  specified by boolean parameters.
 *
 *  @yale.reference Ritthoff/etal/2001a
 *  @yale.xmlclass GeneratingGeneticAlgorithm
 *  @author ingo
 *  @version $Id: GeneratingGeneticAlgorithm.java,v 2.5 2003/08/27 15:28:14 mierswa Exp $
 */
public class GeneratingGeneticAlgorithm extends GeneticAlgorithm {

    public void initApply() throws OperatorException {
	super.initApply();
	
	PopulationOperator generator = getGeneratingPopulationOperator();
	if (generator != null)
	    addPreEvaluationPopulationOperator(generator);
    }

    /** Returns an <code>UnbalancedCrossover</code>. */
    PopulationOperator getCrossoverPopulationOperator() {
	double pCrossover = getParameterAsDouble("p_crossover");
	int crossoverType = getParameterAsInt("crossover_type");
	return new UnbalancedCrossover(crossoverType, pCrossover, false);
    }

    /** Returns a specialized mutation, i.e. a <code>AttributeGenerator</code> */
    PopulationOperator getGeneratingPopulationOperator() {
	int    noOfNewAttributes = getParameterAsInt("max_number_of_new_attributes"); 
	double pGenerate         = getParameterAsDouble("p_generate");
	
	// erzeugt die Generatoren
	ArrayList generators = new ArrayList();
	
	if (getParameterAsBoolean("reciprocal_value")) {
	    FeatureGenerator g =  new ReciprocalValueGenerator(true);
	    generators.add(g);
	}
	if (getParameterAsBoolean("function_characteristica")) {
	    FeatureGenerator g =  new FunctionCharacteristicaGenerator();
	    generators.add(g);
	}
	if (getParameterAsBoolean("use_plus")) {
	    FeatureGenerator g =  new BasicArithmeticOperationGenerator(0, true);
	    generators.add(g);
	}
	if (getParameterAsBoolean("use_diff")) {
	    FeatureGenerator g =  new BasicArithmeticOperationGenerator(1, true);
	    generators.add(g);
	}
	if (getParameterAsBoolean("use_mult")) {
	    FeatureGenerator g =  new BasicArithmeticOperationGenerator(2, true);
	    generators.add(g);
	}
	if (getParameterAsBoolean("use_div")) {
	    FeatureGenerator g =  new BasicArithmeticOperationGenerator(3, true);
	    generators.add(g);
	}

	if (generators.size()==0) {
	    LogService.logMessage("No FeatureGenerators specified for " + getName() + ".", LogService.WARNING);
	} 
	
	// fuegt das Generieren in die PreEval - Liste ein.
	return new AttributeGenerator(pGenerate, noOfNewAttributes, generators);
    }    



    public List getParameterTypes() {
	List types = super.getParameterTypes();
	types.add(new ParameterTypeInt("max_number_of_new_attributes", "Max number of attributes to generate for an individual.", 0, Integer.MAX_VALUE, 1));
	types.add(new ParameterTypeDouble("p_generate", "Probability for an individual to be selected for generation.", 0, 1, 0.1));
	types.add(new ParameterTypeBoolean("reciprocal_value", "Generate reciprocal values.", true));
	types.add(new ParameterTypeBoolean("function_characteristica", "Generate function characteristica (for C9).", false));
	types.add(new ParameterTypeBoolean("use_plus", "Generate sums.", true));
	types.add(new ParameterTypeBoolean("use_diff", "Generate differences.", true));
	types.add(new ParameterTypeBoolean("use_mult", "Generate products.", true));
	types.add(new ParameterTypeBoolean("use_div", "Generate quotients.", true));
	return types;
    }
}