IBEA_Settings.java

//  IBEA_Settings.java 
//
//  Authors:
//       Antonio J. Nebro <antonio@lcc.uma.es>
//       Juan J. Durillo <durillo@lcc.uma.es>
//
//  Copyright (c) 2011 Antonio J. Nebro, Juan J. Durillo
//
//  This program is free software: you can redistribute it and/or modify
//  it under the terms of the GNU Lesser General Public License as published by
//  the Free Software Foundation, either version 3 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 Lesser General Public License for more details.
// 
//  You should have received a copy of the GNU Lesser General Public License
//  along with this program.  If not, see <http://www.gnu.org/licenses/>.

package jmetal.experiments.settings;

import java.util.HashMap;
import java.util.Properties;

import jmetal.core.Algorithm;
import jmetal.core.Operator;
import jmetal.core.Problem;
import jmetal.experiments.Settings;
import jmetal.metaheuristics.ibea.IBEA;
import jmetal.util.comparators.FitnessComparator;
import jmetal.operators.crossover.CrossoverFactory;
import jmetal.operators.mutation.MutationFactory;
import jmetal.operators.selection.BinaryTournament;
import jmetal.problems.ProblemFactory;
import jmetal.qualityIndicator.QualityIndicator;
import jmetal.util.JMException;
import jmetal.util.Configuration.*;

/**
 * Settings class of algorithm IBEA
 */
public class IBEA_Settings extends Settings {

	public int populationSize_   ;
	public int maxEvaluations_   ;
	public int archiveSize_      ;

	public double mutationProbability_   ;
	public double crossoverProbability_  ;

  public double crossoverDistributionIndex_ ;
  public double mutationDistributionIndex_  ;

	/**
	 * Constructor
	 */
	public IBEA_Settings(String problemName) {
		super(problemName) ;

		Object [] problemParams = {"Real"};
    try {
	    problem_ = (new ProblemFactory()).getProblem(problemName_, problemParams);
    } catch (JMException e) {
	    // TODO Auto-generated catch block
	    e.printStackTrace();
    }      

  	// Default settings
		populationSize_ = 100   ;
		maxEvaluations_ = 25000 ;
		archiveSize_    = 100 ;

		mutationProbability_  = 1.0/problem_.getNumberOfVariables() ;
		crossoverProbability_ = 0.9 ;

    crossoverDistributionIndex_ = 20.0  ;
    mutationDistributionIndex_  = 20.0  ;
	} // IBEA_Settings

	/**
	 * Configure NSGAII with user-defined parameter settings
	 * @return A NSGAII algorithm object
	 * @throws jmetal.util.JMException
	 */
	public Algorithm configure() throws JMException {
		Algorithm algorithm ;
		Operator  selection ;
		Operator  crossover ;
		Operator  mutation  ;

		QualityIndicator indicators ;

    HashMap  parameters ; // Operator parameters

		// Creating the problem
    Object [] problemParams = {"Real"};
    problem_ = (new ProblemFactory()).getProblem(problemName_, problemParams);      
		algorithm = new IBEA(problem_) ;

		// Algorithm parameters
		algorithm.setInputParameter("populationSize", populationSize_);
		algorithm.setInputParameter("maxEvaluations", maxEvaluations_);
		algorithm.setInputParameter("archiveSize", archiveSize_);


    // Mutation and Crossover for Real codification 
    parameters = new HashMap() ;
    parameters.put("probability", crossoverProbability_) ;
    parameters.put("distributionIndex", crossoverDistributionIndex_) ;
    crossover = CrossoverFactory.getCrossoverOperator("SBXCrossover", parameters);                   

    parameters = new HashMap() ;
    parameters.put("probability", mutationProbability_) ;
    parameters.put("distributionIndex", mutationDistributionIndex_) ;
    mutation = MutationFactory.getMutationOperator("PolynomialMutation", parameters);                    


    /* Selection Operator */
    parameters = new HashMap() ; 
    parameters.put("comparator", new FitnessComparator()) ;
    selection = new BinaryTournament(parameters);

		// Add the operators to the algorithm
		algorithm.addOperator("crossover",crossover);
		algorithm.addOperator("mutation",mutation);
		algorithm.addOperator("selection",selection);

		// Creating the indicator object
    if ((paretoFrontFile_!=null) && (!paretoFrontFile_.equals(""))) {
			indicators = new QualityIndicator(problem_, paretoFrontFile_);
			algorithm.setInputParameter("indicators", indicators) ;  
		} // if
		return algorithm ;
	} // configure
} // IBEA_Settings