MOCell_main.java

//  SolutionSet.Java
//
//  Author:
//       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.metaheuristics.mocell;

import jmetal.core.Algorithm;
import jmetal.core.Operator;
import jmetal.core.Problem;
import jmetal.core.SolutionSet;
import jmetal.operators.crossover.CrossoverFactory;
import jmetal.operators.mutation.MutationFactory;
import jmetal.operators.selection.SelectionFactory;
import jmetal.problems.Kursawe;
import jmetal.problems.ProblemFactory;
import jmetal.qualityIndicator.QualityIndicator;
import jmetal.util.Configuration;
import jmetal.util.JMException;

import java.io.IOException;
import java.util.HashMap;
import java.util.logging.FileHandler;
import java.util.logging.Logger;

/**
 *  * This class executes the algorithms described in
 *   A.J. Nebro, J.J. Durillo, F. Luna, B. Dorronsoro, E. Alba 
 *   "Design Issues in a Multiobjective Cellular Genetic Algorithm." 
 *   Evolutionary Multi-Criterion Optimization. 4th International Conference, 
 *   EMO 2007. Sendai/Matsushima, Japan, March 2007.
 */
 public class MOCell_main {
  public static Logger      logger_ ;      // Logger object
  public static FileHandler fileHandler_ ; // FileHandler object
  
  /**
   * @param args Command line arguments. The first (optional) argument specifies 
   *             the problem to solve.
   * @throws JMException 
   * @throws IOException 
   * @throws SecurityException 
   * Usage: three options
   *      - jmetal.metaheuristics.mocell.MOCell_main
   *      - jmetal.metaheuristics.mocell.MOCell_main problemName
   *      - jmetal.metaheuristics.mocell.MOCell_main problemName ParetoFrontFile
   */
  public static void main(String [] args) throws JMException, SecurityException, IOException, ClassNotFoundException {
    Problem   problem   ;         // The problem to solve
    Algorithm algorithm ;         // The algorithm to use
    Operator  crossover ;         // Crossover operator
    Operator  mutation  ;         // Mutation operator
    Operator  selection ;         // Selection operator

    QualityIndicator indicators ; // Object to get quality indicators

    HashMap  parameters ; // Operator parameters

    // Logger object and file to store log messages
    logger_      = Configuration.logger_ ;
    fileHandler_ = new FileHandler("MOCell_main.log"); 
    logger_.addHandler(fileHandler_) ;
    
    indicators = null ;
    if (args.length == 1) {
      Object [] params = {"Real"};
      problem = (new ProblemFactory()).getProblem(args[0],params);
    } // if
    else if (args.length == 2) {
      Object [] params = {"Real"};
      problem = (new ProblemFactory()).getProblem(args[0],params);
      indicators = new QualityIndicator(problem, args[1]) ;
    } // if
    else { // Default problem
      problem = new Kursawe("Real", 3); 
      //problem = new Water("Real");
      //problem = new ZDT1("ArrayReal", 1000);
      //problem = new ZDT4("BinaryReal");
      //problem = new WFG1("Real");
      //problem = new DTLZ1("Real");
      //problem = new OKA2("Real") ;
    } // else

    //algorithm = new sMOCell1(problem_) ;
    //algorithm = new sMOCell2(problem_) ;
    //algorithm = new aMOCell1(problem_) ;
    //algorithm = new aMOCell2(problem_) ;
    //algorithm = new aMOCell3(problem_) ;
    algorithm = new MOCell(problem);
 
    // Algorithm parameters
    algorithm.setInputParameter("populationSize",100);
    algorithm.setInputParameter("archiveSize",100);
    algorithm.setInputParameter("maxEvaluations",25000);
    algorithm.setInputParameter("feedBack",20);
      
    // Mutation and Crossover for Real codification 
    parameters = new HashMap() ;
    parameters.put("probability", 0.9) ;
    parameters.put("distributionIndex", 20.0) ;
    crossover = CrossoverFactory.getCrossoverOperator("SBXCrossover", parameters);                   

    parameters = new HashMap() ;
    parameters.put("probability", 1.0/problem.getNumberOfVariables()) ;
    parameters.put("distributionIndex", 20.0) ;
    mutation = MutationFactory.getMutationOperator("PolynomialMutation", parameters);                    

    // Selection Operator 
    parameters = null ;
    selection = SelectionFactory.getSelectionOperator("BinaryTournament", parameters) ;         
    
    // Add the operators to the algorithm
    algorithm.addOperator("crossover",crossover);
    algorithm.addOperator("mutation",mutation);
    algorithm.addOperator("selection",selection);
    
    long initTime = System.currentTimeMillis();
    SolutionSet population = algorithm.execute();
    long estimatedTime = System.currentTimeMillis() - initTime;

    // Result messages 
    logger_.info("Total execution time: "+estimatedTime + "ms");
    logger_.info("Objectives values have been writen to file FUN");
    population.printObjectivesToFile("FUN");
    logger_.info("Variables values have been writen to file VAR");
    population.printVariablesToFile("VAR");      
    
    if (indicators != null) {
      logger_.info("Quality indicators") ;
      logger_.info("Hypervolume: " + indicators.getHypervolume(population)) ;
      logger_.info("GD         : " + indicators.getGD(population)) ;
      logger_.info("IGD        : " + indicators.getIGD(population)) ;
      logger_.info("Spread     : " + indicators.getSpread(population)) ;
      logger_.info("Epsilon    : " + indicators.getEpsilon(population)) ;
    } // if                   
  }//main
} // MOCell_main