// pMOEAD_main.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.moead;
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.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 a parallel version of the MOEAD algorithm described in:
* A.J. Nebro, J.J. Durillo,
* "A Study of the parallelization of the multi-objective metaheuristic
* MOEA/D"
* LION 4, Venice, January 2010.
*/
public class pMOEAD_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.moead.MOEAD_main
* - jmetal.metaheuristics.moead.MOEAD_main problemName
* - jmetal.metaheuristics.moead.MOEAD_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
QualityIndicator indicators ; // Object to get quality indicators
HashMap parameters ; // Operator parameters
int numberOfThreads = 1 ;
String dataDirectory = "" ;
// Logger object and file to store log messages
logger_ = Configuration.logger_ ;
fileHandler_ = new FileHandler("pMOEAD.log");
logger_.addHandler(fileHandler_) ;
indicators = null ;
if (args.length == 1) { // args[0] = problem name
Object [] params = {"Real"};
problem = (new ProblemFactory()).getProblem(args[0],params);
} // if
else if (args.length == 2) { // args[0] = problem name, [1] = pareto front file
Object [] params = {"Real"};
problem = (new ProblemFactory()).getProblem(args[0],params);
indicators = new QualityIndicator(problem, args[1]) ;
} // if
else if (args.length == 3) { // args[0] = problem name, [1] = threads,
// [2] = data directory
Object [] params = {"Real"};
problem = (new ProblemFactory()).getProblem(args[0],params);
numberOfThreads = Integer.parseInt(args[1]) ;
dataDirectory = args[2] ;
} // if
else { // Problem + number of threads + data directory
problem = new Kursawe("Real", 3);
//problem = new Kursawe("BinaryReal", 3);
//problem = new Water("Real");
//problem = new ZDT1("ArrayReal", 100);
//problem = new ConstrEx("Real");
//problem = new DTLZ1("Real");
//problem = new OKA2("Real") ;
} // else
algorithm = new pMOEAD(problem);
// Algorithm parameters
numberOfThreads = 4 ;
algorithm.setInputParameter("populationSize",300);
algorithm.setInputParameter("maxEvaluations",150000);
algorithm.setInputParameter("numberOfThreads", numberOfThreads);
// Directory with the files containing the weight vectors used in
// Q. Zhang, W. Liu, and H Li, The Performance of a New Version of MOEA/D
// on CEC09 Unconstrained MOP Test Instances Working Report CES-491, School
// of CS & EE, University of Essex, 02/2009.
// http://dces.essex.ac.uk/staff/qzhang/MOEAcompetition/CEC09final/code/ZhangMOEADcode/moead0305.rar
algorithm.setInputParameter("dataDirectory",
"/Users/antonio/Softw/pruebas/data/MOEAD_parameters/Weight");
algorithm.setInputParameter("T", 20) ;
algorithm.setInputParameter("delta", 0.9) ;
algorithm.setInputParameter("nr", 2) ;
// Crossover operator
parameters = new HashMap() ;
parameters.put("CR", 1.0) ;
parameters.put("F", 0.5) ;
crossover = CrossoverFactory.getCrossoverOperator("DifferentialEvolutionCrossover", parameters);
crossover.setParameter("CR", 1.0);
crossover.setParameter("F", 0.5);
// Mutation operator
parameters = new HashMap() ;
parameters.put("probability", 1.0/problem.getNumberOfVariables()) ;
parameters.put("distributionIndex", 20.0) ;
mutation = MutationFactory.getMutationOperator("PolynomialMutation", parameters);
algorithm.addOperator("crossover",crossover);
algorithm.addOperator("mutation",mutation);
// Execute the Algorithm
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)) ;
} // if
} //main
} // pMOEAD_main