// pgGA_main.java
//
// Author:
// Antonio J. Nebro <antonio@lcc.uma.es>
//
// Copyright (c) 2013 Antonio J. Nebro
//
// 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.singleObjective.geneticAlgorithm;
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.singleObjective.Griewank;
import jmetal.util.JMException;
import jmetal.util.parallel.IParallelEvaluator;
import jmetal.util.parallel.MultithreadedEvaluator;
import java.util.HashMap;
/**
* This class runs a multithreaded single-objective generational
* genetic algorithm (GA).
*/
public class pgGA_main {
public static void main(String [] args) throws JMException, 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
//int bits ; // Length of bit string in the OneMax problem
HashMap parameters ; // Operator parameters
int threads = 4 ; // 0 - use all the available cores
IParallelEvaluator parallelEvaluator = new MultithreadedEvaluator(threads) ;
//problem = new Sphere("Real", 10) ;
problem = new Griewank("Real", 10) ;
algorithm = new pgGA(problem, parallelEvaluator) ; // Generational GA
/* Algorithm parameters*/
algorithm.setInputParameter("populationSize",100);
algorithm.setInputParameter("maxEvaluations", 2500000);
// 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);
/* Execute the Algorithm */
long initTime = System.currentTimeMillis();
SolutionSet population = algorithm.execute();
long estimatedTime = System.currentTimeMillis() - initTime;
System.out.println("Total execution time: " + estimatedTime);
/* Log messages */
System.out.println("Objectives values have been writen to file FUN");
population.printObjectivesToFile("FUN");
System.out.println("Variables values have been writen to file VAR");
population.printVariablesToFile("VAR");
} //main
} // pgGA_main