GenerationalGA.java

package bsearch.algorithms;

import java.util.HashMap;

import org.nlogo.util.MersenneTwisterFast;

import bsearch.app.BehaviorSearchException;
import bsearch.app.SearchProtocol;
import bsearch.evaluation.SearchManager;
import bsearch.nlogolink.NetLogoLinkException;
import bsearch.representations.Chromosome;
import bsearch.representations.ChromosomeFactory;
import bsearch.space.SearchSpace;

@Deprecated
public strictfp class GenerationalGA extends AbstractSearchMethod{
	
	private double mutationRate = 0.01;
	private double crossoverRate = 0.7;
	private int populationSize = 50;

	public GenerationalGA()
	{
	}
	
	public String getName()
	{
		return "GenerationalGA";
	}
	public String getDescription()
	{
		return "A standard generational Genetic Algorithm wherein a new full replacement population is created in each generation. (Uses tournament selection with tournament size 3)";
	}	

	public void setSearchParams( HashMap<String , String> searchMethodParams ) throws SearchParameterException
	{
		mutationRate = validDoubleParam(searchMethodParams, "mutation-rate", 0.0, 1.0);
		crossoverRate = validDoubleParam(searchMethodParams, "crossover-rate", 0.0, 1.0);
		populationSize = validIntParam(searchMethodParams, "population-size", 2, 1000);
	}
	public HashMap<String , String> getSearchParams()
	{
		HashMap<String,String> params = new HashMap<String,String>();
		params.put("mutation-rate", Double.toString( mutationRate ));
		params.put("crossover-rate", Double.toString( crossoverRate ));
		params.put("population-size", Integer.toString( populationSize ));		
		return params;
	}
	public HashMap<String , String> getSearchParamsHelp()
	{
		HashMap<String,String> params = new HashMap<String,String>();
		params.put("mutation-rate", "likelihood of mutation occurring in each child");
		params.put("crossover-rate", "probability of using two parents to create a child (otherwise child is created asexually)");
		params.put("population-size", "the number of individuals in each generation");
		return params;
	}


	public void search( SearchSpace space , ChromosomeFactory cFactory, SearchProtocol protocol ,
			 SearchManager manager, MersenneTwisterFast rng ) 
		throws BehaviorSearchException, NetLogoLinkException, InterruptedException
	{
		Chromosome[] population = new Chromosome[populationSize];
		Chromosome[] newpopulation = new Chromosome[populationSize];
		
		for (int i = 0; i < populationSize; i++)
		{
			population[i] = cFactory.createChromosome(space, rng);
		}
		
		double[] fitness = manager.computeFitnessBatch(population, protocol.fitnessSamplingReplications, rng);
		
		while ( !manager.searchFinished() )
		{
		    int crossoverPairs = (int) (crossoverRate * populationSize / 2) ;
		    int newPopIndex = 0;
		    for (int i = 0; i < crossoverPairs; i++)
		    {
		    	Chromosome p1 = manager.tournamentSelect(population, fitness, 3, rng);
		    	Chromosome p2 = manager.tournamentSelect(population, fitness, 3, rng);
		    	Chromosome[] children = p1.crossoverWith( p2 , rng ) ;
		    	newpopulation[newPopIndex++] = children[0];
		    	newpopulation[newPopIndex++] = children[1];                	
		    }
		    while (newPopIndex < populationSize)
		    {
		    	newpopulation[newPopIndex++] = manager.tournamentSelect(population, fitness, 3, rng);
		    }
		    for (int i = 0; i < populationSize; i++)
		    {
		    	newpopulation[i] = newpopulation[i].mutate( mutationRate , rng );
		    }
		    // swap in new population
		    Chromosome[] temp = population;
		    population = newpopulation;
			newpopulation = temp;
			
			fitness = manager.computeFitnessBatch(population, protocol.fitnessSamplingReplications, rng);			
		}

	}


}