praktikum-holons/src/algorithms/geneticAlgorithm/Components/GeneticAlgo.java

package algorithms.geneticAlgorithm.Components;

import java.util.ArrayList;
import java.util.Random;

import algorithms.geneticAlgorithm.holegGA.Components.HolegIndividual;

public class GeneticAlgo<I extends HolegIndividual> {

	public int popSize;
	public ArrayList<I> population;
	
	public GAIndividualFactory<I> randomFactory;
	public GASelectionStrategy<I> selector;
	public GACrossoverStrategy<I> reproducer;
	public GAMutationStrategy<I> mutator;
	public GAFittnessFunctionStrategy<I> fittnessFunction;
	public double topPercent;
	public double buttomPercent;
	
	public GeneticAlgo(GASelectionStrategy<I> selection, GACrossoverStrategy<I> crossover, GAMutationStrategy<I> mutator, 
			GAFittnessFunctionStrategy<I> fittnessFkt, GAIndividualFactory<I> factory, int popSize){
		
		this.selector = selection;
		this.reproducer = crossover;
		this.mutator = mutator;
		this.fittnessFunction = fittnessFkt;
		randomFactory = factory;
		this.popSize = popSize;
		
		population = new ArrayList<I>();
		topPercent = 0.0;
		
		//generateRandomPopulation();
	}

	public void generateRandomPopulation() {
		population = new ArrayList<I>();
		for(int i = 0; i < popSize; i++){
			population.add(randomFactory.createRandomIndividual());
			fittnessFunction.calculateFittness(population.get(i));
		}
	}
	
	public void createNextGeneration(){
		ArrayList<I> nextGen = new ArrayList<I>();
		
		
		int topBound = (int) Math.ceil(topPercent * popSize);
		//int topBound = 1;
		population = getSortedPopulation();
		
		for(I individual : population.subList(0, topBound)){
			ArrayList<I> childs = new ArrayList<I>();
			childs.add(individual);
			childs.add(individual);
			childs = reproducer.crossOver(childs);
			for(I i : childs){
				i.addLogEntry("Top % from previous gen");
				fittnessFunction.calculateFittness(i);
				nextGen.add(i);
			}
		}
		
		selector.setCurrentPopulation(population);
		while(nextGen.size() < popSize){
			ArrayList<I> freshInds = new ArrayList<I>();
			freshInds = reproducer.crossOver(selector.selectIndividuals());
			for(I i : freshInds){
				i = mutator.mutateIndividual(i);
				fittnessFunction.calculateFittness(i);
			}
			nextGen.addAll(freshInds);
		}
		
		if(popSize % 2 == 1){
			Random rnd = new Random();
			nextGen.remove(rnd.nextInt(popSize));
		}
		population = nextGen;
	}
	
	public ArrayList<I> getPopulation(){
		return population;
	}
	
	public ArrayList<I> getSortedPopulation(){
		return sortPopulation(population);
	}
	
	public ArrayList<I> sortPopulation(ArrayList<I> individuals){
		ArrayList<I> sortedList = new ArrayList<I>();
		for(I hI : individuals){
			for(int i = 0; i <= sortedList.size(); i++){
				if(i == sortedList.size()){
					sortedList.add(hI);
					break;
				}else if(sortedList.get(i).getFittness() < hI.getFittness()){
					sortedList.add(i, hI);
					break;
				}
			}
		}
		return sortedList;
	}
}