src/Chromosome.java

import java.util.ArrayList;
import java.util.Random;
import java.lang.Math;
public class Chromosome {
	public static final int GENG_LENGTH = 14;
	public static final int MAX_X = 127;
	public static final int MAX_Y = 127;
	private int x,y;
	private String gene;
	public int getX() {
		return x;
	}
	public int getY() {
		return y;
	}
	public String getGene() {
		return gene;
	}
	public Chromosome(int x,int y) {
		if(x > MAX_X || y > MAX_Y || x < 0 || y < 0)
			return;
		this.x = x;
		this.y = y;
		String tem = Integer.toBinaryString(x);

		for(int i = tem.length(); i < GENG_LENGTH/2; i++) {
			tem = "0" + tem; 
		}
		gene = tem;
		tem = Integer.toBinaryString(y);
		for(int i = tem.length(); i < GENG_LENGTH/2; i++) {
			tem = "0" + tem; 
		}
		gene = gene + tem;
	}
	public Chromosome(String gene) {
		if(gene.length() != Chromosome.GENG_LENGTH)
			return;
		this.gene = gene;
		String xStr = gene.substring(0, Chromosome.GENG_LENGTH/2);
		String yStr = gene.substring(Chromosome.GENG_LENGTH/2);
		this.x = Integer.parseInt(xStr,2);
		this.y = Integer.parseInt(yStr,2);

	}
	public String toString() {
		return "x:" + x + "\ty:" + y + "\tgene:"+gene;
	}
	public void selfMutation(String newGene) {
		if(newGene.length() != Chromosome.GENG_LENGTH)
			return;
		this.gene = newGene;
		String xStr = newGene.substring(0, Chromosome.GENG_LENGTH/2);
		String yStr = newGene.substring(Chromosome.GENG_LENGTH/2);
		this.x = Integer.parseInt(xStr,2);
		this.y = Integer.parseInt(yStr,2);
	}

	//初始化种群
	public static ArrayList<Chromosome> initGroup(int size) {
		ArrayList<Chromosome> list = new ArrayList<Chromosome>();
		Random random = new Random();
		for(int i = 0; i < size; i++) {
			int x = random.nextInt() % 128;
			int y = random.nextInt() % 128;
			x = x < 0? (-x):x;
			y = y < 0? (-y):y;
			list.add(new Chromosome(x,y));
		}
		return list;
	}
	//计算适应度
	public int calcFitness() {
		return x*x+y*y;
	}
	//选择运算
	public static ArrayList<Chromosome> selector(ArrayList<Chromosome> fatherGroup,int sonGroupSize) {
		ArrayList<Chromosome> sonGroup = new ArrayList<Chromosome>();
		int totalFitness = 0;
		double[] fitness = new double[fatherGroup.size()];
		for(Chromosome chrom : fatherGroup) {
			totalFitness += chrom.calcFitness();
		}
		int index = 0;
		//计算适应度
		for(Chromosome chrom : fatherGroup) {
			fitness[index] = chrom.calcFitness() / ((double)totalFitness);
			index++;
		}
		//计算累加适应度
		for(int i = 1; i < fitness.length; i++) {
			fitness[i] = fitness[i-1]+fitness[i];
		}
		//轮盘赌选择
		for(int i = 0; i < sonGroupSize; i++) {
			Random random = new Random();
			double probability = random.nextDouble();
			int choose;
			for(choose = 1; choose < fitness.length - 1; choose++) {
				if(probability < fitness[choose])
					break;
			}
			sonGroup.add(new Chromosome(fatherGroup.get(choose).getGene()));			
		}
		return sonGroup;
	}
	//交叉运算--one point
	public static ArrayList<Chromosome> corssover(ArrayList<Chromosome> fatherGroup,double probability) {
		ArrayList<Chromosome> sonGroup = new ArrayList<Chromosome>();
		sonGroup.addAll(fatherGroup);
		Random random = new Random();
		for(int k = 0; k < fatherGroup.size() / 2; k++) {
			if(probability > random.nextDouble()) {
				int i = 0,j = 0;
				do {
					i = random.nextInt(fatherGroup.size());
					j = random.nextInt(fatherGroup.size());
				} while(i == j);
				int position = random.nextInt(Chromosome.GENG_LENGTH);
				String parent1 = fatherGroup.get(i).getGene();
				String parent2 = fatherGroup.get(j).getGene();
				String son1 = parent1.substring(0, position) + parent2.substring(position);
				String son2 = parent2.substring(0, position) + parent1.substring(position);
				sonGroup.add(new Chromosome(son1));
				sonGroup.add(new Chromosome(son2));
			}
		}
		return sonGroup;
	}
	//变异
	public static void mutation(ArrayList<Chromosome> fatherGroup,double probability) {
		Random random = new Random();
		Chromosome bestOne = Chromosome.best(fatherGroup);
		fatherGroup.add(new Chromosome(bestOne.getGene()));
		for(Chromosome c : fatherGroup) {
			String newGene = c.getGene();
			for(int i = 0; i < newGene.length();i++){
				if(probability > random.nextDouble()) {
					String newChar = newGene.charAt(i) == '0'?"1":"0";
					newGene = newGene.substring(0, i) + newChar + newGene.substring(i+1);
				}
			}
			c.selfMutation(newGene);
		}
	}
	public static Chromosome best(ArrayList<Chromosome> group) {
		Chromosome bestOne = group.get(0);
		for(Chromosome c : group) {
			if(c.calcFitness() > bestOne.calcFitness())
				bestOne = c;
		}
		return bestOne;
	}
	//测试
	public static void main(String[] args) {
		final int GROUP_SIZE = 20;
		final double CORSSOVER_P = 0.6;
		final double MUTATION_P = 0.01;
		ArrayList<Chromosome> group = Chromosome.initGroup(GROUP_SIZE);
		Chromosome theBest;
		do{
			group = Chromosome.corssover(group, CORSSOVER_P);
			Chromosome.mutation(group, MUTATION_P);
			group = Chromosome.selector(group, GROUP_SIZE);
			theBest = Chromosome.best(group);
			System.out.println(theBest.calcFitness());
		}while(theBest.calcFitness() < 32258);
	}
}