Generating New Population for Genetic Algorithm in java

/* Generating New Population for Genetic Algorithm in java code */ 

import java.util.Collections;
import java.util.Vector;

public class Simulation 

  {
    private static int NUM_CHROMOSOMES = 10;
    private static int MAX_POWER = 10;
    private static int MAX_NUMBER = (int) Math.pow(2, MAX_POWER) - 1;
    private static int FITNESS_THRESHOLD = 5;
    private static float MUTATE = (float) .05;
   
    private Vector population;
    private boolean done = true;
    int numRuns = 0;
    int randomValue=0;
   
   
    public Simulation()

   {
        generateRandomPopulation();
    }
   
    private void generateRandomPopulation()

    {
        System.out.println("***Randomly Generating population with: " + NUM_CHROMOSOMES + " Chromosome(s)***");
       
        population = new Vector();
       
        for(int i = 0; i < NUM_CHROMOSOMES; ++i)

       {
            randomValue = (int) (Math.random()*MAX_NUMBER);
            population.add(new Chromosome(randomValue, MAX_POWER));
        }
        System.out.println("First Population: " + population +"\n");
    }
    public int getRandomvalue()
    {
        return randomValue;
    }

    public static int getMaxpower()
    {
        return MAX_POWER;
    }
   
    public void start()

      {
        Collections.sort(population);
        Chromosome fitess = (Chromosome) population.lastElement();
       
        done = fitess.fitness() >= MAX_POWER? true:false;
       
        if(done)

        {
            System.out.println("DONE, solution found: " + fitess);   
        }
        else

        {
            numRuns++;
            System.out.println("FITESS: " + fitess + " fitness: " + fitess.fitness());
            generateNewPopulation();
            start();
        }
    }
   
    private void generateNewPopulation()

    {
       
        System.out.println("***Generating New Population");
        Vector temp = new Vector();
       
        for(int i = 0; i < population.size()/2; ++i)

      {
            Chromosome p1 = selectParent();
            Chromosome p2 = selectParent();
            temp.add(cross1(p1, p2));
            temp.add(cross2(p1, p2));
        }
       
        population.clear();
        population.addAll(temp);
        System.out.println("New Population: " + population + "\n");
    }
   
    private Chromosome selectParent()

      {
        int delta = population.size();
        delta = NUM_CHROMOSOMES - NUM_CHROMOSOMES/2;
       
        int num = (int) (Math.random()*10 + 1);
        int index;
       
        if(num >= 4)

       {
            index = (int) (Math.random()*delta + NUM_CHROMOSOMES/2);
        }
        else

       {
            index = (int) (Math.random()*delta);   
        }
       
        return (Chromosome) population.get(index);
    }
   
    private Chromosome cross1(Chromosome parent1, Chromosome parent2)

      {
        String bitS1 = parent1.getBitString();
        String bitS2 = parent2.getBitString();
        int length = bitS1.length();
       
        String newBitString = bitS1.substring(0, length/2) + bitS2.substring(length/2, length);
        Chromosome offspring = new Chromosome();
        offspring.setBitString(newBitString);
       
        if(shouldMutate())

       {
            mutate(offspring);
        }
       
        return offspring;
    }
   
    private Chromosome cross2(Chromosome parent1, Chromosome parent2)

    {
        String bitS1 = parent1.getBitString();
        String bitS2 = parent2.getBitString();
        int length = bitS1.length();
       
        String newBitString = bitS2.substring(0, length/2) + bitS1.substring(length/2, length);
        Chromosome offspring = new Chromosome();
        offspring.setBitString(newBitString);
       
        if(shouldMutate())

       {
            mutate(offspring);
        }
       
        return offspring;
    }
   
    private boolean shouldMutate()

   {
        double num = Math.random();
        int number = (int) (num*100);
        num = (double) number/100;
        return (num <= MUTATE);
    }
   
    private void mutate(Chromosome offspring)

   {
        String s = offspring.getBitString();
        int num = s.length();
        int index = (int) (Math.random()*num);
        String newBit = flip(s.substring(index, index+1));
        String newBitString = s.substring(0, index) + newBit + s.substring(index+1, s.length());
        offspring.setBitString(newBitString);
    }
   
    private String flip(String s)

   {
        return s.equals("0")? "1":"0";
    }

    public static void main(String[] args) 

   {
        double average = 0;
        int sum = 0;
            Simulation s = new Simulation();
            s.start();
            sum = sum + s.numRuns;
            System.out.println("Number of runs: " + s.numRuns);
    }
}