Sudoku Genetic Algorithm java

GeneticOperators.java

import java.util.Random;

public class GeneticOperators {

    public static int[] initialize(int[] gene) {
        int dimensions = (int) Math.sqrt(gene.length);

        for (int i = 0; i < gene.length; i++) {
            if (gene[i] == 0) gene[i] = new Random().nextInt(dimensions) + 1;
        }

        return gene;
    }

    public static int[] randomMutation(int[] gene) {
        int dimensions = (int) Math.sqrt(gene.length);
        int[] mutation = gene;
        int rand = new Random().nextInt(gene.length);
        for (int i = 0; i < rand; i++)
            mutation = mutation(gene, new Random().nextInt(gene.length), new Random().nextInt(dimensions) + 1);


        return mutation;
    }

    public static int[] mutation(int[] gene) {
        int dimensions = (int) Math.sqrt(gene.length);
        int[] mutation = mutation(gene, new Random().nextInt(gene.length), new Random().nextInt(dimensions) + 1);

        return mutation;
    }


    public static int[] mutation(int[] gene, int index, int value) {
        gene[index] = value;

        return gene;
    }

    public static int[][] crossover(int[] gene1, int[] gene2) {
        int start = new Random().nextInt(gene1.length);
        int end = new Random().nextInt(gene1.length - start) + start;

        return crossover(gene1, gene2, start, end);
    }

    public static int[][] crossover(int[] gene1, int[] gene2, boolean singlePoint) {
        int start = (singlePoint) ? 0 : new Random().nextInt(gene1.length);
        int end = new Random().nextInt(gene1.length - start) + start;

        return crossover(gene1, gene2, start, end);
    }

    public static int[][] crossover(int[] gene1, int[] gene2, int start, int end) {
        int[][] newGene = new int[2][gene1.length];
        for (int i = 0; i < gene1.length; i++) {
            newGene[0][i] = (i >= start && i <= end) ? gene2[i] : gene1[i];
            newGene[1][i] = (i >= start && i <= end) ? gene1[i] : gene2[i];
        }
        return newGene;
    }
}

Main.java

import java.util.Random;
import java.util.Vector;

public class Main {
    public static void main(String[] args) {
        Random random = new Random();
        int populationSize = 50;
        int maxIterations = 5000;
        int iteration = 0;
        Sudoku.setInitialGene(new int[]{1, 0, 0, 4, 0, 0, 0, 0, 0, 3, 2, 0, 0, 0, 0, 0});
        Sudoku currentSudoku = new Sudoku(GeneticOperators.initialize(Sudoku.getInitialGene().clone()));

        while (currentSudoku.getFitnessValue() != 0 && iteration < maxIterations) {
            System.out.println("current: " + currentSudoku + ", iteration: " + iteration);
            Vector<Sudoku> population = new Vector<>();
            for (int i = 0; i < populationSize; i++) population.add(new Sudoku(currentSudoku.getGene().clone()));

            for (int i = 0; i < population.size(); i++) {
                if (random.nextBoolean())
                    population.get(i).mutation();
                else
                    population.get(i).crossover(population.get(random.nextInt(population.size())));
            }
            if (random.nextBoolean())
                currentSudoku = Sudoku.bestSelection(population);
            else
                currentSudoku = Sudoku.rouletteSelection(population);
            iteration++;
        }


        System.out.println("goal: " + currentSudoku + ", iteration: " + iteration);

    }


}

Sudoku.java

import java.util.Vector;

public class Sudoku {
    private static int[] initialGene;
    private int[] gene;
    private int fitnessValue;
    private double probability;

    public Sudoku(int[] gene) {
        this.gene = gene;
        fitnessValue = fitness();

    }


    public static Sudoku bestSelection(Vector<Sudoku> sudokus) {
        Sudoku min = sudokus.firstElement();
        for (Sudoku sudoku : sudokus)
            if (sudoku.fitnessValue < min.fitnessValue)
                min = sudoku;

        return min;
    }

    public static Sudoku rouletteSelection(Vector<Sudoku> sudokus) {
        int max = 0;
        for (Sudoku sudoku : sudokus)
            if (sudoku.fitnessValue > max) max = sudoku.fitnessValue;
//        int sum = 0;
//        for (Sudoku sudoku : sudokus)
//            sum += sudoku.getFitnessValue();
//        for (Sudoku sudoku : sudokus)
//            sudoku.setProbability(sudoku.getFitnessValue() / (sum * 1.0));

        int sum = 0;
        for (Sudoku sudoku : sudokus)
            sum += max - sudoku.fitnessValue;
        for (Sudoku sudoku : sudokus)
            sudoku.setProbability((max - sudoku.fitnessValue) / (sum * 1.0));

        double random = Math.random() * sum;
        int i;
        for (i = 0; i < sudokus.size() && random > 0; i++) {
            random -= max - sudokus.get(i).fitnessValue;
        }
        return sudokus.get(i - 1);
    }

    public void randomMutation() {
        int[] mutation = GeneticOperators.randomMutation(this.getGene());
        this.setGene(mutation);
    }

    public void mutation() {
        int[] mutation = GeneticOperators.mutation(this.getGene());
        this.setGene(mutation);
    }

    public void mutation(int index, int value) {
        int[] mutation = GeneticOperators.mutation(this.getGene(), index, value);
        this.setGene(mutation);
    }

    public static void randomMutation(Sudoku sudoku) {
        int[] mutation = GeneticOperators.randomMutation(sudoku.getGene());
        sudoku.setGene(mutation);
    }

    public static void mutation(Sudoku sudoku) {
        int[] mutation = GeneticOperators.mutation(sudoku.getGene());
        sudoku.setGene(mutation);
    }

    public static void mutation(Sudoku sudoku, int index, int value) {
        int[] mutation = GeneticOperators.mutation(sudoku.getGene(), index, value);
        sudoku.setGene(mutation);
    }

    public void crossover(Sudoku sudoku1, boolean singlePoint) {
        int[][] crossover = GeneticOperators.crossover(this.getGene(), sudoku1.getGene(), singlePoint);
        this.setGene(crossover[0]);
        sudoku1.setGene(crossover[1]);
    }

    public void crossover(Sudoku sudoku1) {
        int[][] crossover = GeneticOperators.crossover(this.getGene(), sudoku1.getGene());
        this.setGene(crossover[0]);
        sudoku1.setGene(crossover[1]);
    }

    public void crossover(Sudoku sudoku1, int start, int end) {
        int[][] crossover = GeneticOperators.crossover(this.getGene(), sudoku1.getGene(), start, end);
        this.setGene(crossover[0]);
        sudoku1.setGene(crossover[1]);
    }

    public static void crossover(Sudoku sudoku, Sudoku sudoku1, boolean singlePoint) {
        int[][] crossover = GeneticOperators.crossover(sudoku.getGene(), sudoku1.getGene(), singlePoint);
        sudoku.setGene(crossover[0]);
        sudoku1.setGene(crossover[1]);
    }

    public static void crossover(Sudoku sudoku, Sudoku sudoku1) {
        int[][] crossover = GeneticOperators.crossover(sudoku.getGene(), sudoku1.getGene());
        sudoku.setGene(crossover[0]);
        sudoku1.setGene(crossover[1]);
    }

    public static void crossover(Sudoku sudoku, Sudoku sudoku1, int start, int end) {
        int[][] crossover = GeneticOperators.crossover(sudoku.getGene(), sudoku1.getGene(), start, end);
        sudoku.setGene(crossover[0]);
        sudoku1.setGene(crossover[1]);
    }

    public int fitness() {
        return fitness(this.gene);
    }

    public static int fitness(int[] gene) {
        int fitness = 0;
        int[][] newGene = oneDToTwoD(gene);
        int[][] newInitialGene = oneDToTwoD(initialGene);
        for (int i = 0; i < newGene.length; i++) {
            boolean[] rowFlag = new boolean[newGene.length + 1];
            boolean[] colFlag = new boolean[newGene.length + 1];
            for (int j = 0; j < newGene.length; j++) {
                if (rowFlag[newGene[i][j]])
                    fitness++;
                if (colFlag[newGene[j][i]])
                    fitness++;
                if ((newInitialGene[i][j] != 0 && newInitialGene[i][j] != newGene[i][j]) || newGene[i][j] == 0)
                    fitness += 1000;
                rowFlag[newGene[i][j]] = true;
                colFlag[newGene[j][i]] = true;
            }
        }
        int blockSize = (int) Math.sqrt(newGene.length);
        for (int i = 0; i < newGene.length; i += blockSize) {
            for (int j = 0; j < newGene.length; j += blockSize) {
                boolean[] blockFlag = new boolean[newGene.length + 1];

                for (int k = 0; k < blockSize; k++) {
                    for (int l = 0; l < blockSize; l++) {
                        if (blockFlag[newGene[i + k][j + l]])
                            fitness++;
                        blockFlag[newGene[i + k][j + l]] = true;
                    }
                }
            }
        }
        return fitness;
    }

    public static int[] twoDToOneD(int[][] twoD) {
        int[] oneD = new int[twoD.length * twoD.length];
        for (int i = 0; i < oneD.length; i++)
            oneD[i] = twoD[i / twoD.length][i % twoD.length];

        return oneD;
    }

    public static int[][] oneDToTwoD(int[] oneD) {
        int[][] twoD = new int[(int) Math.sqrt(oneD.length)][(int) Math.sqrt(oneD.length)];
        for (int i = 0; i < oneD.length; i++)
            twoD[i / twoD.length][i % twoD.length] = oneD[i];

        return twoD;
    }

    public static int[] getInitialGene() {
        return initialGene;
    }

    public static void setInitialGene(int[] initialGene) {
        Sudoku.initialGene = initialGene;
    }

    public int[] getGene() {
        return gene;
    }

    public void setGene(int[] gene) {
        this.gene = gene;
        fitnessValue = fitness();
    }

    public int getFitnessValue() {
        return fitnessValue;
    }

    public void setFitnessValue(int fitnessValue) {
        this.fitnessValue = fitnessValue;
    }

    public double getProbability() {
        return probability;
    }

    public void setProbability(double probability) {
        this.probability = probability;
    }

    @Override
    public String toString() {
        String string = "Gene: ";
        int dimensions = (int) Math.sqrt(gene.length);
        for (int i : gene) {
            string += i;
        }
        for (int i = 0; i < gene.length; i++)
            string += ((i % dimensions == 0) ? "\n" : "") + gene[i] + " ";
        string += "\nFitness: " + fitnessValue;

        return string;
    }
}

|SampleOutput.txt

current: Gene: 1334134243241432
1 3 3 4 
1 3 4 2 
4 3 2 4 
1 4 3 2 
Fitness: 14, iteration: 0
current: Gene: 1314134243241432
1 3 1 4 
1 3 4 2 
4 3 2 4 
1 4 3 2 
Fitness: 13, iteration: 1
current: Gene: 1314234243241432
1 3 1 4 
2 3 4 2 
4 3 2 4 
1 4 3 2 
Fitness: 12, iteration: 2
current: Gene: 1314214243241432
1 3 1 4 
2 1 4 2 
4 3 2 4 
1 4 3 2 
Fitness: 11, iteration: 3
current: Gene: 1314214243241432
1 3 1 4 
2 1 4 2 
4 3 2 4 
1 4 3 2 
Fitness: 11, iteration: 4
current: Gene: 1314224243241432
1 3 1 4 
2 2 4 2 
4 3 2 4 
1 4 3 2 
Fitness: 12, iteration: 5
current: Gene: 1314324243241432
1 3 1 4 
3 2 4 2 
4 3 2 4 
1 4 3 2 
Fitness: 11, iteration: 6
current: Gene: 1314324343241432
1 3 1 4 
3 2 4 3 
4 3 2 4 
1 4 3 2 
Fitness: 10, iteration: 7
current: Gene: 1314324343241432
1 3 1 4 
3 2 4 3 
4 3 2 4 
1 4 3 2 
Fitness: 10, iteration: 8
current: Gene: 1314324343241433
1 3 1 4 
3 2 4 3 
4 3 2 4 
1 4 3 3 
Fitness: 12, iteration: 9
current: Gene: 1314324343211433
1 3 1 4 
3 2 4 3 
4 3 2 1 
1 4 3 3 
Fitness: 10, iteration: 10
current: Gene: 1314324343211433
1 3 1 4 
3 2 4 3 
4 3 2 1 
1 4 3 3 
Fitness: 10, iteration: 11
current: Gene: 1314324343211432
1 3 1 4 
3 2 4 3 
4 3 2 1 
1 4 3 2 
Fitness: 8, iteration: 12
current: Gene: 1314324343211432
1 3 1 4 
3 2 4 3 
4 3 2 1 
1 4 3 2 
Fitness: 8, iteration: 13
current: Gene: 1314324343211432
1 3 1 4 
3 2 4 3 
4 3 2 1 
1 4 3 2 
Fitness: 8, iteration: 14
current: Gene: 1314323343211432
1 3 1 4 
3 2 3 3 
4 3 2 1 
1 4 3 2 
Fitness: 10, iteration: 15
current: Gene: 1314321343211432
1 3 1 4 
3 2 1 3 
4 3 2 1 
1 4 3 2 
Fitness: 9, iteration: 16
current: Gene: 1314321343211432
1 3 1 4 
3 2 1 3 
4 3 2 1 
1 4 3 2 
Fitness: 9, iteration: 17
current: Gene: 1314321343211432
1 3 1 4 
3 2 1 3 
4 3 2 1 
1 4 3 2 
Fitness: 9, iteration: 18
current: Gene: 1314421343211432
1 3 1 4 
4 2 1 3 
4 3 2 1 
1 4 3 2 
Fitness: 8, iteration: 19
current: Gene: 1314424343211432
1 3 1 4 
4 2 4 3 
4 3 2 1 
1 4 3 2 
Fitness: 8, iteration: 20
current: Gene: 1314424343211132
1 3 1 4 
4 2 4 3 
4 3 2 1 
1 1 3 2 
Fitness: 9, iteration: 21
current: Gene: 1314424343211132
1 3 1 4 
4 2 4 3 
4 3 2 1 
1 1 3 2 
Fitness: 9, iteration: 22
current: Gene: 1314424343211132
1 3 1 4 
4 2 4 3 
4 3 2 1 
1 1 3 2 
Fitness: 9, iteration: 23
current: Gene: 1314424343211132
1 3 1 4 
4 2 4 3 
4 3 2 1 
1 1 3 2 
Fitness: 9, iteration: 24
current: Gene: 1314424343212132
1 3 1 4 
4 2 4 3 
4 3 2 1 
2 1 3 2 
Fitness: 7, iteration: 25
current: Gene: 1314424343212132
1 3 1 4 
4 2 4 3 
4 3 2 1 
2 1 3 2 
Fitness: 7, iteration: 26
current: Gene: 1314424343212132
1 3 1 4 
4 2 4 3 
4 3 2 1 
2 1 3 2 
Fitness: 7, iteration: 27
current: Gene: 1314424343212134
1 3 1 4 
4 2 4 3 
4 3 2 1 
2 1 3 4 
Fitness: 6, iteration: 28
current: Gene: 1314424343212134
1 3 1 4 
4 2 4 3 
4 3 2 1 
2 1 3 4 
Fitness: 6, iteration: 29
current: Gene: 1314424343212134
1 3 1 4 
4 2 4 3 
4 3 2 1 
2 1 3 4 
Fitness: 6, iteration: 30
current: Gene: 1314424323212134
1 3 1 4 
4 2 4 3 
2 3 2 1 
2 1 3 4 
Fitness: 8, iteration: 31
current: Gene: 1314424323212134
1 3 1 4 
4 2 4 3 
2 3 2 1 
2 1 3 4 
Fitness: 8, iteration: 32
current: Gene: 1314424323212234
1 3 1 4 
4 2 4 3 
2 3 2 1 
2 2 3 4 
Fitness: 11, iteration: 33
current: Gene: 1314424323232234
1 3 1 4 
4 2 4 3 
2 3 2 3 
2 2 3 4 
Fitness: 14, iteration: 34
current: Gene: 1314424323232234
1 3 1 4 
4 2 4 3 
2 3 2 3 
2 2 3 4 
Fitness: 14, iteration: 35
current: Gene: 1314424343232234
1 3 1 4 
4 2 4 3 
4 3 2 3 
2 2 3 4 
Fitness: 12, iteration: 36
current: Gene: 1314424343222234
1 3 1 4 
4 2 4 3 
4 3 2 2 
2 2 3 4 
Fitness: 11, iteration: 37
current: Gene: 1314424343221234
1 3 1 4 
4 2 4 3 
4 3 2 2 
1 2 3 4 
Fitness: 10, iteration: 38
current: Gene: 1314424343221234
1 3 1 4 
4 2 4 3 
4 3 2 2 
1 2 3 4 
Fitness: 10, iteration: 39
current: Gene: 1314424343221234
1 3 1 4 
4 2 4 3 
4 3 2 2 
1 2 3 4 
Fitness: 10, iteration: 40
current: Gene: 1314424343221234
1 3 1 4 
4 2 4 3 
4 3 2 2 
1 2 3 4 
Fitness: 10, iteration: 41
current: Gene: 1314424343221234
1 3 1 4 
4 2 4 3 
4 3 2 2 
1 2 3 4 
Fitness: 10, iteration: 42
current: Gene: 1314424343221234
1 3 1 4 
4 2 4 3 
4 3 2 2 
1 2 3 4 
Fitness: 10, iteration: 43
current: Gene: 1314424343221234
1 3 1 4 
4 2 4 3 
4 3 2 2 
1 2 3 4 
Fitness: 10, iteration: 44
current: Gene: 1314424343221234
1 3 1 4 
4 2 4 3 
4 3 2 2 
1 2 3 4 
Fitness: 10, iteration: 45
current: Gene: 1314424343221234
1 3 1 4 
4 2 4 3 
4 3 2 2 
1 2 3 4 
Fitness: 10, iteration: 46
current: Gene: 1314424343221234
1 3 1 4 
4 2 4 3 
4 3 2 2 
1 2 3 4 
Fitness: 10, iteration: 47
current: Gene: 1314424343221234
1 3 1 4 
4 2 4 3 
4 3 2 2 
1 2 3 4 
Fitness: 10, iteration: 48
current: Gene: 1314424343221234
1 3 1 4 
4 2 4 3 
4 3 2 2 
1 2 3 4 
Fitness: 10, iteration: 49
current: Gene: 1314424343221234
1 3 1 4 
4 2 4 3 
4 3 2 2 
1 2 3 4 
Fitness: 10, iteration: 50
current: Gene: 1314424343221234
1 3 1 4 
4 2 4 3 
4 3 2 2 
1 2 3 4 
Fitness: 10, iteration: 51
current: Gene: 1314424343221234
1 3 1 4 
4 2 4 3 
4 3 2 2 
1 2 3 4 
Fitness: 10, iteration: 52
current: Gene: 1314424343221234
1 3 1 4 
4 2 4 3 
4 3 2 2 
1 2 3 4 
Fitness: 10, iteration: 53
current: Gene: 1314424343221232
1 3 1 4 
4 2 4 3 
4 3 2 2 
1 2 3 2 
Fitness: 12, iteration: 54
current: Gene: 1314424343221232
1 3 1 4 
4 2 4 3 
4 3 2 2 
1 2 3 2 
Fitness: 12, iteration: 55
current: Gene: 1314424343241232
1 3 1 4 
4 2 4 3 
4 3 2 4 
1 2 3 2 
Fitness: 11, iteration: 56
current: Gene: 1314424343211232
1 3 1 4 
4 2 4 3 
4 3 2 1 
1 2 3 2 
Fitness: 9, iteration: 57
current: Gene: 1314424343211232
1 3 1 4 
4 2 4 3 
4 3 2 1 
1 2 3 2 
Fitness: 9, iteration: 58
current: Gene: 1314424343213232
1 3 1 4 
4 2 4 3 
4 3 2 1 
3 2 3 2 
Fitness: 10, iteration: 59
current: Gene: 1314424343213232
1 3 1 4 
4 2 4 3 
4 3 2 1 
3 2 3 2 
Fitness: 10, iteration: 60
current: Gene: 1314424343213232
1 3 1 4 
4 2 4 3 
4 3 2 1 
3 2 3 2 
Fitness: 10, iteration: 61
current: Gene: 1314424343213234
1 3 1 4 
4 2 4 3 
4 3 2 1 
3 2 3 4 
Fitness: 9, iteration: 62
current: Gene: 1314424343211234
1 3 1 4 
4 2 4 3 
4 3 2 1 
1 2 3 4 
Fitness: 8, iteration: 63
current: Gene: 1314424343211234
1 3 1 4 
4 2 4 3 
4 3 2 1 
1 2 3 4 
Fitness: 8, iteration: 64
current: Gene: 1314424343211234
1 3 1 4 
4 2 4 3 
4 3 2 1 
1 2 3 4 
Fitness: 8, iteration: 65
current: Gene: 1314324343211234
1 3 1 4 
3 2 4 3 
4 3 2 1 
1 2 3 4 
Fitness: 8, iteration: 66
current: Gene: 1414324343211234
1 4 1 4 
3 2 4 3 
4 3 2 1 
1 2 3 4 
Fitness: 7, iteration: 67
current: Gene: 1414324243211234
1 4 1 4 
3 2 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 7, iteration: 68
current: Gene: 1414324243211234
1 4 1 4 
3 2 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 7, iteration: 69
current: Gene: 1414324243211234
1 4 1 4 
3 2 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 7, iteration: 70
current: Gene: 1414324243211234
1 4 1 4 
3 2 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 7, iteration: 71
current: Gene: 1414324243211234
1 4 1 4 
3 2 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 7, iteration: 72
current: Gene: 1414324243211234
1 4 1 4 
3 2 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 7, iteration: 73
current: Gene: 1414324243211234
1 4 1 4 
3 2 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 7, iteration: 74
current: Gene: 1414324243211234
1 4 1 4 
3 2 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 7, iteration: 75
current: Gene: 1414324243211234
1 4 1 4 
3 2 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 7, iteration: 76
current: Gene: 1414324243211234
1 4 1 4 
3 2 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 7, iteration: 77
current: Gene: 1414314243211234
1 4 1 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 78
current: Gene: 1414314243211234
1 4 1 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 79
current: Gene: 1414314243211234
1 4 1 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 80
current: Gene: 1414344243211234
1 4 1 4 
3 4 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 8, iteration: 81
current: Gene: 1414314243211234
1 4 1 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 82
current: Gene: 1414314243211231
1 4 1 4 
3 1 4 2 
4 3 2 1 
1 2 3 1 
Fitness: 8, iteration: 83
current: Gene: 1414314243211231
1 4 1 4 
3 1 4 2 
4 3 2 1 
1 2 3 1 
Fitness: 8, iteration: 84
current: Gene: 1414314243211231
1 4 1 4 
3 1 4 2 
4 3 2 1 
1 2 3 1 
Fitness: 8, iteration: 85
current: Gene: 1414314243211231
1 4 1 4 
3 1 4 2 
4 3 2 1 
1 2 3 1 
Fitness: 8, iteration: 86
current: Gene: 1414314243211231
1 4 1 4 
3 1 4 2 
4 3 2 1 
1 2 3 1 
Fitness: 8, iteration: 87
current: Gene: 1414314243211231
1 4 1 4 
3 1 4 2 
4 3 2 1 
1 2 3 1 
Fitness: 8, iteration: 88
current: Gene: 1414314243211233
1 4 1 4 
3 1 4 2 
4 3 2 1 
1 2 3 3 
Fitness: 7, iteration: 89
current: Gene: 1414314343211233
1 4 1 4 
3 1 4 3 
4 3 2 1 
1 2 3 3 
Fitness: 9, iteration: 90
current: Gene: 1114314343211233
1 1 1 4 
3 1 4 3 
4 3 2 1 
1 2 3 3 
Fitness: 11, iteration: 91
current: Gene: 1114314343211233
1 1 1 4 
3 1 4 3 
4 3 2 1 
1 2 3 3 
Fitness: 11, iteration: 92
current: Gene: 1214314343211233
1 2 1 4 
3 1 4 3 
4 3 2 1 
1 2 3 3 
Fitness: 9, iteration: 93
current: Gene: 1214314343211233
1 2 1 4 
3 1 4 3 
4 3 2 1 
1 2 3 3 
Fitness: 9, iteration: 94
current: Gene: 1214314343211233
1 2 1 4 
3 1 4 3 
4 3 2 1 
1 2 3 3 
Fitness: 9, iteration: 95
current: Gene: 1214314343211234
1 2 1 4 
3 1 4 3 
4 3 2 1 
1 2 3 4 
Fitness: 7, iteration: 96
current: Gene: 1214314343211234
1 2 1 4 
3 1 4 3 
4 3 2 1 
1 2 3 4 
Fitness: 7, iteration: 97
current: Gene: 1214314343211234
1 2 1 4 
3 1 4 3 
4 3 2 1 
1 2 3 4 
Fitness: 7, iteration: 98
current: Gene: 1214314343211234
1 2 1 4 
3 1 4 3 
4 3 2 1 
1 2 3 4 
Fitness: 7, iteration: 99
current: Gene: 1214314343211234
1 2 1 4 
3 1 4 3 
4 3 2 1 
1 2 3 4 
Fitness: 7, iteration: 100
current: Gene: 1214314243211234
1 2 1 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 101
current: Gene: 1214314243211234
1 2 1 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 102
current: Gene: 1214314243211234
1 2 1 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 103
current: Gene: 1214314243211234
1 2 1 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 104
current: Gene: 1214314243211234
1 2 1 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 105
current: Gene: 1214314243211234
1 2 1 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 106
current: Gene: 1214314243211234
1 2 1 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 107
current: Gene: 1214314243211234
1 2 1 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 108
current: Gene: 1214314243211234
1 2 1 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 109
current: Gene: 1214314243211234
1 2 1 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 110
current: Gene: 1214314243211234
1 2 1 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 111
current: Gene: 1214314243211234
1 2 1 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 112
current: Gene: 1214314243211234
1 2 1 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 113
current: Gene: 1214314243211234
1 2 1 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 114
current: Gene: 1214314243211234
1 2 1 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 115
current: Gene: 1214314243211234
1 2 1 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 116
current: Gene: 1214314243211234
1 2 1 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 117
current: Gene: 1214314243211234
1 2 1 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 118
current: Gene: 1214314243211234
1 2 1 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 119
current: Gene: 1234314243211234
1 2 3 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 120
current: Gene: 1234314243221234
1 2 3 4 
3 1 4 2 
4 3 2 2 
1 2 3 4 
Fitness: 9, iteration: 121
current: Gene: 1234314243221234
1 2 3 4 
3 1 4 2 
4 3 2 2 
1 2 3 4 
Fitness: 9, iteration: 122
current: Gene: 1234314243211234
1 2 3 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 123
current: Gene: 1234314243211214
1 2 3 4 
3 1 4 2 
4 3 2 1 
1 2 1 4 
Fitness: 7, iteration: 124
current: Gene: 1234314243211234
1 2 3 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 125
current: Gene: 1234314243211234
1 2 3 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 126
current: Gene: 1234314243211234
1 2 3 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 127
current: Gene: 1234314243211234
1 2 3 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 128
current: Gene: 1234314243211234
1 2 3 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 129
current: Gene: 1234314243211234
1 2 3 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 130
current: Gene: 1234314243211234
1 2 3 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 131
current: Gene: 1234314243211234
1 2 3 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 132
current: Gene: 1234314243211234
1 2 3 4 
3 1 4 2 
4 3 2 1 
1 2 3 4 
Fitness: 6, iteration: 133
current: Gene: 1234314243214234
1 2 3 4 
3 1 4 2 
4 3 2 1 
4 2 3 4 
Fitness: 8, iteration: 134
current: Gene: 1234314243214234
1 2 3 4 
3 1 4 2 
4 3 2 1 
4 2 3 4 
Fitness: 8, iteration: 135
current: Gene: 1234314243214234
1 2 3 4 
3 1 4 2 
4 3 2 1 
4 2 3 4 
Fitness: 8, iteration: 136
current: Gene: 1234314243214231
1 2 3 4 
3 1 4 2 
4 3 2 1 
4 2 3 1 
Fitness: 8, iteration: 137
current: Gene: 1234314243214231
1 2 3 4 
3 1 4 2 
4 3 2 1 
4 2 3 1 
Fitness: 8, iteration: 138
current: Gene: 1234314243214233
1 2 3 4 
3 1 4 2 
4 3 2 1 
4 2 3 3 
Fitness: 8, iteration: 139
current: Gene: 1234314243214233
1 2 3 4 
3 1 4 2 
4 3 2 1 
4 2 3 3 
Fitness: 8, iteration: 140
current: Gene: 1234314243214433
1 2 3 4 
3 1 4 2 
4 3 2 1 
4 4 3 3 
Fitness: 9, iteration: 141
current: Gene: 1234314243214233
1 2 3 4 
3 1 4 2 
4 3 2 1 
4 2 3 3 
Fitness: 8, iteration: 142
current: Gene: 1234314243214233
1 2 3 4 
3 1 4 2 
4 3 2 1 
4 2 3 3 
Fitness: 8, iteration: 143
current: Gene: 1234314243214243
1 2 3 4 
3 1 4 2 
4 3 2 1 
4 2 4 3 
Fitness: 7, iteration: 144
current: Gene: 1234311243214243
1 2 3 4 
3 1 1 2 
4 3 2 1 
4 2 4 3 
Fitness: 6, iteration: 145
current: Gene: 1234311243212243
1 2 3 4 
3 1 1 2 
4 3 2 1 
2 2 4 3 
Fitness: 5, iteration: 146
current: Gene: 1234311243212243
1 2 3 4 
3 1 1 2 
4 3 2 1 
2 2 4 3 
Fitness: 5, iteration: 147
current: Gene: 1234341243212243
1 2 3 4 
3 4 1 2 
4 3 2 1 
2 2 4 3 
Fitness: 3, iteration: 148
current: Gene: 1234341243212243
1 2 3 4 
3 4 1 2 
4 3 2 1 
2 2 4 3 
Fitness: 3, iteration: 149
current: Gene: 1234441243212243
1 2 3 4 
4 4 1 2 
4 3 2 1 
2 2 4 3 
Fitness: 6, iteration: 150
current: Gene: 1234441243211243
1 2 3 4 
4 4 1 2 
4 3 2 1 
1 2 4 3 
Fitness: 5, iteration: 151
current: Gene: 1244441243211243
1 2 4 4 
4 4 1 2 
4 3 2 1 
1 2 4 3 
Fitness: 8, iteration: 152
current: Gene: 1244341243211243
1 2 4 4 
3 4 1 2 
4 3 2 1 
1 2 4 3 
Fitness: 5, iteration: 153
current: Gene: 1244321243211243
1 2 4 4 
3 2 1 2 
4 3 2 1 
1 2 4 3 
Fitness: 8, iteration: 154
current: Gene: 1234321243211243
1 2 3 4 
3 2 1 2 
4 3 2 1 
1 2 4 3 
Fitness: 5, iteration: 155
current: Gene: 1234321243211243
1 2 3 4 
3 2 1 2 
4 3 2 1 
1 2 4 3 
Fitness: 5, iteration: 156
current: Gene: 1234341243211243
1 2 3 4 
3 4 1 2 
4 3 2 1 
1 2 4 3 
Fitness: 2, iteration: 157
current: Gene: 1234341243211243
1 2 3 4 
3 4 1 2 
4 3 2 1 
1 2 4 3 
Fitness: 2, iteration: 158
current: Gene: 1244341243211243
1 2 4 4 
3 4 1 2 
4 3 2 1 
1 2 4 3 
Fitness: 5, iteration: 159
current: Gene: 1244341443211243
1 2 4 4 
3 4 1 4 
4 3 2 1 
1 2 4 3 
Fitness: 8, iteration: 160
current: Gene: 1244341443211243
1 2 4 4 
3 4 1 4 
4 3 2 1 
1 2 4 3 
Fitness: 8, iteration: 161
current: Gene: 1224341443211243
1 2 2 4 
3 4 1 4 
4 3 2 1 
1 2 4 3 
Fitness: 7, iteration: 162
current: Gene: 1224341443211243
1 2 2 4 
3 4 1 4 
4 3 2 1 
1 2 4 3 
Fitness: 7, iteration: 163
current: Gene: 1224341343211243
1 2 2 4 
3 4 1 3 
4 3 2 1 
1 2 4 3 
Fitness: 6, iteration: 164
current: Gene: 1234341343211243
1 2 3 4 
3 4 1 3 
4 3 2 1 
1 2 4 3 
Fitness: 5, iteration: 165
current: Gene: 1234341343211243
1 2 3 4 
3 4 1 3 
4 3 2 1 
1 2 4 3 
Fitness: 5, iteration: 166
current: Gene: 1234341343211243
1 2 3 4 
3 4 1 3 
4 3 2 1 
1 2 4 3 
Fitness: 5, iteration: 167
current: Gene: 1234341343211243
1 2 3 4 
3 4 1 3 
4 3 2 1 
1 2 4 3 
Fitness: 5, iteration: 168
current: Gene: 1234341343211243
1 2 3 4 
3 4 1 3 
4 3 2 1 
1 2 4 3 
Fitness: 5, iteration: 169
current: Gene: 1234341343211243
1 2 3 4 
3 4 1 3 
4 3 2 1 
1 2 4 3 
Fitness: 5, iteration: 170
current: Gene: 1234341343211243
1 2 3 4 
3 4 1 3 
4 3 2 1 
1 2 4 3 
Fitness: 5, iteration: 171
current: Gene: 1234341343211243
1 2 3 4 
3 4 1 3 
4 3 2 1 
1 2 4 3 
Fitness: 5, iteration: 172
current: Gene: 1234341243211243
1 2 3 4 
3 4 1 2 
4 3 2 1 
1 2 4 3 
Fitness: 2, iteration: 173
current: Gene: 1234341243211243
1 2 3 4 
3 4 1 2 
4 3 2 1 
1 2 4 3 
Fitness: 2, iteration: 174
current: Gene: 1234341243231243
1 2 3 4 
3 4 1 2 
4 3 2 3 
1 2 4 3 
Fitness: 5, iteration: 175
current: Gene: 1234341243211243
1 2 3 4 
3 4 1 2 
4 3 2 1 
1 2 4 3 
Fitness: 2, iteration: 176
current: Gene: 1234341243211243
1 2 3 4 
3 4 1 2 
4 3 2 1 
1 2 4 3 
Fitness: 2, iteration: 177
current: Gene: 1234341243211243
1 2 3 4 
3 4 1 2 
4 3 2 1 
1 2 4 3 
Fitness: 2, iteration: 178
current: Gene: 1234341243213243
1 2 3 4 
3 4 1 2 
4 3 2 1 
3 2 4 3 
Fitness: 4, iteration: 179
current: Gene: 1234341243212243
1 2 3 4 
3 4 1 2 
4 3 2 1 
2 2 4 3 
Fitness: 3, iteration: 180
current: Gene: 1234341243212243
1 2 3 4 
3 4 1 2 
4 3 2 1 
2 2 4 3 
Fitness: 3, iteration: 181
goal: Gene: 1234341243212143
1 2 3 4 
3 4 1 2 
4 3 2 1 
2 1 4 3 
Fitness: 0, iteration: 182