Genetic_Algorithm_Notebook.ipynb

{
  "cells": [
    {
      "cell_type": "code",
      "execution_count": 1,
      "metadata": {
        "id": "ctCWyqoVVpst"
      },
      "outputs": [],
      "source": [
        "import numpy as np\n",
        "import matplotlib.pyplot\n",
        "import random\n",
        "import math"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 2,
      "metadata": {
        "id": "YC-eLJ3lYiqr"
      },
      "outputs": [],
      "source": [
        "# Used to convert integer to binary string\n",
        "bin8 = lambda x : ''.join(reversed( [str((x >> i) & 1) for i in range(8)] ) )"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 3,
      "metadata": {
        "id": "9o1ENCEQ67Us"
      },
      "outputs": [],
      "source": [
        "# To calculate fitness function 1 \n",
        "def fitness_fun1(x):\n",
        "  return math.sin(math.pi * x/256)\n",
        "\n",
        "# To calculate fitness function 2\n",
        "def fitness_fun2(x,y):\n",
        "  return -1 * ((x-3.14)**2 + (y-2.72)**2 + math.sin(3*x + 1.41) + math.sin(4*y - 1.73))"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "id": "avePtCs09I7a"
      },
      "outputs": [],
      "source": [
        "# Function to computer xor\n",
        "def xor_c(a, b):\n",
        "    return '0' if(a == b) else '1';\n",
        " \n",
        "# Function to flip bit\n",
        "def flip(c):\n",
        "    return '1' if(c == '0') else '0';\n",
        " \n",
        "# Function to convert from binary to gray code\n",
        "def binarytoGray(binary):\n",
        "    gray = \"\";\n",
        "    gray += binary[0];\n",
        "\n",
        "    for i in range(1, len(binary)):\n",
        "        gray += xor_c(binary[i - 1],\n",
        "                      binary[i]);\n",
        " \n",
        "    return gray;\n",
        "\n",
        "# Helper Function to convert from gray code to binary\n",
        "def flip_num(my_nu):\n",
        "   return '1' if(my_nu == '0') else '0';\n",
        "\n",
        "# Function to convert from gray code to binary\n",
        "def gray_to_binary(gray):\n",
        "   binary_code = \"\"\n",
        "   binary_code += gray[0]\n",
        "   for i in range(1, len(gray)):\n",
        "\n",
        "      if (gray[i] == '0'):\n",
        "         binary_code += binary_code[i - 1]\n",
        "      else:\n",
        "         binary_code += flip_num(binary_code[i - 1])\n",
        "\n",
        "   return binary_code\n",
        "\n",
        "def binaryToDecimal(x):\n",
        "    return int(x, 2)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "id": "qDTiGBi2cPSh"
      },
      "outputs": [],
      "source": [
        "isGrayCode = False\n",
        "num_parents_mating = 4\n",
        "num_weights = 8"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "id": "JOKVbbn9ZWu7"
      },
      "outputs": [],
      "source": [
        "# Function to generate Population for fitness function 1\n",
        "def generatePopulationForFunc1():\n",
        "  population_matrix = np.array([])\n",
        "  for _ in range(8):\n",
        "    x = random.randint(0,255)\n",
        "    if(isGrayCode):\n",
        "      bin = binarytoGray(bin8(x))\n",
        "    else:\n",
        "      bin = bin8(x)\n",
        "    population_matrix = np.append(population_matrix, bin)\n",
        "  return population_matrix"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
      "metadata": {},
      "outputs": [],
      "source": [
        "# Function to generate Population for fitness function 2\n",
        "def generatePopulationForFunc2():\n",
        "  population_matrix = np.array([])\n",
        "  for _ in range(8):\n",
        "    x = random.randint(-5,5)\n",
        "    y = random.randint(-5,5)\n",
        "    individual = np.array([x,y])\n",
        "    if(population_matrix.shape[0] == 0):\n",
        "      population_matrix = individual\n",
        "    else:\n",
        "      population_matrix = np.vstack((population_matrix, individual))\n",
        "  return population_matrix"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {},
      "outputs": [],
      "source": [
        "# Function to calculate fitness of population for fitness function 1\n",
        "def calculatePopFitnessFunction1(pop):\n",
        "    population_fitness = np.array([])\n",
        "    for i in range(len(pop)):\n",
        "        func1Output = fitness_fun1(binaryToDecimal(pop[i]))\n",
        "        population_fitness = np.append(population_fitness,func1Output)\n",
        "    return population_fitness\n",
        "\n",
        "# Function to calculate fitness of population for fitness function 2\n",
        "def calculatePopFitnessFunction2(pop):\n",
        "    population_fitness = np.array([])\n",
        "    for i in range(len(pop)):\n",
        "        func2Output = fitness_fun2(pop[i][0], pop[i][1])\n",
        "        population_fitness = np.append(population_fitness,func2Output)\n",
        "    return population_fitness"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 9,
      "metadata": {
        "id": "UV_nB5V--vRN"
      },
      "outputs": [],
      "source": [
        "# Function to select parents with highest fitness of population function 1\n",
        "def select_mating_pool(pop, fitness, num_parents):\n",
        "  parents = np.array([])\n",
        "  for _ in range(num_parents):\n",
        "    max_fitness_idx = np.where(fitness == np.max(fitness))[0][0]\n",
        "    parents = np.append(parents,pop[max_fitness_idx])\n",
        "    fitness[max_fitness_idx] = -99999999999\n",
        "  return parents\n",
        "\n",
        "# Function to select parents with highest fitness of population function 2\n",
        "def select_mating_pool_func2(pop, fitness, num_parents):\n",
        "  parents = np.array([])\n",
        "  for _ in range(num_parents):\n",
        "    max_fitness_idx = np.where(fitness == np.max(fitness))[0][0]\n",
        "    if(parents.shape[0] == 0):\n",
        "      parents = pop[max_fitness_idx]\n",
        "    else:\n",
        "      parents = np.vstack((parents, pop[max_fitness_idx]))\n",
        "    fitness[max_fitness_idx] = -99999999999\n",
        "  return parents"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 10,
      "metadata": {
        "id": "lwmE0dAmGryL"
      },
      "outputs": [],
      "source": [
        "# Function to compute fifty percent crossover for function 1\n",
        "def fiftyPercentCrossoverFunctionOne(parents, offspring_size):\n",
        "    offsprings = np.empty(offspring_size, dtype=object)\n",
        "    crossover_point = int(len(parents[0]) / 2)\n",
        "    for k in range(0, offspring_size, 2):\n",
        "        parent1 = parents[k]\n",
        "        parent2 = parents[k + 1]\n",
        "        offsprings[k] = f'{parent1[0:crossover_point]}{parent2[crossover_point:]}'\n",
        "        offsprings[k + 1] = f'{parent2[0:crossover_point]}{parent1[crossover_point:]}'\n",
        "    return offsprings\n",
        "\n",
        "# Function to compute fifty percent crossover for function 2\n",
        "def fiftyPercentCrossoverFunctionTwo(parents, offspring_size):\n",
        "    offsprings = np.array([])\n",
        "    print(parents)\n",
        "    for k in range(0, offspring_size, 2):\n",
        "        parent1 = parents[k]\n",
        "        parent2 = parents[k + 1]\n",
        "        offspring1 = np.array([parent1[0],parent2[1]])\n",
        "        offspring2 = np.array([parent2[0],parent1[1]])\n",
        "        if(offsprings.shape[0] == 0):\n",
        "            offsprings = offspring1\n",
        "            offsprings = np.vstack((offsprings, offspring2))\n",
        "        else:\n",
        "            offsprings = np.vstack((offsprings, offspring1))\n",
        "            offsprings = np.vstack((offsprings, offspring2))\n",
        "    return offsprings"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 11,
      "metadata": {},
      "outputs": [],
      "source": [
        "# Function to compute one point crossover for function 1\n",
        "def onePointCrossover(parents, offspring_size):\n",
        "    offspring = np.empty(offspring_size, dtype=object)\n",
        "    crossover_point = np.random.randint(0,len(parents[0]))\n",
        "    print(f'Crossover Point: {crossover_point}')\n",
        "    for k in range(0, offspring_size, 2):\n",
        "        parent1 = parents[k]\n",
        "        parent2 = parents[k + 1]\n",
        "        offspring[k] = f'{parent1[0:crossover_point]}{parent2[crossover_point:]}'\n",
        "        offspring[k + 1] = f'{parent2[0:crossover_point]}{parent1[crossover_point:]}'\n",
        "    return offspring"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {},
      "outputs": [],
      "source": [
        "# Function to compute two point crossover for function 1\n",
        "def twoPointCrossover(parents, offspring_size):\n",
        "    offspring = np.empty(offspring_size, dtype=object)\n",
        "    crossover_point1, crossover_point2 = random.sample(range(0, len(parents[0])), 2)\n",
        "    print(f'Crossover Point 1: {crossover_point1}')\n",
        "    print(f'Crossover Point 2: {crossover_point2}')\n",
        "    for k in range(0, offspring_size, 2):\n",
        "        parent1 = parents[k]\n",
        "        parent2 = parents[k + 1]\n",
        "        if(crossover_point1 < crossover_point2):\n",
        "            offspring[k] = f'{parent1[0:crossover_point1]}{parent2[crossover_point1:crossover_point2]}{parent1[crossover_point2:]}'\n",
        "            offspring[k + 1] = f'{parent2[0:crossover_point1]}{parent1[crossover_point1:crossover_point2]}{parent2[crossover_point2:]}'\n",
        "        else:\n",
        "            offspring[k] = f'{parent1[0:crossover_point2]}{parent2[crossover_point2:crossover_point1]}{parent1[crossover_point1:]}'\n",
        "            offspring[k + 1] = f'{parent2[0:crossover_point2]}{parent1[crossover_point2:crossover_point1]}{parent2[crossover_point1:]}'\n",
        "    return offspring"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {},
      "outputs": [],
      "source": [
        "# For first function if value is greater than 255 or less than 0 bring back into range\n",
        "def repairFunctionOne(x, range):\n",
        "    value = 0\n",
        "    if(isGrayCode):\n",
        "        binaryOfGrayCode = gray_to_binary(x)\n",
        "        value = binaryToDecimal(binaryOfGrayCode)\n",
        "    else:\n",
        "        value = binaryToDecimal(x)\n",
        "\n",
        "    if(value > range[1]):\n",
        "        value = range[1]\n",
        "\n",
        "    elif(value < range[0]):\n",
        "        value = range[0]\n",
        "\n",
        "    if(isGrayCode):\n",
        "        value = binarytoGray(bin8(value))\n",
        "    else:\n",
        "        value = bin8(value)\n",
        "    return value\n",
        "\n",
        "# For second function if value is greater than 5 or less than -5 bring back into range\n",
        "def repairFunctionTwo(x, rangeValues):\n",
        "    print(x)\n",
        "    for i in range(len(x)):\n",
        "        if x[i] < rangeValues[0]:\n",
        "            x[i] = rangeValues[0]\n",
        "\n",
        "        elif x[i] > rangeValues[1]:\n",
        "            x[i] = rangeValues[1]\n",
        "    return x"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 14,
      "metadata": {},
      "outputs": [],
      "source": [
        "# Function to compute mutation for function 1\n",
        "def mutationFunctionOne(offspring, probability):\n",
        "    for i in range(len(offspring)):\n",
        "        flipOrNot = True if random.random() < probability else False\n",
        "        if(flipOrNot):\n",
        "            offspring = offspring[0:i] + \"0\" + offspring[i+1:] if offspring[i] == \"1\" else offspring[0:i] + \"1\" + offspring[i+1:]\n",
        "    return offspring\n",
        "\n",
        "# Function to compute mutation for function 2\n",
        "def mutationFunctionTwo(offspring, probability):\n",
        "    for i in range(len(offspring)):\n",
        "        flipOrNot = True if random.random() < probability else False\n",
        "        if(flipOrNot):\n",
        "            offspring[i] = random.randint(-5,5)\n",
        "    return offspring"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 15,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Generation :  0\n",
            "Population Matrix\n",
            "['00000110' '01011110' '10001101' '11011111' '11110101' '00111010'\n",
            " '01111001' '10001001']\n",
            "Fitness\n",
            "[0.07356456 0.91420976 0.98730142 0.39399204 0.13458071 0.65317284\n",
            " 0.99631261 0.99390697]\n",
            "Best Fitness: 0.996312612182778\n",
            "Parents\n",
            "['01111001' '10001001' '10001101' '01011110']\n",
            "Crossover\n",
            "['01111001' '10001001' '10001110' '01011101']\n",
            "Mutation\n",
            "['01111001' '00001001' '10001110' '01001101']\n",
            "Generation :  1\n",
            "Population Matrix\n",
            "['01111001' '10001001' '10001101' '01011110' '01111001' '00001001'\n",
            " '10001110' '01001101']\n",
            "Fitness\n",
            "[0.99631261 0.99390697 0.98730142 0.91420976 0.99631261 0.11022221\n",
            " 0.98527764 0.8104572 ]\n",
            "Best Fitness: 0.996312612182778\n",
            "Parents\n",
            "['01111001' '01111001' '10001001' '10001101']\n",
            "Crossover\n",
            "['01111001' '01111001' '10001101' '10001001']\n",
            "Mutation\n",
            "['01111001' '01111001' '10001101' '10001001']\n",
            "Generation :  2\n",
            "Population Matrix\n",
            "['01111001' '01111001' '10001001' '10001101' '01111001' '01111001'\n",
            " '10001101' '10001001']\n",
            "Fitness\n",
            "[0.99631261 0.99631261 0.99390697 0.98730142 0.99631261 0.99631261\n",
            " 0.98730142 0.99390697]\n",
            "Best Fitness: 0.996312612182778\n",
            "Parents\n",
            "['01111001' '01111001' '01111001' '01111001']\n",
            "Crossover\n",
            "['01111001' '01111001' '01111001' '01111001']\n",
            "Mutation\n",
            "['11111001' '01111001' '01111001' '01111001']\n",
            "Generation :  3\n",
            "Population Matrix\n",
            "['01111001' '01111001' '01111001' '01111001' '11111001' '01111001'\n",
            " '01111001' '01111001']\n",
            "Fitness\n",
            "[0.99631261 0.99631261 0.99631261 0.99631261 0.08579731 0.99631261\n",
            " 0.99631261 0.99631261]\n",
            "Best Fitness: 0.996312612182778\n",
            "Parents\n",
            "['01111001' '01111001' '01111001' '01111001']\n",
            "Crossover Point: 4\n",
            "Crossover\n",
            "['01111001' '01111001' '01111001' '01111001']\n",
            "Mutation\n",
            "['11111001' '01111001' '01111001' '01111101']\n",
            "Generation :  4\n",
            "Population Matrix\n",
            "['01111001' '01111001' '01111001' '01111001' '11111001' '01111001'\n",
            " '01111001' '01111101']\n",
            "Fitness\n",
            "[0.99631261 0.99631261 0.99631261 0.99631261 0.08579731 0.99631261\n",
            " 0.99631261 0.99932238]\n",
            "Best Fitness: 0.9993223845883495\n",
            "Parents\n",
            "['01111101' '01111001' '01111001' '01111001']\n",
            "Crossover\n",
            "['01111001' '01111101' '01111001' '01111001']\n",
            "Mutation\n",
            "['01111001' '01111101' '01111001' '01111001']\n",
            "Generation :  5\n",
            "Population Matrix\n",
            "['01111101' '01111001' '01111001' '01111001' '01111001' '01111101'\n",
            " '01111001' '01111001']\n",
            "Fitness\n",
            "[0.99932238 0.99631261 0.99631261 0.99631261 0.99631261 0.99932238\n",
            " 0.99631261 0.99631261]\n",
            "Best Fitness: 0.9993223845883495\n",
            "Parents\n",
            "['01111101' '01111101' '01111001' '01111001']\n",
            "Crossover\n",
            "['01111101' '01111101' '01111001' '01111001']\n",
            "Mutation\n",
            "['01111101' '01101101' '01111001' '00111001']\n",
            "Generation :  6\n",
            "Population Matrix\n",
            "['01111101' '01111101' '01111001' '01111001' '01111101' '01101101'\n",
            " '01111001' '00111001']\n",
            "Fitness\n",
            "[0.99932238 0.99932238 0.99631261 0.99631261 0.99932238 0.97293995\n",
            " 0.99631261 0.64383154]\n",
            "Best Fitness: 0.9993223845883495\n",
            "Parents\n",
            "['01111101' '01111101' '01111101' '01111001']\n",
            "Crossover\n",
            "['01111101' '01111101' '01111001' '01111101']\n",
            "Mutation\n",
            "['01111100' '11111101' '01011001' '01111111']\n",
            "Generation :  7\n",
            "Population Matrix\n",
            "['01111101' '01111101' '01111101' '01111001' '01111100' '11111101'\n",
            " '01011001' '01111111']\n",
            "Fitness\n",
            "[0.99932238 0.99932238 0.99932238 0.99631261 0.99879546 0.03680722\n",
            " 0.88763962 0.9999247 ]\n",
            "Best Fitness: 0.9999247018391445\n",
            "Parents\n",
            "['01111111' '01111101' '01111101' '01111101']\n",
            "Crossover Point: 5\n",
            "Crossover\n",
            "['01111101' '01111111' '01111101' '01111101']\n",
            "Mutation\n",
            "['01111111' '01111111' '01111101' '01011101']\n",
            "Generation :  8\n",
            "Population Matrix\n",
            "['01111111' '01111101' '01111101' '01111101' '01111111' '01111111'\n",
            " '01111101' '01011101']\n",
            "Fitness\n",
            "[0.9999247  0.99932238 0.99932238 0.99932238 0.9999247  0.9999247\n",
            " 0.99932238 0.90916798]\n",
            "Best Fitness: 0.9999247018391445\n",
            "Parents\n",
            "['01111111' '01111111' '01111111' '01111101']\n",
            "Crossover Point: 5\n",
            "Crossover\n",
            "['01111111' '01111111' '01111101' '01111111']\n",
            "Mutation\n",
            "['01111101' '00111111' '00111101' '01111111']\n",
            "Generation :  9\n",
            "Population Matrix\n",
            "['01111111' '01111111' '01111111' '01111101' '01111101' '00111111'\n",
            " '00111101' '01111111']\n",
            "Fitness\n",
            "[0.9999247  0.9999247  0.9999247  0.99932238 0.99932238 0.69837625\n",
            " 0.680601   0.9999247 ]\n",
            "Best Fitness: 0.9999247018391445\n",
            "Parents\n",
            "['01111111' '01111111' '01111111' '01111111']\n",
            "Crossover Point: 4\n",
            "Crossover\n",
            "['01111111' '01111111' '01111111' '01111111']\n",
            "Mutation\n",
            "['01110111' '11101111' '01111111' '01111111']\n",
            "Generation :  10\n",
            "Population Matrix\n",
            "['01111111' '01111111' '01111111' '01111111' '01110111' '11101111'\n",
            " '01111111' '01111111']\n",
            "Fitness\n",
            "[0.9999247  0.9999247  0.9999247  0.9999247  0.99390697 0.20711138\n",
            " 0.9999247  0.9999247 ]\n",
            "Best Fitness: 0.9999247018391445\n",
            "Parents\n",
            "['01111111' '01111111' '01111111' '01111111']\n",
            "Crossover Point: 4\n",
            "Crossover\n",
            "['01111111' '01111111' '01111111' '01111111']\n",
            "Mutation\n",
            "['01111101' '01110111' '01101111' '01111111']\n",
            "Generation :  11\n",
            "Population Matrix\n",
            "['01111111' '01111111' '01111111' '01111111' '01111101' '01110111'\n",
            " '01101111' '01111111']\n",
            "Fitness\n",
            "[0.9999247  0.9999247  0.9999247  0.9999247  0.99932238 0.99390697\n",
            " 0.97831737 0.9999247 ]\n",
            "Best Fitness: 0.9999247018391445\n",
            "Parents\n",
            "['01111111' '01111111' '01111111' '01111111']\n",
            "Crossover\n",
            "['01111111' '01111111' '01111111' '01111111']\n",
            "Mutation\n",
            "['01111111' '01111101' '10111111' '01111111']\n",
            "Generation :  12\n",
            "Population Matrix\n",
            "['01111111' '01111111' '01111111' '01111111' '01111111' '01111101'\n",
            " '10111111' '01111111']\n",
            "Fitness\n",
            "[0.9999247  0.9999247  0.9999247  0.9999247  0.9999247  0.99932238\n",
            " 0.71573083 0.9999247 ]\n",
            "Best Fitness: 0.9999247018391445\n",
            "Parents\n",
            "['01111111' '01111111' '01111111' '01111111']\n",
            "Crossover Point: 6\n",
            "Crossover\n",
            "['01111111' '01111111' '01111111' '01111111']\n",
            "Mutation\n",
            "['01111111' '01111111' '01111111' '01111111']\n",
            "Generation :  13\n",
            "Population Matrix\n",
            "['01111111' '01111111' '01111111' '01111111' '01111111' '01111111'\n",
            " '01111111' '01111111']\n",
            "Fitness\n",
            "[0.9999247 0.9999247 0.9999247 0.9999247 0.9999247 0.9999247 0.9999247\n",
            " 0.9999247]\n",
            "Best Fitness: 0.9999247018391445\n",
            "Parents\n",
            "['01111111' '01111111' '01111111' '01111111']\n",
            "Crossover\n",
            "['01111111' '01111111' '01111111' '01111111']\n",
            "Mutation\n",
            "['11111111' '01111111' '01111111' '01111111']\n",
            "Generation :  14\n",
            "Population Matrix\n",
            "['01111111' '01111111' '01111111' '01111111' '11111111' '01111111'\n",
            " '01111111' '01111111']\n",
            "Fitness\n",
            "[0.9999247  0.9999247  0.9999247  0.9999247  0.01227154 0.9999247\n",
            " 0.9999247  0.9999247 ]\n",
            "Best Fitness: 0.9999247018391445\n",
            "Parents\n",
            "['01111111' '01111111' '01111111' '01111111']\n",
            "Crossover Point: 3\n",
            "Crossover\n",
            "['01111111' '01111111' '01111111' '01111111']\n",
            "Mutation\n",
            "['01111111' '01111111' '01111111' '01111111']\n",
            "Generation :  15\n",
            "Population Matrix\n",
            "['01111111' '01111111' '01111111' '01111111' '01111111' '01111111'\n",
            " '01111111' '01111111']\n",
            "Fitness\n",
            "[0.9999247 0.9999247 0.9999247 0.9999247 0.9999247 0.9999247 0.9999247\n",
            " 0.9999247]\n",
            "Best Fitness: 0.9999247018391445\n",
            "Parents\n",
            "['01111111' '01111111' '01111111' '01111111']\n",
            "Crossover Point: 7\n",
            "Crossover\n",
            "['01111111' '01111111' '01111111' '01111111']\n",
            "Mutation\n",
            "['01111111' '01111111' '01111111' '01111111']\n",
            "Generation :  16\n",
            "Population Matrix\n",
            "['01111111' '01111111' '01111111' '01111111' '01111111' '01111111'\n",
            " '01111111' '01111111']\n",
            "Fitness\n",
            "[0.9999247 0.9999247 0.9999247 0.9999247 0.9999247 0.9999247 0.9999247\n",
            " 0.9999247]\n",
            "Best Fitness: 0.9999247018391445\n",
            "Parents\n",
            "['01111111' '01111111' '01111111' '01111111']\n",
            "Crossover Point: 7\n",
            "Crossover\n",
            "['01111111' '01111111' '01111111' '01111111']\n",
            "Mutation\n",
            "['01111111' '00111111' '01110111' '01111111']\n",
            "Generation :  17\n",
            "Population Matrix\n",
            "['01111111' '01111111' '01111111' '01111111' '01111111' '00111111'\n",
            " '01110111' '01111111']\n",
            "Fitness\n",
            "[0.9999247  0.9999247  0.9999247  0.9999247  0.9999247  0.69837625\n",
            " 0.99390697 0.9999247 ]\n",
            "Best Fitness: 0.9999247018391445\n",
            "Parents\n",
            "['01111111' '01111111' '01111111' '01111111']\n",
            "Crossover Point: 0\n",
            "Crossover\n",
            "['01111111' '01111111' '01111111' '01111111']\n",
            "Mutation\n",
            "['01111001' '01111111' '01111111' '01111101']\n",
            "Generation :  18\n",
            "Population Matrix\n",
            "['01111111' '01111111' '01111111' '01111111' '01111001' '01111111'\n",
            " '01111111' '01111101']\n",
            "Fitness\n",
            "[0.9999247  0.9999247  0.9999247  0.9999247  0.99631261 0.9999247\n",
            " 0.9999247  0.99932238]\n",
            "Best Fitness: 0.9999247018391445\n",
            "Parents\n",
            "['01111111' '01111111' '01111111' '01111111']\n",
            "Crossover Point: 0\n",
            "Crossover\n",
            "['01111111' '01111111' '01111111' '01111111']\n",
            "Mutation\n",
            "['01111111' '01111011' '01111111' '01111111']\n",
            "Generation :  19\n",
            "Population Matrix\n",
            "['01111111' '01111111' '01111111' '01111111' '01111111' '01111011'\n",
            " '01111111' '01111111']\n",
            "Fitness\n",
            "[0.9999247  0.9999247  0.9999247  0.9999247  0.9999247  0.99811811\n",
            " 0.9999247  0.9999247 ]\n",
            "Best Fitness: 0.9999247018391445\n",
            "Parents\n",
            "['01111111' '01111111' '01111111' '01111111']\n",
            "Crossover Point: 3\n",
            "Crossover\n",
            "['01111111' '01111111' '01111111' '01111111']\n",
            "Mutation\n",
            "['01111111' '01111111' '01111111' '01101101']\n",
            "Best solution :  01111111\n",
            "Best solution fitness :  0.9999247018391445\n"
          ]
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Visualize the generations of the GA for the 1st objective function.\n",
        "new_population = generatePopulationForFunc1()\n",
        "new_population_fitness = np.array([])\n",
        "best_outputs = []\n",
        "best_average_outputs = []\n",
        "num_generations = 20\n",
        "num_parents_mating = 4\n",
        "offspring_size = 4\n",
        "\n",
        "for generation in range(num_generations):\n",
        "    print(\"Generation : \", generation)\n",
        "\n",
        "    print(\"Population Matrix\")\n",
        "    print(new_population)\n",
        "\n",
        "    # Measuring the fitness of each chromosome in the population.\n",
        "    population_fitness = calculatePopFitnessFunction1(new_population)\n",
        "    print(\"Fitness\")\n",
        "    print(population_fitness)\n",
        "    print(\"Best Fitness:\", np.max(population_fitness))\n",
        "    best_outputs.append(np.max(population_fitness))\n",
        "    best_average_outputs.append(np.average(population_fitness))\n",
        "\n",
        "    # Selecting the best parents in the population for mating.\n",
        "    parents = select_mating_pool(new_population, population_fitness, num_parents_mating)\n",
        "    print(\"Parents\")\n",
        "    print(parents)\n",
        "\n",
        "    # Generating next generation using crossover.\n",
        "    offspring_crossover = fiftyPercentCrossoverFunctionOne(parents, offspring_size) if random.random() < 0.5 else onePointCrossover(parents, offspring_size)\n",
        "    print(\"Crossover\")\n",
        "    print(offspring_crossover)\n",
        "\n",
        "    # Adding some variations to the offspring using mutation.\n",
        "    offspring_mutation = np.array([])\n",
        "    for i in range(len(offspring_crossover)):\n",
        "        offspring_mutation = np.append(offspring_mutation, mutationFunctionOne(offspring_crossover[i], 0.05))\n",
        "    print(\"Mutation\")\n",
        "    print(offspring_mutation)\n",
        "\n",
        "    new_population = np.append(parents, offspring_mutation)\n",
        "\n",
        "    for i in range(len(new_population)):\n",
        "        new_population[i] = repairFunctionOne(new_population[i], [0 ,255])\n",
        "    \n",
        "# Getting the best solution after iterating finishing all generations.\n",
        "# At first, the fitness is calculated for each solution in the final generation.\n",
        "new_population_fitness = calculatePopFitnessFunction1(new_population)\n",
        "\n",
        "# Then return the index of that solution corresponding to the best fitness.\n",
        "best_match_idx = np.where(new_population_fitness == np.max(new_population_fitness))[0][0]\n",
        "\n",
        "print(\"Best solution : \", new_population[best_match_idx])\n",
        "print(\"Best solution fitness : \", new_population_fitness[best_match_idx])\n",
        "\n",
        "matplotlib.pyplot.plot(best_outputs)\n",
        "matplotlib.pyplot.plot(best_average_outputs)\n",
        "matplotlib.pyplot.xlabel(\"Iteration\")\n",
        "matplotlib.pyplot.ylabel(\"Fitness\")\n",
        "matplotlib.pyplot.show()"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 16,
      "metadata": {},
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Generation :  0\n",
            "Population Matrix\n",
            "[[ 3  5]\n",
            " [ 0  0]\n",
            " [ 2  5]\n",
            " [-1  4]\n",
            " [-5 -2]\n",
            " [-4  2]\n",
            " [ 4 -5]\n",
            " [-5  4]]\n",
            "Fitness\n",
            "[ -3.83695275 -17.25774626  -6.85339613 -18.76937504 -87.98450306\n",
            " -52.40369104 -60.82687034 -68.03518875]\n",
            "Best Fitness: 3.836952745094602\n",
            "Parents\n",
            "[[ 3  5]\n",
            " [ 2  5]\n",
            " [ 0  0]\n",
            " [-1  4]]\n",
            "[[ 3  5]\n",
            " [ 2  5]\n",
            " [ 0  0]\n",
            " [-1  4]]\n",
            "Crossover\n",
            "[[ 3  5]\n",
            " [ 2  5]\n",
            " [ 0  4]\n",
            " [-1  0]]\n",
            "Mutation\n",
            "[[ 4  5]\n",
            " [ 2  5]\n",
            " [ 0  4]\n",
            " [-1  0]]\n",
            "[3 5]\n",
            "[2 5]\n",
            "[0 0]\n",
            "[-1  4]\n",
            "[4 5]\n",
            "[2 5]\n",
            "[0 4]\n",
            "[-1  0]\n",
            "Generation :  1\n",
            "Population Matrix\n",
            "[[ 3  5]\n",
            " [ 2  5]\n",
            " [ 0  0]\n",
            " [-1  4]\n",
            " [ 4  5]\n",
            " [ 2  5]\n",
            " [ 0  4]\n",
            " [-1  0]]\n",
            "Fitness\n",
            "[ -3.83695275  -6.85339613 -17.25774626 -18.76937504  -6.13740826\n",
            "  -6.85339613 -13.47629075 -22.55083055]\n",
            "Best Fitness: 3.836952745094602\n",
            "Parents\n",
            "[[3 5]\n",
            " [4 5]\n",
            " [2 5]\n",
            " [2 5]]\n",
            "[[3 5]\n",
            " [4 5]\n",
            " [2 5]\n",
            " [2 5]]\n",
            "Crossover\n",
            "[[3 5]\n",
            " [4 5]\n",
            " [2 5]\n",
            " [2 5]]\n",
            "Mutation\n",
            "[[3 5]\n",
            " [4 5]\n",
            " [2 5]\n",
            " [2 5]]\n",
            "[3 5]\n",
            "[4 5]\n",
            "[2 5]\n",
            "[2 5]\n",
            "[3 5]\n",
            "[4 5]\n",
            "[2 5]\n",
            "[2 5]\n",
            "Generation :  2\n",
            "Population Matrix\n",
            "[[3 5]\n",
            " [4 5]\n",
            " [2 5]\n",
            " [2 5]\n",
            " [3 5]\n",
            " [4 5]\n",
            " [2 5]\n",
            " [2 5]]\n",
            "Fitness\n",
            "[-3.83695275 -6.13740826 -6.85339613 -6.85339613 -3.83695275 -6.13740826\n",
            " -6.85339613 -6.85339613]\n",
            "Best Fitness: 3.836952745094602\n",
            "Parents\n",
            "[[3 5]\n",
            " [3 5]\n",
            " [4 5]\n",
            " [4 5]]\n",
            "[[3 5]\n",
            " [3 5]\n",
            " [4 5]\n",
            " [4 5]]\n",
            "Crossover\n",
            "[[3 5]\n",
            " [3 5]\n",
            " [4 5]\n",
            " [4 5]]\n",
            "Mutation\n",
            "[[3 5]\n",
            " [3 5]\n",
            " [4 0]\n",
            " [4 5]]\n",
            "[3 5]\n",
            "[3 5]\n",
            "[4 5]\n",
            "[4 5]\n",
            "[3 5]\n",
            "[3 5]\n",
            "[4 0]\n",
            "[4 5]\n",
            "Generation :  3\n",
            "Population Matrix\n",
            "[[3 5]\n",
            " [3 5]\n",
            " [4 5]\n",
            " [4 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [4 0]\n",
            " [4 5]]\n",
            "Fitness\n",
            "[-3.83695275 -3.83695275 -6.13740826 -6.13740826 -3.83695275 -3.83695275\n",
            " -7.89770685 -6.13740826]\n",
            "Best Fitness: 3.836952745094602\n",
            "Parents\n",
            "[[3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 5]]\n",
            "[[3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 5]]\n",
            "Crossover\n",
            "[[3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 5]]\n",
            "Mutation\n",
            "[[0 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 5]]\n",
            "[3 5]\n",
            "[3 5]\n",
            "[3 5]\n",
            "[3 5]\n",
            "[0 5]\n",
            "[3 5]\n",
            "[3 5]\n",
            "[3 5]\n",
            "Generation :  4\n",
            "Population Matrix\n",
            "[[3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [0 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 5]]\n",
            "Fitness\n",
            "[ -3.83695275  -3.83695275  -3.83695275  -3.83695275 -15.49744767\n",
            "  -3.83695275  -3.83695275  -3.83695275]\n",
            "Best Fitness: 3.836952745094602\n",
            "Parents\n",
            "[[3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 5]]\n",
            "[[3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 5]]\n",
            "Crossover\n",
            "[[3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 5]]\n",
            "Mutation\n",
            "[[3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [2 5]]\n",
            "[3 5]\n",
            "[3 5]\n",
            "[3 5]\n",
            "[3 5]\n",
            "[3 5]\n",
            "[3 5]\n",
            "[3 5]\n",
            "[2 5]\n",
            "Generation :  5\n",
            "Population Matrix\n",
            "[[3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [2 5]]\n",
            "Fitness\n",
            "[-3.83695275 -3.83695275 -3.83695275 -3.83695275 -3.83695275 -3.83695275\n",
            " -3.83695275 -6.85339613]\n",
            "Best Fitness: 3.836952745094602\n",
            "Parents\n",
            "[[3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 5]]\n",
            "[[3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 5]]\n",
            "Crossover\n",
            "[[3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 5]]\n",
            "Mutation\n",
            "[[3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 5]]\n",
            "[3 5]\n",
            "[3 5]\n",
            "[3 5]\n",
            "[3 5]\n",
            "[3 5]\n",
            "[3 5]\n",
            "[3 5]\n",
            "[3 5]\n",
            "Generation :  6\n",
            "Population Matrix\n",
            "[[3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 5]]\n",
            "Fitness\n",
            "[-3.83695275 -3.83695275 -3.83695275 -3.83695275 -3.83695275 -3.83695275\n",
            " -3.83695275 -3.83695275]\n",
            "Best Fitness: 3.836952745094602\n",
            "Parents\n",
            "[[3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 5]]\n",
            "[[3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 5]]\n",
            "Crossover\n",
            "[[3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 5]]\n",
            "Mutation\n",
            "[[3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 3]]\n",
            "[3 5]\n",
            "[3 5]\n",
            "[3 5]\n",
            "[3 5]\n",
            "[3 5]\n",
            "[3 5]\n",
            "[3 5]\n",
            "[3 3]\n",
            "Generation :  7\n",
            "Population Matrix\n",
            "[[3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[-3.83695275 -3.83695275 -3.83695275 -3.83695275 -3.83695275 -3.83695275\n",
            " -3.83695275  1.4835133 ]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 5]]\n",
            "[[3 3]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 5]]\n",
            "Crossover\n",
            "[[3 5]\n",
            " [3 3]\n",
            " [3 5]\n",
            " [3 5]]\n",
            "Mutation\n",
            "[[3 5]\n",
            " [3 3]\n",
            " [3 5]\n",
            " [3 5]]\n",
            "[3 3]\n",
            "[3 5]\n",
            "[3 5]\n",
            "[3 5]\n",
            "[3 5]\n",
            "[3 3]\n",
            "[3 5]\n",
            "[3 5]\n",
            "Generation :  8\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 3]\n",
            " [3 5]\n",
            " [3 5]]\n",
            "Fitness\n",
            "[ 1.4835133  -3.83695275 -3.83695275 -3.83695275 -3.83695275  1.4835133\n",
            " -3.83695275 -3.83695275]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 5]\n",
            " [3 5]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 5]\n",
            " [3 5]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 5]\n",
            " [3 5]]\n",
            "Mutation\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 5]\n",
            " [3 5]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 5]\n",
            "[3 5]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 5]\n",
            "[3 5]\n",
            "Generation :  9\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 5]\n",
            " [3 5]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 5]\n",
            " [3 5]]\n",
            "Fitness\n",
            "[ 1.4835133   1.4835133  -3.83695275 -3.83695275  1.4835133   1.4835133\n",
            " -3.83695275 -3.83695275]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  10\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133\n",
            " 1.4835133]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  11\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133\n",
            " 1.4835133]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  12\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133\n",
            " 1.4835133]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  13\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133\n",
            " 1.4835133]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  14\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133\n",
            " 1.4835133]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  15\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133\n",
            " 1.4835133]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  16\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133\n",
            " 1.4835133]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  17\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133\n",
            " 1.4835133]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[3 3]\n",
            " [4 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[4 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  18\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [4 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[ 1.4835133   1.4835133   1.4835133   1.4835133   1.4835133  -0.81694222\n",
            "  1.4835133   1.4835133 ]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  19\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133\n",
            " 1.4835133]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  20\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133\n",
            " 1.4835133]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  21\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133\n",
            " 1.4835133]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  22\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133\n",
            " 1.4835133]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[ 3  3]\n",
            " [ 2  3]\n",
            " [-3  3]\n",
            " [ 3  3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[2 3]\n",
            "[-3  3]\n",
            "[3 3]\n",
            "Generation :  23\n",
            "Population Matrix\n",
            "[[ 3  3]\n",
            " [ 3  3]\n",
            " [ 3  3]\n",
            " [ 3  3]\n",
            " [ 3  3]\n",
            " [ 2  3]\n",
            " [-3  3]\n",
            " [ 3  3]]\n",
            "Fitness\n",
            "[  1.4835133    1.4835133    1.4835133    1.4835133    1.4835133\n",
            "  -1.53293009 -36.06452281   1.4835133 ]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[5 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[5 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  24\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [5 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[ 1.4835133  1.4835133  1.4835133  1.4835133 -2.1441074  1.4835133\n",
            "  1.4835133  1.4835133]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  25\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133\n",
            " 1.4835133]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[3 1]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 1]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  26\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 1]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[ 1.4835133   1.4835133   1.4835133   1.4835133  -2.90996013  1.4835133\n",
            "  1.4835133   1.4835133 ]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  27\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133\n",
            " 1.4835133]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[ 3 -2]\n",
            " [ 3  3]\n",
            " [ 3  3]\n",
            " [ 3  3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[ 3 -2]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  28\n",
            "Population Matrix\n",
            "[[ 3  3]\n",
            " [ 3  3]\n",
            " [ 3  3]\n",
            " [ 3  3]\n",
            " [ 3 -2]\n",
            " [ 3  3]\n",
            " [ 3  3]\n",
            " [ 3  3]]\n",
            "Fitness\n",
            "[  1.4835133    1.4835133    1.4835133    1.4835133  -21.76511013\n",
            "   1.4835133    1.4835133    1.4835133 ]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[ 3  3]\n",
            " [ 3  3]\n",
            " [ 3  3]\n",
            " [-4 -1]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[-4 -1]\n",
            "Generation :  29\n",
            "Population Matrix\n",
            "[[ 3  3]\n",
            " [ 3  3]\n",
            " [ 3  3]\n",
            " [ 3  3]\n",
            " [ 3  3]\n",
            " [ 3  3]\n",
            " [ 3  3]\n",
            " [-4 -1]]\n",
            "Fitness\n",
            "[  1.4835133    1.4835133    1.4835133    1.4835133    1.4835133\n",
            "   1.4835133    1.4835133  -66.26227609]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [2 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[2 3]\n",
            "[3 3]\n",
            "Generation :  30\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [2 3]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[ 1.4835133   1.4835133   1.4835133   1.4835133   1.4835133   1.4835133\n",
            " -1.53293009  1.4835133 ]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  31\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133\n",
            " 1.4835133]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  32\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133\n",
            " 1.4835133]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  33\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133\n",
            " 1.4835133]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  34\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133\n",
            " 1.4835133]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[-2 -3]\n",
            " [ 3  3]\n",
            " [ 3  4]\n",
            " [ 3  3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[-2 -3]\n",
            "[3 3]\n",
            "[3 4]\n",
            "[3 3]\n",
            "Generation :  35\n",
            "Population Matrix\n",
            "[[ 3  3]\n",
            " [ 3  3]\n",
            " [ 3  3]\n",
            " [ 3  3]\n",
            " [-2 -3]\n",
            " [ 3  3]\n",
            " [ 3  4]\n",
            " [ 3  3]]\n",
            "Fitness\n",
            "[  1.4835133    1.4835133    1.4835133    1.4835133  -59.21227339\n",
            "   1.4835133   -1.81579583   1.4835133 ]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[ 3  3]\n",
            " [-3  3]\n",
            " [ 3  3]\n",
            " [ 3  3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[-3  3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  36\n",
            "Population Matrix\n",
            "[[ 3  3]\n",
            " [ 3  3]\n",
            " [ 3  3]\n",
            " [ 3  3]\n",
            " [ 3  3]\n",
            " [-3  3]\n",
            " [ 3  3]\n",
            " [ 3  3]]\n",
            "Fitness\n",
            "[  1.4835133    1.4835133    1.4835133    1.4835133    1.4835133\n",
            " -36.06452281   1.4835133    1.4835133 ]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  37\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133\n",
            " 1.4835133]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  38\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133\n",
            " 1.4835133]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[3 3]\n",
            " [2 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[2 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  39\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [2 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[ 1.4835133   1.4835133   1.4835133   1.4835133   1.4835133  -1.53293009\n",
            "  1.4835133   1.4835133 ]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[2 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[2 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  40\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [2 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[ 1.4835133   1.4835133   1.4835133   1.4835133  -1.53293009  1.4835133\n",
            "  1.4835133   1.4835133 ]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  41\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133\n",
            " 1.4835133]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[4 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[4 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  42\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [4 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[ 1.4835133   1.4835133   1.4835133   1.4835133  -0.81694222  1.4835133\n",
            "  1.4835133   1.4835133 ]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[ 3  3]\n",
            " [ 3 -2]\n",
            " [ 3  3]\n",
            " [ 3 -5]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[ 3 -2]\n",
            "[3 3]\n",
            "[ 3 -5]\n",
            "Generation :  43\n",
            "Population Matrix\n",
            "[[ 3  3]\n",
            " [ 3  3]\n",
            " [ 3  3]\n",
            " [ 3  3]\n",
            " [ 3  3]\n",
            " [ 3 -2]\n",
            " [ 3  3]\n",
            " [ 3 -5]]\n",
            "Fitness\n",
            "[  1.4835133    1.4835133    1.4835133    1.4835133    1.4835133\n",
            " -21.76511013   1.4835133  -58.52641482]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  44\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133\n",
            " 1.4835133]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  45\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133\n",
            " 1.4835133]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[-5  3]\n",
            " [ 3  3]\n",
            " [ 3  3]\n",
            " [ 3  3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[-5  3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  46\n",
            "Population Matrix\n",
            "[[ 3  3]\n",
            " [ 3  3]\n",
            " [ 3  3]\n",
            " [ 3  3]\n",
            " [-5  3]\n",
            " [ 3  3]\n",
            " [ 3  3]\n",
            " [ 3  3]]\n",
            "Fitness\n",
            "[  1.4835133    1.4835133    1.4835133    1.4835133  -64.73587963\n",
            "   1.4835133    1.4835133    1.4835133 ]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  47\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133\n",
            " 1.4835133]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  48\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133\n",
            " 1.4835133]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Generation :  49\n",
            "Population Matrix\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Fitness\n",
            "[1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133 1.4835133\n",
            " 1.4835133]\n",
            "Best Fitness: -1.483513295303561\n",
            "Parents\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Crossover\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "Mutation\n",
            "[[3 3]\n",
            " [3 3]\n",
            " [3 3]\n",
            " [3 3]]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "[3 3]\n",
            "Best solution :  [3 3]\n",
            "Best solution fitness :  1.483513295303561\n"
          ]
        },
        {
          "data": {
            "image/png": "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",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "# Visualize the generations of the GA for the 2nd objective function.\n",
        "new_population = generatePopulationForFunc2()\n",
        "new_population_fitness = np.array([])\n",
        "best_outputs = []\n",
        "best_average_outputs = []\n",
        "num_generations = 50\n",
        "num_parents_mating = 4\n",
        "offspring_size = 4\n",
        "\n",
        "for generation in range(num_generations):\n",
        "    print(\"Generation : \", generation)\n",
        "\n",
        "    print(\"Population Matrix\")\n",
        "    print(new_population)\n",
        "\n",
        "    # Measuring the fitness of each chromosome in the population.\n",
        "    population_fitness = calculatePopFitnessFunction2(new_population)\n",
        "    print(\"Fitness\")\n",
        "    print(population_fitness)\n",
        "    print(\"Best Fitness:\", -1*np.max(population_fitness))\n",
        "    best_outputs.append(-1 * np.max(population_fitness))\n",
        "    best_average_outputs.append(np.average(population_fitness))\n",
        "\n",
        "    # Selecting the best parents in the population for mating.\n",
        "    parents = select_mating_pool_func2(new_population, population_fitness, num_parents_mating)\n",
        "    print(\"Parents\")\n",
        "    print(parents)\n",
        "\n",
        "    # Generating next generation using crossover.\n",
        "    offspring_crossover = fiftyPercentCrossoverFunctionTwo(parents, offspring_size)\n",
        "    print(\"Crossover\")\n",
        "    print(offspring_crossover)\n",
        "\n",
        "    # Adding some variations to the offspring using mutation.\n",
        "    offspring_mutation = np.array([])\n",
        "    for i in range(len(offspring_crossover)):\n",
        "        if(offspring_mutation.shape[0] == 0):\n",
        "            offspring_mutation = mutationFunctionTwo(offspring_crossover[i], 0.1)\n",
        "        else:\n",
        "            offspring_mutation = np.vstack((offspring_mutation, mutationFunctionTwo(offspring_crossover[i],  0.05)))\n",
        "    print(\"Mutation\")\n",
        "    print(offspring_mutation)\n",
        "\n",
        "    new_population = np.vstack((parents, offspring_mutation))\n",
        "\n",
        "    for i in range(len(new_population)):\n",
        "        new_population[i] = repairFunctionTwo(new_population[i], [-5 ,5])\n",
        "    \n",
        "# Getting the best solution after iterating finishing all generations.\n",
        "# At first, the fitness is calculated for each solution in the final generation.\n",
        "new_population_fitness = calculatePopFitnessFunction2(new_population)\n",
        "\n",
        "# Then return the index of that solution corresponding to the best fitness.\n",
        "best_match_idx = np.where(new_population_fitness == np.max(new_population_fitness))[0][0]\n",
        "\n",
        "print(\"Best solution : \", new_population[best_match_idx])\n",
        "print(\"Best solution fitness : \", new_population_fitness[best_match_idx])\n",
        "\n",
        "matplotlib.pyplot.plot(best_outputs)\n",
        "matplotlib.pyplot.plot(best_average_outputs)\n",
        "matplotlib.pyplot.xlabel(\"Iteration\")\n",
        "matplotlib.pyplot.ylabel(\"Fitness\")\n",
        "matplotlib.pyplot.show()"
      ]
    }
  ],
  "metadata": {
    "colab": {
      "provenance": []
    },
    "kernelspec": {
      "display_name": "Python 3.9.7",
      "language": "python",
      "name": "python3"
    },
    "language_info": {
      "codemirror_mode": {
        "name": "ipython",
        "version": 3
      },
      "file_extension": ".py",
      "mimetype": "text/x-python",
      "name": "python",
      "nbconvert_exporter": "python",
      "pygments_lexer": "ipython3",
      "version": "3.9.7"
    },
    "vscode": {
      "interpreter": {
        "hash": "bd8840e4b805e6c306030f2f45ef2cb25a3f70d3a477bda7a0575d8107e3354d"
      }
    }
  },
  "nbformat": 4,
  "nbformat_minor": 0
}