lab10

Reviewed-on: #9

lab_10/lab10.ipynb

@@ -0,0 +1,664 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "0c5af2a3",
+   "metadata": {},
+   "source": [
+    "## Лабораторная 10\n",
+    "Датасет: Knapsack Problem Data (https://www.kaggle.com/datasets/warcoder/knapsack-problem)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "b54c40b4",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Weights</th>\n",
+       "      <th>Prices</th>\n",
+       "      <th>Capacity</th>\n",
+       "      <th>Best picks</th>\n",
+       "      <th>Best price</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>[46 40 42 38 10]</td>\n",
+       "      <td>[12 19 19 15  8]</td>\n",
+       "      <td>40</td>\n",
+       "      <td>[0. 1. 0. 0. 0.]</td>\n",
+       "      <td>19.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>[11 31  4  6  7]</td>\n",
+       "      <td>[ 2  8 18 16  3]</td>\n",
+       "      <td>64</td>\n",
+       "      <td>[1. 1. 1. 1. 1.]</td>\n",
+       "      <td>47.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>[32 49 27 37 24]</td>\n",
+       "      <td>[19 16 16  4  1]</td>\n",
+       "      <td>87</td>\n",
+       "      <td>[1. 0. 1. 0. 1.]</td>\n",
+       "      <td>36.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>[20 35 22 23 16]</td>\n",
+       "      <td>[19 17 19  9  1]</td>\n",
+       "      <td>21</td>\n",
+       "      <td>[1. 0. 0. 0. 0.]</td>\n",
+       "      <td>19.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>[ 7 12 19 13 20]</td>\n",
+       "      <td>[10 11 18 15  5]</td>\n",
+       "      <td>50</td>\n",
+       "      <td>[0. 1. 1. 1. 0.]</td>\n",
+       "      <td>44.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9995</th>\n",
+       "      <td>[18 12 11 49 32]</td>\n",
+       "      <td>[12  3 17 19  7]</td>\n",
+       "      <td>41</td>\n",
+       "      <td>[1. 1. 1. 0. 0.]</td>\n",
+       "      <td>32.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9996</th>\n",
+       "      <td>[20  2 24  7  7]</td>\n",
+       "      <td>[17 12  4  3  8]</td>\n",
+       "      <td>17</td>\n",
+       "      <td>[0. 1. 0. 1. 1.]</td>\n",
+       "      <td>23.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9997</th>\n",
+       "      <td>[43 43  5 15 23]</td>\n",
+       "      <td>[15  5  7  2  7]</td>\n",
+       "      <td>62</td>\n",
+       "      <td>[1. 0. 1. 0. 0.]</td>\n",
+       "      <td>22.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9998</th>\n",
+       "      <td>[49  9 15 21 39]</td>\n",
+       "      <td>[11 15  3 12 19]</td>\n",
+       "      <td>65</td>\n",
+       "      <td>[0. 1. 1. 0. 1.]</td>\n",
+       "      <td>37.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9999</th>\n",
+       "      <td>[25 36 42 19 39]</td>\n",
+       "      <td>[15 12  7 18 12]</td>\n",
+       "      <td>79</td>\n",
+       "      <td>[1. 0. 0. 1. 0.]</td>\n",
+       "      <td>33.0</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>10000 rows × 5 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "               Weights            Prices  Capacity        Best picks  \\\n",
+       "0     [46 40 42 38 10]  [12 19 19 15  8]        40  [0. 1. 0. 0. 0.]   \n",
+       "1     [11 31  4  6  7]  [ 2  8 18 16  3]        64  [1. 1. 1. 1. 1.]   \n",
+       "2     [32 49 27 37 24]  [19 16 16  4  1]        87  [1. 0. 1. 0. 1.]   \n",
+       "3     [20 35 22 23 16]  [19 17 19  9  1]        21  [1. 0. 0. 0. 0.]   \n",
+       "4     [ 7 12 19 13 20]  [10 11 18 15  5]        50  [0. 1. 1. 1. 0.]   \n",
+       "...                ...               ...       ...               ...   \n",
+       "9995  [18 12 11 49 32]  [12  3 17 19  7]        41  [1. 1. 1. 0. 0.]   \n",
+       "9996  [20  2 24  7  7]  [17 12  4  3  8]        17  [0. 1. 0. 1. 1.]   \n",
+       "9997  [43 43  5 15 23]  [15  5  7  2  7]        62  [1. 0. 1. 0. 0.]   \n",
+       "9998  [49  9 15 21 39]  [11 15  3 12 19]        65  [0. 1. 1. 0. 1.]   \n",
+       "9999  [25 36 42 19 39]  [15 12  7 18 12]        79  [1. 0. 0. 1. 0.]   \n",
+       "\n",
+       "      Best price  \n",
+       "0           19.0  \n",
+       "1           47.0  \n",
+       "2           36.0  \n",
+       "3           19.0  \n",
+       "4           44.0  \n",
+       "...          ...  \n",
+       "9995        32.0  \n",
+       "9996        23.0  \n",
+       "9997        22.0  \n",
+       "9998        37.0  \n",
+       "9999        33.0  \n",
+       "\n",
+       "[10000 rows x 5 columns]"
+      ]
+     },
+     "execution_count": 2,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import pandas as pd\n",
+    "\n",
+    "df = pd.read_csv(\".//static//csv//knapsack_5_items.csv\")\n",
+    "\n",
+    "df"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "44d383ce",
+   "metadata": {},
+   "source": [
+    "Хромосома - набор 0 и 1, 1 - предмет выбран, 0 - не выбран.\n",
+    "Ген - одно значение в хромосоме."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5b9bb0e1",
+   "metadata": {},
+   "source": [
+    "Функция генерации начальной популяции"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "de8b8b81",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "[[0, 0, 1, 1, 1],\n",
+       " [1, 0, 0, 1, 1],\n",
+       " [0, 1, 1, 1, 0],\n",
+       " [1, 1, 0, 1, 1],\n",
+       " [0, 0, 0, 0, 1],\n",
+       " [0, 1, 0, 1, 1],\n",
+       " [1, 1, 0, 0, 1],\n",
+       " [1, 0, 1, 1, 1],\n",
+       " [1, 0, 0, 0, 0],\n",
+       " [1, 0, 1, 1, 0]]"
+      ]
+     },
+     "execution_count": 4,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import random\n",
+    "\n",
+    "def create_individual(length):\n",
+    "    individual = []\n",
+    "    for _ in range(length):\n",
+    "        individual.append(random.randint(0, 1))\n",
+    "    return individual\n",
+    "\n",
+    "def create_population(length, size):\n",
+    "    population = []\n",
+    "    for _ in range(size):\n",
+    "        population.append(create_individual(length))\n",
+    "    return population\n",
+    "\n",
+    "create_population(5, 10)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f27534fb",
+   "metadata": {},
+   "source": [
+    "Фитнес-функция"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "da1c3553",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "44"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "def evaluate_fitness(individual, weights, prices, capacity):\n",
+    "    total_value = 0\n",
+    "    total_weight = 0\n",
+    "    \n",
+    "    for selected, weight, price in zip(individual, weights, prices):\n",
+    "        if selected:\n",
+    "            total_value += price\n",
+    "            total_weight += weight\n",
+    "            \n",
+    "    if total_weight > capacity:\n",
+    "        return 0\n",
+    "    return total_value\n",
+    "\n",
+    "evaluate_fitness([0, 1, 1, 1, 0], [7, 12, 19, 13, 20], [10, 11, 18, 15, 5], 50)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c9ef1b7b",
+   "metadata": {},
+   "source": [
+    "Оператор кроссинговера"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "37486d57",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "([0, 1, 1, 0, 0], [1, 0, 1, 1, 0])"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "def crossover(parent1, parent2):\n",
+    "    point = random.randint(1, len(parent1) - 1)\n",
+    "    return (parent1[:point] + parent2[point:], parent2[:point] + parent1[point:])\n",
+    "\n",
+    "crossover([0, 1, 1, 1, 0], [1, 0, 1, 0, 0])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "87c1a74a",
+   "metadata": {},
+   "source": [
+    "Операторы мутации"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "95d1068f",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "До мутации: [0, 1, 1, 1, 0]\n",
+      "После побитовой мутации: [1, 1, 0, 1, 0]\n",
+      "После свапа генов: [1, 0, 1, 1, 0]\n"
+     ]
+    }
+   ],
+   "source": [
+    "import random\n",
+    "\n",
+    "def mutate_flip_bits(individual, mutation_rate):\n",
+    "    for i in range(len(individual)):\n",
+    "        chance = random.random()\n",
+    "        if chance < mutation_rate:\n",
+    "            individual[i] = 1 - individual[i]\n",
+    "\n",
+    "def mutate_swap_genes(individual, mutation_rate):\n",
+    "    chance = random.random()\n",
+    "    if chance < mutation_rate and len(individual) >= 2:\n",
+    "        i, j = random.sample(range(len(individual)), 2)\n",
+    "        individual[i], individual[j] = individual[j], individual[i]\n",
+    "\n",
+    "individual = [0, 1, 1, 1, 0]\n",
+    "print(\"До мутации:\", individual)\n",
+    "\n",
+    "mutate_flip_bits(individual, 0.5)\n",
+    "print(\"После побитовой мутации:\", individual)\n",
+    "\n",
+    "mutate_swap_genes(individual, 1)\n",
+    "print(\"После свапа генов:\", individual)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5d2d9f69",
+   "metadata": {},
+   "source": [
+    "Реализация генетического алгоритма и его применение"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "3f4d52de",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Weights</th>\n",
+       "      <th>Prices</th>\n",
+       "      <th>Capacity</th>\n",
+       "      <th>Best picks</th>\n",
+       "      <th>Best price</th>\n",
+       "      <th>algorithmPicks</th>\n",
+       "      <th>algorithmPrice</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>[46 40 42 38 10]</td>\n",
+       "      <td>[12 19 19 15  8]</td>\n",
+       "      <td>40</td>\n",
+       "      <td>[0. 1. 0. 0. 0.]</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>[0, 1, 0, 0, 0]</td>\n",
+       "      <td>19</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>[11 31  4  6  7]</td>\n",
+       "      <td>[ 2  8 18 16  3]</td>\n",
+       "      <td>64</td>\n",
+       "      <td>[1. 1. 1. 1. 1.]</td>\n",
+       "      <td>47.0</td>\n",
+       "      <td>[1, 1, 1, 1, 1]</td>\n",
+       "      <td>47</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>[32 49 27 37 24]</td>\n",
+       "      <td>[19 16 16  4  1]</td>\n",
+       "      <td>87</td>\n",
+       "      <td>[1. 0. 1. 0. 1.]</td>\n",
+       "      <td>36.0</td>\n",
+       "      <td>[1, 0, 1, 0, 1]</td>\n",
+       "      <td>36</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>[20 35 22 23 16]</td>\n",
+       "      <td>[19 17 19  9  1]</td>\n",
+       "      <td>21</td>\n",
+       "      <td>[1. 0. 0. 0. 0.]</td>\n",
+       "      <td>19.0</td>\n",
+       "      <td>[1, 0, 0, 0, 0]</td>\n",
+       "      <td>19</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>[ 7 12 19 13 20]</td>\n",
+       "      <td>[10 11 18 15  5]</td>\n",
+       "      <td>50</td>\n",
+       "      <td>[0. 1. 1. 1. 0.]</td>\n",
+       "      <td>44.0</td>\n",
+       "      <td>[0, 1, 1, 1, 0]</td>\n",
+       "      <td>44</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9995</th>\n",
+       "      <td>[18 12 11 49 32]</td>\n",
+       "      <td>[12  3 17 19  7]</td>\n",
+       "      <td>41</td>\n",
+       "      <td>[1. 1. 1. 0. 0.]</td>\n",
+       "      <td>32.0</td>\n",
+       "      <td>[1, 1, 1, 0, 0]</td>\n",
+       "      <td>32</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9996</th>\n",
+       "      <td>[20  2 24  7  7]</td>\n",
+       "      <td>[17 12  4  3  8]</td>\n",
+       "      <td>17</td>\n",
+       "      <td>[0. 1. 0. 1. 1.]</td>\n",
+       "      <td>23.0</td>\n",
+       "      <td>[0, 1, 0, 1, 1]</td>\n",
+       "      <td>23</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9997</th>\n",
+       "      <td>[43 43  5 15 23]</td>\n",
+       "      <td>[15  5  7  2  7]</td>\n",
+       "      <td>62</td>\n",
+       "      <td>[1. 0. 1. 0. 0.]</td>\n",
+       "      <td>22.0</td>\n",
+       "      <td>[1, 0, 1, 0, 0]</td>\n",
+       "      <td>22</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9998</th>\n",
+       "      <td>[49  9 15 21 39]</td>\n",
+       "      <td>[11 15  3 12 19]</td>\n",
+       "      <td>65</td>\n",
+       "      <td>[0. 1. 1. 0. 1.]</td>\n",
+       "      <td>37.0</td>\n",
+       "      <td>[0, 1, 1, 0, 1]</td>\n",
+       "      <td>37</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9999</th>\n",
+       "      <td>[25 36 42 19 39]</td>\n",
+       "      <td>[15 12  7 18 12]</td>\n",
+       "      <td>79</td>\n",
+       "      <td>[1. 0. 0. 1. 0.]</td>\n",
+       "      <td>33.0</td>\n",
+       "      <td>[1, 0, 0, 1, 0]</td>\n",
+       "      <td>33</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "               Weights            Prices  Capacity        Best picks  \\\n",
+       "0     [46 40 42 38 10]  [12 19 19 15  8]        40  [0. 1. 0. 0. 0.]   \n",
+       "1     [11 31  4  6  7]  [ 2  8 18 16  3]        64  [1. 1. 1. 1. 1.]   \n",
+       "2     [32 49 27 37 24]  [19 16 16  4  1]        87  [1. 0. 1. 0. 1.]   \n",
+       "3     [20 35 22 23 16]  [19 17 19  9  1]        21  [1. 0. 0. 0. 0.]   \n",
+       "4     [ 7 12 19 13 20]  [10 11 18 15  5]        50  [0. 1. 1. 1. 0.]   \n",
+       "9995  [18 12 11 49 32]  [12  3 17 19  7]        41  [1. 1. 1. 0. 0.]   \n",
+       "9996  [20  2 24  7  7]  [17 12  4  3  8]        17  [0. 1. 0. 1. 1.]   \n",
+       "9997  [43 43  5 15 23]  [15  5  7  2  7]        62  [1. 0. 1. 0. 0.]   \n",
+       "9998  [49  9 15 21 39]  [11 15  3 12 19]        65  [0. 1. 1. 0. 1.]   \n",
+       "9999  [25 36 42 19 39]  [15 12  7 18 12]        79  [1. 0. 0. 1. 0.]   \n",
+       "\n",
+       "      Best price   algorithmPicks  algorithmPrice  \n",
+       "0           19.0  [0, 1, 0, 0, 0]              19  \n",
+       "1           47.0  [1, 1, 1, 1, 1]              47  \n",
+       "2           36.0  [1, 0, 1, 0, 1]              36  \n",
+       "3           19.0  [1, 0, 0, 0, 0]              19  \n",
+       "4           44.0  [0, 1, 1, 1, 0]              44  \n",
+       "9995        32.0  [1, 1, 1, 0, 0]              32  \n",
+       "9996        23.0  [0, 1, 0, 1, 1]              23  \n",
+       "9997        22.0  [1, 0, 1, 0, 0]              22  \n",
+       "9998        37.0  [0, 1, 1, 0, 1]              37  \n",
+       "9999        33.0  [1, 0, 0, 1, 0]              33  "
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "import ast\n",
+    "import re\n",
+    "\n",
+    "population_size = 100\n",
+    "num_generations = 10\n",
+    "mutation_rate = 0.1\n",
+    "mutation_strategy = 'flip'\n",
+    "\n",
+    "def select_parents(population, weights, prices, capacity):\n",
+    "    fitness_list = [evaluate_fitness(ind, weights, prices, capacity) for ind in population]\n",
+    "    total_fitness = sum(fitness_list)\n",
+    "\n",
+    "    if total_fitness == 0:\n",
+    "        return random.choice(population), random.choice(population)\n",
+    "\n",
+    "    selection_probs = [fitness / total_fitness for fitness in fitness_list]\n",
+    "    selected = random.choices(population, weights=selection_probs, k=2)\n",
+    "    return selected[0], selected[1]\n",
+    "\n",
+    "def genetic_algorithm(weights, prices, capacity,\n",
+    "                      population_size=100, num_generations=10,\n",
+    "                      mutation_rate=0.1, mutation_strategy='flip'):\n",
+    "\n",
+    "    num_elements = len(weights)\n",
+    "    population = create_population(num_elements, population_size)\n",
+    "\n",
+    "    for generation in range(num_generations):\n",
+    "        next_population = []\n",
+    "\n",
+    "        for _ in range(population_size // 2):\n",
+    "            parent1, parent2 = select_parents(population, weights, prices, capacity)\n",
+    "            child1, child2 = crossover(parent1, parent2)\n",
+    "\n",
+    "            if mutation_strategy == 'flip':\n",
+    "                mutate_flip_bits(child1, mutation_rate)\n",
+    "                mutate_flip_bits(child2, mutation_rate)\n",
+    "            elif mutation_strategy == 'swap':\n",
+    "                mutate_swap_genes(child1, mutation_rate)\n",
+    "                mutate_swap_genes(child2, mutation_rate)\n",
+    "\n",
+    "            next_population.append(child1)\n",
+    "            next_population.append(child2)\n",
+    "\n",
+    "        population = next_population\n",
+    "\n",
+    "    best_individual = None\n",
+    "    best_fitness = -1\n",
+    "\n",
+    "    for individual in population:\n",
+    "        fitness = evaluate_fitness(individual, weights, prices, capacity)\n",
+    "        if fitness > best_fitness:\n",
+    "            best_fitness = fitness\n",
+    "            best_individual = individual\n",
+    "\n",
+    "    return best_individual, best_fitness\n",
+    "\n",
+    "picks = []\n",
+    "best_prices = []\n",
+    "\n",
+    "def fix_list_string(s):\n",
+    "    s = re.sub(r'\\[\\s*', '[', s)\n",
+    "    s = re.sub(r'\\s*\\]', ']', s)\n",
+    "    s = re.sub(r'\\s+', ',', s)\n",
+    "    return s\n",
+    "\n",
+    "for _, row in df.iterrows():\n",
+    "    weights = ast.literal_eval(fix_list_string(row['Weights']))\n",
+    "    prices = ast.literal_eval(fix_list_string(row['Prices']))\n",
+    "    capacity = row['Capacity']\n",
+    "\n",
+    "    best_individual, best_value = genetic_algorithm(\n",
+    "        weights, prices, capacity,\n",
+    "        population_size, num_generations,\n",
+    "        mutation_rate, mutation_strategy\n",
+    "    )\n",
+    "    \n",
+    "    picks.append(best_individual)\n",
+    "    best_prices.append(best_value)\n",
+    "\n",
+    "df['algorithmPicks'] = picks\n",
+    "df['algorithmPrice'] = best_prices\n",
+    "\n",
+    "pd.concat([df.head(5), df.tail(5)])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e60888a3",
+   "metadata": {},
+   "source": [
+    "Ответы алгоритма совпадают с теми ответами, которые уже имелись в наборе данных"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "aimvenv",
+   "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": "3.12.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}