sample.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {
    "toc": true
   },
   "source": [
    "<h1>Table of Contents<span class=\"tocSkip\"></span></h1>\n",
    "<div class=\"toc\"><ul class=\"toc-item\"><li><span><a href=\"#Load-distances-data\" data-toc-modified-id=\"Load-distances-data-1\"><span class=\"toc-item-num\">1&nbsp;&nbsp;</span>Load distances data</a></span></li><li><span><a href=\"#Create-a-GeneticAlgorithmTSP-object\" data-toc-modified-id=\"Create-a-GeneticAlgorithmTSP-object-2\"><span class=\"toc-item-num\">2&nbsp;&nbsp;</span>Create a GeneticAlgorithmTSP object</a></span><ul class=\"toc-item\"><li><span><a href=\"#Run-the-GA\" data-toc-modified-id=\"Run-the-GA-2.1\"><span class=\"toc-item-num\">2.1&nbsp;&nbsp;</span>Run the GA</a></span></li></ul></li><li><span><a href=\"#Generate-a-plot-for-the-best-solution\" data-toc-modified-id=\"Generate-a-plot-for-the-best-solution-3\"><span class=\"toc-item-num\">3&nbsp;&nbsp;</span>Generate a plot for the best solution</a></span></li></ul></div>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2021-05-02 00:48:33,890\tINFO services.py:1174 -- View the Ray dashboard at http://127.0.0.1:8265\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "import folium\n",
    "from branca.element import Figure\n",
    "import pandas as pd\n",
    "import GeneticAlgoLibrary"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Load distances data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Bangalore</th>\n",
       "      <th>Jaipur</th>\n",
       "      <th>Varanasi</th>\n",
       "      <th>Udaipur</th>\n",
       "      <th>Delhi</th>\n",
       "      <th>Chennai</th>\n",
       "      <th>Mysore</th>\n",
       "      <th>Agra</th>\n",
       "      <th>Kolkata</th>\n",
       "      <th>Mumbai</th>\n",
       "      <th>Hyderabad</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>Bangalore</th>\n",
       "      <td>0</td>\n",
       "      <td>2026</td>\n",
       "      <td>1825</td>\n",
       "      <td>1724</td>\n",
       "      <td>2166</td>\n",
       "      <td>346</td>\n",
       "      <td>149</td>\n",
       "      <td>1923</td>\n",
       "      <td>1862</td>\n",
       "      <td>980</td>\n",
       "      <td>569</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Jaipur</th>\n",
       "      <td>2026</td>\n",
       "      <td>0</td>\n",
       "      <td>849</td>\n",
       "      <td>393</td>\n",
       "      <td>287</td>\n",
       "      <td>2108</td>\n",
       "      <td>2121</td>\n",
       "      <td>240</td>\n",
       "      <td>1520</td>\n",
       "      <td>1146</td>\n",
       "      <td>1483</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Varanasi</th>\n",
       "      <td>1825</td>\n",
       "      <td>849</td>\n",
       "      <td>0</td>\n",
       "      <td>1154</td>\n",
       "      <td>834</td>\n",
       "      <td>1862</td>\n",
       "      <td>1976</td>\n",
       "      <td>614</td>\n",
       "      <td>683</td>\n",
       "      <td>1524</td>\n",
       "      <td>1237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Udaipur</th>\n",
       "      <td>1724</td>\n",
       "      <td>393</td>\n",
       "      <td>1154</td>\n",
       "      <td>0</td>\n",
       "      <td>661</td>\n",
       "      <td>2077</td>\n",
       "      <td>1809</td>\n",
       "      <td>634</td>\n",
       "      <td>1825</td>\n",
       "      <td>753</td>\n",
       "      <td>1349</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Delhi</th>\n",
       "      <td>2166</td>\n",
       "      <td>287</td>\n",
       "      <td>834</td>\n",
       "      <td>661</td>\n",
       "      <td>0</td>\n",
       "      <td>2203</td>\n",
       "      <td>2317</td>\n",
       "      <td>233</td>\n",
       "      <td>1498</td>\n",
       "      <td>1415</td>\n",
       "      <td>1578</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Chennai</th>\n",
       "      <td>346</td>\n",
       "      <td>2108</td>\n",
       "      <td>1862</td>\n",
       "      <td>2077</td>\n",
       "      <td>2203</td>\n",
       "      <td>0</td>\n",
       "      <td>482</td>\n",
       "      <td>1957</td>\n",
       "      <td>1669</td>\n",
       "      <td>1345</td>\n",
       "      <td>627</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mysore</th>\n",
       "      <td>149</td>\n",
       "      <td>2121</td>\n",
       "      <td>1976</td>\n",
       "      <td>1809</td>\n",
       "      <td>2317</td>\n",
       "      <td>482</td>\n",
       "      <td>0</td>\n",
       "      <td>2072</td>\n",
       "      <td>2012</td>\n",
       "      <td>1064</td>\n",
       "      <td>718</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Agra</th>\n",
       "      <td>1923</td>\n",
       "      <td>240</td>\n",
       "      <td>614</td>\n",
       "      <td>634</td>\n",
       "      <td>233</td>\n",
       "      <td>1957</td>\n",
       "      <td>2072</td>\n",
       "      <td>0</td>\n",
       "      <td>1280</td>\n",
       "      <td>1323</td>\n",
       "      <td>1334</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Kolkata</th>\n",
       "      <td>1862</td>\n",
       "      <td>1520</td>\n",
       "      <td>683</td>\n",
       "      <td>1825</td>\n",
       "      <td>1498</td>\n",
       "      <td>1669</td>\n",
       "      <td>2012</td>\n",
       "      <td>1280</td>\n",
       "      <td>0</td>\n",
       "      <td>2053</td>\n",
       "      <td>1493</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Mumbai</th>\n",
       "      <td>980</td>\n",
       "      <td>1146</td>\n",
       "      <td>1524</td>\n",
       "      <td>753</td>\n",
       "      <td>1415</td>\n",
       "      <td>1345</td>\n",
       "      <td>1064</td>\n",
       "      <td>1323</td>\n",
       "      <td>2053</td>\n",
       "      <td>0</td>\n",
       "      <td>711</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>Hyderabad</th>\n",
       "      <td>569</td>\n",
       "      <td>1483</td>\n",
       "      <td>1237</td>\n",
       "      <td>1349</td>\n",
       "      <td>1578</td>\n",
       "      <td>627</td>\n",
       "      <td>718</td>\n",
       "      <td>1334</td>\n",
       "      <td>1493</td>\n",
       "      <td>711</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           Bangalore  Jaipur  Varanasi  Udaipur  Delhi  Chennai  Mysore  Agra  \\\n",
       "Bangalore          0    2026      1825     1724   2166      346     149  1923   \n",
       "Jaipur          2026       0       849      393    287     2108    2121   240   \n",
       "Varanasi        1825     849         0     1154    834     1862    1976   614   \n",
       "Udaipur         1724     393      1154        0    661     2077    1809   634   \n",
       "Delhi           2166     287       834      661      0     2203    2317   233   \n",
       "Chennai          346    2108      1862     2077   2203        0     482  1957   \n",
       "Mysore           149    2121      1976     1809   2317      482       0  2072   \n",
       "Agra            1923     240       614      634    233     1957    2072     0   \n",
       "Kolkata         1862    1520       683     1825   1498     1669    2012  1280   \n",
       "Mumbai           980    1146      1524      753   1415     1345    1064  1323   \n",
       "Hyderabad        569    1483      1237     1349   1578      627     718  1334   \n",
       "\n",
       "           Kolkata  Mumbai  Hyderabad  \n",
       "Bangalore     1862     980        569  \n",
       "Jaipur        1520    1146       1483  \n",
       "Varanasi       683    1524       1237  \n",
       "Udaipur       1825     753       1349  \n",
       "Delhi         1498    1415       1578  \n",
       "Chennai       1669    1345        627  \n",
       "Mysore        2012    1064        718  \n",
       "Agra          1280    1323       1334  \n",
       "Kolkata          0    2053       1493  \n",
       "Mumbai        2053       0        711  \n",
       "Hyderabad     1493     711          0  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data = pd.read_csv(\"./data/cities_and_distances.csv\")\n",
    "data.reset_index(inplace=True)\n",
    "data1 = data.iloc[:,2:]\n",
    "data1.index = data1.columns.values\n",
    "data1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create a GeneticAlgorithmTSP object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "ga_obj =  GeneticAlgoLibrary.GeneticAlgorithmTSP(number_of_cities=11,\n",
    "                             initial_pop_size=10,\n",
    "                             nelite=5,\n",
    "                             percentage_to_crossover=30,\n",
    "                             percentage_to_mutate=20,\n",
    "                             dist_mat=data1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "(pid=19324) 2021-05-02 00:48:49,095\tINFO worker.py:665 -- Calling ray.init() again after it has already been called.\n",
      "(pid=19032) 2021-05-02 00:48:49,143\tINFO worker.py:665 -- Calling ray.init() again after it has already been called.\n",
      "(pid=17720) 2021-05-02 00:48:49,143\tINFO worker.py:665 -- Calling ray.init() again after it has already been called.\n",
      "(pid=348) 2021-05-02 00:48:49,135\tINFO worker.py:665 -- Calling ray.init() again after it has already been called.\n"
     ]
    },
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       "      <td>11861</td>\n",
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       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>[4, 2, 1, 7, 9, 3, 5, 10, 8, 6]</td>\n",
       "      <td>12523</td>\n",
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       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>[1, 8, 3, 10, 5, 4, 7, 2, 9, 6]</td>\n",
       "      <td>13134</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>[4, 9, 1, 3, 5, 2, 8, 7, 10, 6]</td>\n",
       "      <td>13223</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
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       "      <td>14154</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>[10, 1, 8, 9, 7, 3, 4, 5, 2, 6]</td>\n",
       "      <td>14433</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>[2, 7, 10, 4, 9, 3, 6, 5, 8, 1]</td>\n",
       "      <td>15025</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>[6, 3, 7, 8, 10, 4, 9, 2, 5, 1]</td>\n",
       "      <td>15878</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>[7, 9, 2, 3, 4, 5, 8, 6, 10, 1]</td>\n",
       "      <td>16696</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>[1, 6, 8, 10, 7, 9, 3, 5, 2, 4]</td>\n",
       "      <td>18001</td>\n",
       "    </tr>\n",
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      ],
      "text/plain": [
       "                             Route   Cost\n",
       "0  [6, 10, 3, 1, 4, 7, 9, 8, 5, 2]  11861\n",
       "8  [4, 2, 1, 7, 9, 3, 5, 10, 8, 6]  12523\n",
       "9  [1, 8, 3, 10, 5, 4, 7, 2, 9, 6]  13134\n",
       "2  [4, 9, 1, 3, 5, 2, 8, 7, 10, 6]  13223\n",
       "3  [9, 3, 6, 10, 8, 7, 5, 2, 1, 4]  14154\n",
       "1  [10, 1, 8, 9, 7, 3, 4, 5, 2, 6]  14433\n",
       "7  [2, 7, 10, 4, 9, 3, 6, 5, 8, 1]  15025\n",
       "5  [6, 3, 7, 8, 10, 4, 9, 2, 5, 1]  15878\n",
       "6  [7, 9, 2, 3, 4, 5, 8, 6, 10, 1]  16696\n",
       "4  [1, 6, 8, 10, 7, 9, 3, 5, 2, 4]  18001"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ga_obj.initial_pop_cost()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
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       "      <th>0</th>\n",
       "      <td>[6, 10, 3, 1, 4, 7, 9, 8, 5, 2]</td>\n",
       "      <td>11861</td>\n",
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       "      <th>8</th>\n",
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       "      <td>12523</td>\n",
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       "      <th>9</th>\n",
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       "      <td>13134</td>\n",
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       "      <th>2</th>\n",
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       "      <td>13223</td>\n",
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       "                             Route   Cost\n",
       "0  [6, 10, 3, 1, 4, 7, 9, 8, 5, 2]  11861\n",
       "8  [4, 2, 1, 7, 9, 3, 5, 10, 8, 6]  12523\n",
       "9  [1, 8, 3, 10, 5, 4, 7, 2, 9, 6]  13134\n",
       "2  [4, 9, 1, 3, 5, 2, 8, 7, 10, 6]  13223\n",
       "3  [9, 3, 6, 10, 8, 7, 5, 2, 1, 4]  14154"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ga_obj.the_elite_few()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Mutation: 100%|█████████████████████████████████████████████████████████████████████████████████████| 5/5 [00:00<?, ?it/s]\n"
     ]
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       "      <th>0</th>\n",
       "      <td>[8, 5, 2, 6, 10, 3, 1, 4, 7, 9]</td>\n",
       "      <td>12652</td>\n",
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       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>[2, 1, 7, 9, 3, 5, 10, 8, 6, 4]</td>\n",
       "      <td>15682</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>[7, 2, 9, 6, 1, 8, 3, 10, 5, 4]</td>\n",
       "      <td>16936</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>[6, 4, 9, 1, 3, 5, 2, 8, 7, 10]</td>\n",
       "      <td>13225</td>\n",
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       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>[6, 10, 8, 7, 5, 2, 1, 4, 9, 3]</td>\n",
       "      <td>12487</td>\n",
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      "text/plain": [
       "                             Route   Cost\n",
       "0  [8, 5, 2, 6, 10, 3, 1, 4, 7, 9]  12652\n",
       "1  [2, 1, 7, 9, 3, 5, 10, 8, 6, 4]  15682\n",
       "2  [7, 2, 9, 6, 1, 8, 3, 10, 5, 4]  16936\n",
       "3  [6, 4, 9, 1, 3, 5, 2, 8, 7, 10]  13225\n",
       "4  [6, 10, 8, 7, 5, 2, 1, 4, 9, 3]  12487"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ga_obj.mutation_function(ga_obj.the_elite_few())"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[10, 3, 1, 4, 7, 9, 8, 5, 2, 6]"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ga_obj.get_mutated_path([8, 5, 2, 6, 10, 3, 1, 4, 7, 9],4)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Run the GA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# ga_obj = GeneticAlgoLibrary.OverallGaRun(noverall=1,\n",
    "#                                      number_of_cities=11,\n",
    "#                                      initial_pop_size=1000,\n",
    "#                                      nelite=10,\n",
    "#                                      percentage_to_crossover=20,\n",
    "#                                      percentage_to_mutate=20,\n",
    "#                                      dist_mat=data1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Cities Mapping: 100%|█████████████████████████████████████████████████████████████████████████████| 11/11 [00:00<?, ?it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Starting 10 iterations of the GA\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 68.94it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 192.06it/s]\n",
      "Crossover: 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 171.19it/s]\n",
      "Crossover: 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 177.79it/s]\n",
      "Crossover: 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 458.04it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 192.08it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-----------------------------------------------------------------\n",
      "Best solution for initial population size of 10000 and number \n",
      "            of runs 10 is \n",
      "                              Route  Cost\n",
      "1  [5, 10, 6, 9, 3, 1, 4, 7, 2, 8]  7580\n",
      "Generated 20(0.001%) of the 3628800 solutions\n",
      "Total distance travelled to cover the final route of \n",
      " Bangalore => Chennai => Hyderabad => Mysore => Mumbai => Udaipur => Jaipur => Delhi => Agra => Varanasi => Kolkata => Bangalore is 7580 KM.\n",
      "             (Generated from initial population size of 10000)\n",
      "-----------------------------------------------------------------\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Cities Mapping: 100%|█████████████████████████████████████████████████████████████████████████████| 11/11 [00:00<?, ?it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Starting 100 iterations of the GA\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 375.34it/s]\n",
      "Crossover: 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 316.15it/s]\n",
      "Crossover: 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 673.13it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 188.80it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 375.19it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 192.04it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 173.79it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 656.73it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 192.06it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 374.74it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 375.40it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 192.05it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 371.98it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 375.39it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 375.43it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 375.41it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 376.91it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 375.41it/s]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 375.12it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 376.90it/s]\n",
      "Crossover: 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 376.62it/s]\n",
      "Crossover: 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 375.31it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 376.68it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 376.07it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 376.64it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 375.15it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|████████████████████████████████████████████████████████████████████████████████████| 3/3 [00:00<?, ?it/s]\n",
      "Crossover: 100%|███████████████████████████████████████████████████████████████████████████| 3/3 [00:00<00:00, 375.31it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-----------------------------------------------------------------\n",
      "Best solution for initial population size of 10000 and number \n",
      "            of runs 100 is \n",
      "                              Route  Cost\n",
      "1  [10, 9, 3, 1, 4, 7, 2, 8, 5, 6]  6543\n",
      "Generated 200(0.006%) of the 3628800 solutions\n",
      "Total distance travelled to cover the final route of \n",
      " Bangalore => Hyderabad => Mumbai => Udaipur => Jaipur => Delhi => Agra => Varanasi => Kolkata => Chennai => Mysore => Bangalore is 6543 KM.\n",
      "             (Generated from initial population size of 10000)\n",
      "-----------------------------------------------------------------\n"
     ]
    }
   ],
   "source": [
    "for i in [10,\n",
    "          100,\n",
    "#           1000\n",
    "         ]:\n",
    "    ga_obj = GeneticAlgoLibrary.OverallGaRun(noverall=i,\n",
    "                                       number_of_cities=11,\n",
    "                                       initial_pop_size=10000,\n",
    "                                       nelite=10,\n",
    "                                       percentage_to_crossover=20,\n",
    "                                       percentage_to_mutate=20,\n",
    "                                       dist_mat=data1)\n",
    "    best_sol = ga_obj.run_overall_ga()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Generate a plot for the best solution"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
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                [[12.9716, 77.5946], [17.385, 78.4867], [19.076, 72.8777], [24.5854, 73.7125], [26.9124, 75.7873], [28.7041, 77.1025], [27.1767, 78.0081], [25.3176, 82.9739], [22.5726, 88.3639], [13.0827, 80.2707], [12.2958, 76.6394]],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": false, "fillColor": "blue", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "noClip": false, "opacity": 1.0, "smoothFactor": 1.0, "stroke": true, "weight": 2}
            ).addTo(map_29c2732204e442bfbc2fa2e5638841d5);
        
    
        var popup_3434278b542a4ea09c9e79f5dc1efca3 = L.popup({"maxWidth": "100%"});

        
            var html_18f410c641b8464ea558ffb067e36713 = $(`<div id="html_18f410c641b8464ea558ffb067e36713" style="width: 100.0%; height: 100.0%;"><b>Best path</b></div>`)[0];
            popup_3434278b542a4ea09c9e79f5dc1efca3.setContent(html_18f410c641b8464ea558ffb067e36713);
        

        poly_line_7b7e41ee1af34e77bcddd1a91f28a4e3.bindPopup(popup_3434278b542a4ea09c9e79f5dc1efca3)
        ;

        
    
    
            poly_line_7b7e41ee1af34e77bcddd1a91f28a4e3.bindTooltip(
                `<div>
                     Route
                 </div>`,
                {"sticky": true}
            );
        
    
            var poly_line_411d9d6c6f654aec97adbd76d9ccd26d = L.polyline(
                [[12.9716, 77.5946], [17.385, 78.4867], [19.076, 72.8777], [24.5854, 73.7125], [26.9124, 75.7873], [28.7041, 77.1025], [27.1767, 78.0081], [25.3176, 82.9739], [22.5726, 88.3639], [13.0827, 80.2707], [12.2958, 76.6394], [12.9716, 77.5946]],
                {"bubblingMouseEvents": true, "color": "blue", "dashArray": null, "dashOffset": null, "fill": false, "fillColor": "blue", "fillOpacity": 0.2, "fillRule": "evenodd", "lineCap": "round", "lineJoin": "round", "noClip": false, "opacity": 1.0, "smoothFactor": 1.0, "stroke": true, "weight": 2}
            ).addTo(map_29c2732204e442bfbc2fa2e5638841d5);
        
    
        var popup_7fa1d4942d984635b05b425915ec43c2 = L.popup({"maxWidth": "100%"});

        
            var html_d38fcc48e3584a5c96203a8994d7182d = $(`<div id="html_d38fcc48e3584a5c96203a8994d7182d" style="width: 100.0%; height: 100.0%;"><b>Best path</b></div>`)[0];
            popup_7fa1d4942d984635b05b425915ec43c2.setContent(html_d38fcc48e3584a5c96203a8994d7182d);
        

        poly_line_411d9d6c6f654aec97adbd76d9ccd26d.bindPopup(popup_7fa1d4942d984635b05b425915ec43c2)
        ;

        
    
    
            poly_line_411d9d6c6f654aec97adbd76d9ccd26d.bindTooltip(
                `<div>
                     Route
                 </div>`,
                {"sticky": true}
            );
        
</script> onload=\"this.contentDocument.open();this.contentDocument.write(atob(this.getAttribute('data-html')));this.contentDocument.close();\" \"allowfullscreen\" \"webkitallowfullscreen\" \"mozallowfullscreen\"></iframe>"
      ],
      "text/plain": [
       "<folium.folium.Map at 0x15038f79f28>"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Adding the starting point i.e bangalore in this case\n",
    "final_route = [0]\n",
    "final_route.extend(best_sol[0][\"Route\"].values[0])\n",
    "final_route.append(0)\n",
    "\n",
    "# creating a lisot with naplot_objectes\n",
    "final_route_naplot_objectes = []\n",
    "for i in final_route:\n",
    "    final_route_naplot_objectes.append(data1.index[i])\n",
    "\n",
    "lat_lon = pd.read_csv(\"./data/city_lat_lon.csv\")\n",
    "\n",
    "\n",
    "fig=Figure(height=1000,width=750)\n",
    "plot_object=folium.Map(location=[12.9716, 77.5946],tiles='cartodbpositron',zoom_start=5)\n",
    "fig.add_child(plot_object)\n",
    "\n",
    "coordinates = []\n",
    "for i in final_route_naplot_objectes:\n",
    "    lat,lon = lat_lon[lat_lon.City == i][\"Lat\"].values[0],lat_lon[lat_lon.City == i][\"Lon\"].values[0]\n",
    "    folio_group_object = folium.FeatureGroup(\"Route\")\n",
    "    coordinates.append([lat,lon])\n",
    "    line_1=folium.vector_layers.PolyLine(coordinates,popup='<b>Best path</b>',tooltip='Route',color='blue',\n",
    "                                         weight=2).add_to(folio_group_object)\n",
    "    line_1.add_to(plot_object)\n",
    "plot_object"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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