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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Real World Facility Backup Coverage Location Problem\n",
+    "\n",
+    "*Authors:* [Erin Olson](https://github.com/erinrolson), [Germano Barcelos](https://github.com/gegen07), [James Gaboardi](https://github.com/jGaboardi), [Levi J. Wolf](https://github.com/ljwolf), [Qunshan Zhao](https://github.com/qszhao)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 174,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import geopandas\n",
+    "import pandas\n",
+    "import pulp\n",
+    "from shapely.geometry import Point\n",
+    "import matplotlib.pyplot as plt\n",
+    "import time"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The problem is composed by 4 datafiles\n",
+    "- network distances were calculated using the ArcGIS Network Analyst Extension and contains the calculated distance between facility candidate sites to each demand node\n",
+    "- demand_points represents the demand nodes with important features for facility location modeling such as population metrics\n",
+    "- facility_points represents the stores that are candidate facility sites\n",
+    "- tract is the polygon of census tract 205.\n",
+    "\n",
+    "All datasets are available online in this [repository](https://github.com/huanfachen/Open_source_location_cover_models/tree/master/Data/San_Francisco_store)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 175,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "DIRPATH = \"../spopt/tests/data/\"\n",
+    "\n",
+    "network_distance = pandas.read_csv(DIRPATH+\"SF_network_distance_candidateStore_16_censusTract_205_new.csv\")\n",
+    "demand_points = pandas.read_csv(DIRPATH+ \"SF_demand_205_centroid_uniform_weight.csv\", index_col=0)\n",
+    "facility_points = pandas.read_csv(DIRPATH + \"SF_store_site_16_longlat.csv\", index_col=0)\n",
+    "study_area = geopandas.read_file(DIRPATH + \"ServiceAreas_4.shp\").dissolve()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Display network_distance dataframe"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 176,
+   "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>distance</th>\n",
+       "      <th>name</th>\n",
+       "      <th>DestinationName</th>\n",
+       "      <th>demand</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>671.573346</td>\n",
+       "      <td>Store_1</td>\n",
+       "      <td>60750479.01</td>\n",
+       "      <td>6540</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1333.708063</td>\n",
+       "      <td>Store_1</td>\n",
+       "      <td>60750479.02</td>\n",
+       "      <td>3539</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1656.188884</td>\n",
+       "      <td>Store_1</td>\n",
+       "      <td>60750352.02</td>\n",
+       "      <td>4436</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1783.006047</td>\n",
+       "      <td>Store_1</td>\n",
+       "      <td>60750602.00</td>\n",
+       "      <td>231</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>1790.950612</td>\n",
+       "      <td>Store_1</td>\n",
+       "      <td>60750478.00</td>\n",
+       "      <td>7787</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3275</th>\n",
+       "      <td>19643.307257</td>\n",
+       "      <td>Store_19</td>\n",
+       "      <td>60816023.00</td>\n",
+       "      <td>3204</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3276</th>\n",
+       "      <td>20245.369594</td>\n",
+       "      <td>Store_19</td>\n",
+       "      <td>60816029.00</td>\n",
+       "      <td>4135</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3277</th>\n",
+       "      <td>20290.986235</td>\n",
+       "      <td>Store_19</td>\n",
+       "      <td>60816026.00</td>\n",
+       "      <td>7887</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3278</th>\n",
+       "      <td>20875.680521</td>\n",
+       "      <td>Store_19</td>\n",
+       "      <td>60816025.00</td>\n",
+       "      <td>5146</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3279</th>\n",
+       "      <td>20958.530406</td>\n",
+       "      <td>Store_19</td>\n",
+       "      <td>60816024.00</td>\n",
+       "      <td>6511</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>3280 rows × 4 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "          distance      name  DestinationName  demand\n",
+       "0       671.573346   Store_1      60750479.01    6540\n",
+       "1      1333.708063   Store_1      60750479.02    3539\n",
+       "2      1656.188884   Store_1      60750352.02    4436\n",
+       "3      1783.006047   Store_1      60750602.00     231\n",
+       "4      1790.950612   Store_1      60750478.00    7787\n",
+       "...            ...       ...              ...     ...\n",
+       "3275  19643.307257  Store_19      60816023.00    3204\n",
+       "3276  20245.369594  Store_19      60816029.00    4135\n",
+       "3277  20290.986235  Store_19      60816026.00    7887\n",
+       "3278  20875.680521  Store_19      60816025.00    5146\n",
+       "3279  20958.530406  Store_19      60816024.00    6511\n",
+       "\n",
+       "[3280 rows x 4 columns]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "display(network_distance)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Display demand points dataframe"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 177,
+   "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>OBJECTID</th>\n",
+       "      <th>ID</th>\n",
+       "      <th>NAME</th>\n",
+       "      <th>STATE_NAME</th>\n",
+       "      <th>AREA</th>\n",
+       "      <th>POP2000</th>\n",
+       "      <th>HOUSEHOLDS</th>\n",
+       "      <th>HSE_UNITS</th>\n",
+       "      <th>BUS_COUNT</th>\n",
+       "      <th>long</th>\n",
+       "      <th>lat</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>6081602900</td>\n",
+       "      <td>60816029.00</td>\n",
+       "      <td>California</td>\n",
+       "      <td>0.48627</td>\n",
+       "      <td>4135</td>\n",
+       "      <td>1679</td>\n",
+       "      <td>1715</td>\n",
+       "      <td>112</td>\n",
+       "      <td>-122.488653</td>\n",
+       "      <td>37.650807</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2</td>\n",
+       "      <td>6081602800</td>\n",
+       "      <td>60816028.00</td>\n",
+       "      <td>California</td>\n",
+       "      <td>0.47478</td>\n",
+       "      <td>4831</td>\n",
+       "      <td>1484</td>\n",
+       "      <td>1506</td>\n",
+       "      <td>59</td>\n",
+       "      <td>-122.483550</td>\n",
+       "      <td>37.659998</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>3</td>\n",
+       "      <td>6081601700</td>\n",
+       "      <td>60816017.00</td>\n",
+       "      <td>California</td>\n",
+       "      <td>0.46393</td>\n",
+       "      <td>4155</td>\n",
+       "      <td>1294</td>\n",
+       "      <td>1313</td>\n",
+       "      <td>55</td>\n",
+       "      <td>-122.456484</td>\n",
+       "      <td>37.663272</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>4</td>\n",
+       "      <td>6081601900</td>\n",
+       "      <td>60816019.00</td>\n",
+       "      <td>California</td>\n",
+       "      <td>0.81907</td>\n",
+       "      <td>9041</td>\n",
+       "      <td>3273</td>\n",
+       "      <td>3330</td>\n",
+       "      <td>118</td>\n",
+       "      <td>-122.434247</td>\n",
+       "      <td>37.662385</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>5</td>\n",
+       "      <td>6081602500</td>\n",
+       "      <td>60816025.00</td>\n",
+       "      <td>California</td>\n",
+       "      <td>0.46603</td>\n",
+       "      <td>5146</td>\n",
+       "      <td>1459</td>\n",
+       "      <td>1467</td>\n",
+       "      <td>44</td>\n",
+       "      <td>-122.451187</td>\n",
+       "      <td>37.640219</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>201</th>\n",
+       "      <td>204</td>\n",
+       "      <td>6075011100</td>\n",
+       "      <td>60750111.00</td>\n",
+       "      <td>California</td>\n",
+       "      <td>0.09466</td>\n",
+       "      <td>5559</td>\n",
+       "      <td>2930</td>\n",
+       "      <td>3037</td>\n",
+       "      <td>362</td>\n",
+       "      <td>-122.418479</td>\n",
+       "      <td>37.791082</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>202</th>\n",
+       "      <td>205</td>\n",
+       "      <td>6075012200</td>\n",
+       "      <td>60750122.00</td>\n",
+       "      <td>California</td>\n",
+       "      <td>0.07211</td>\n",
+       "      <td>7035</td>\n",
+       "      <td>3862</td>\n",
+       "      <td>4074</td>\n",
+       "      <td>272</td>\n",
+       "      <td>-122.417237</td>\n",
+       "      <td>37.785728</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>203</th>\n",
+       "      <td>206</td>\n",
+       "      <td>6075017601</td>\n",
+       "      <td>60750176.01</td>\n",
+       "      <td>California</td>\n",
+       "      <td>0.24306</td>\n",
+       "      <td>5756</td>\n",
+       "      <td>2437</td>\n",
+       "      <td>2556</td>\n",
+       "      <td>943</td>\n",
+       "      <td>-122.410115</td>\n",
+       "      <td>37.779459</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>204</th>\n",
+       "      <td>207</td>\n",
+       "      <td>6075017800</td>\n",
+       "      <td>60750178.00</td>\n",
+       "      <td>California</td>\n",
+       "      <td>0.27882</td>\n",
+       "      <td>5829</td>\n",
+       "      <td>3115</td>\n",
+       "      <td>3231</td>\n",
+       "      <td>807</td>\n",
+       "      <td>-122.405411</td>\n",
+       "      <td>37.778934</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>205</th>\n",
+       "      <td>208</td>\n",
+       "      <td>6075012400</td>\n",
+       "      <td>60750124.00</td>\n",
+       "      <td>California</td>\n",
+       "      <td>0.17496</td>\n",
+       "      <td>8188</td>\n",
+       "      <td>4328</td>\n",
+       "      <td>4609</td>\n",
+       "      <td>549</td>\n",
+       "      <td>-122.416455</td>\n",
+       "      <td>37.782289</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>205 rows × 11 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     OBJECTID          ID         NAME  STATE_NAME     AREA  POP2000  \\\n",
+       "1           1  6081602900  60816029.00  California  0.48627     4135   \n",
+       "2           2  6081602800  60816028.00  California  0.47478     4831   \n",
+       "3           3  6081601700  60816017.00  California  0.46393     4155   \n",
+       "4           4  6081601900  60816019.00  California  0.81907     9041   \n",
+       "5           5  6081602500  60816025.00  California  0.46603     5146   \n",
+       "..        ...         ...          ...         ...      ...      ...   \n",
+       "201       204  6075011100  60750111.00  California  0.09466     5559   \n",
+       "202       205  6075012200  60750122.00  California  0.07211     7035   \n",
+       "203       206  6075017601  60750176.01  California  0.24306     5756   \n",
+       "204       207  6075017800  60750178.00  California  0.27882     5829   \n",
+       "205       208  6075012400  60750124.00  California  0.17496     8188   \n",
+       "\n",
+       "     HOUSEHOLDS  HSE_UNITS  BUS_COUNT        long        lat  \n",
+       "1          1679       1715        112 -122.488653  37.650807  \n",
+       "2          1484       1506         59 -122.483550  37.659998  \n",
+       "3          1294       1313         55 -122.456484  37.663272  \n",
+       "4          3273       3330        118 -122.434247  37.662385  \n",
+       "5          1459       1467         44 -122.451187  37.640219  \n",
+       "..          ...        ...        ...         ...        ...  \n",
+       "201        2930       3037        362 -122.418479  37.791082  \n",
+       "202        3862       4074        272 -122.417237  37.785728  \n",
+       "203        2437       2556        943 -122.410115  37.779459  \n",
+       "204        3115       3231        807 -122.405411  37.778934  \n",
+       "205        4328       4609        549 -122.416455  37.782289  \n",
+       "\n",
+       "[205 rows x 11 columns]"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "display(demand_points)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Display facility_points dataframe"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 178,
+   "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>OBJECTID</th>\n",
+       "      <th>NAME</th>\n",
+       "      <th>long</th>\n",
+       "      <th>lat</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>Store_1</td>\n",
+       "      <td>-122.510018</td>\n",
+       "      <td>37.772364</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2</td>\n",
+       "      <td>Store_2</td>\n",
+       "      <td>-122.488873</td>\n",
+       "      <td>37.753764</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>3</td>\n",
+       "      <td>Store_3</td>\n",
+       "      <td>-122.464927</td>\n",
+       "      <td>37.774727</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>4</td>\n",
+       "      <td>Store_4</td>\n",
+       "      <td>-122.473945</td>\n",
+       "      <td>37.743164</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>5</td>\n",
+       "      <td>Store_5</td>\n",
+       "      <td>-122.449291</td>\n",
+       "      <td>37.731545</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>6</td>\n",
+       "      <td>Store_6</td>\n",
+       "      <td>-122.491745</td>\n",
+       "      <td>37.649309</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>7</td>\n",
+       "      <td>Store_7</td>\n",
+       "      <td>-122.483182</td>\n",
+       "      <td>37.701109</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>8</td>\n",
+       "      <td>Store_11</td>\n",
+       "      <td>-122.433782</td>\n",
+       "      <td>37.655364</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>9</td>\n",
+       "      <td>Store_12</td>\n",
+       "      <td>-122.438982</td>\n",
+       "      <td>37.719236</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>10</td>\n",
+       "      <td>Store_13</td>\n",
+       "      <td>-122.440218</td>\n",
+       "      <td>37.745382</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>11</td>\n",
+       "      <td>Store_14</td>\n",
+       "      <td>-122.421636</td>\n",
+       "      <td>37.742964</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>12</td>\n",
+       "      <td>Store_15</td>\n",
+       "      <td>-122.430982</td>\n",
+       "      <td>37.782964</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>13</td>\n",
+       "      <td>Store_16</td>\n",
+       "      <td>-122.426873</td>\n",
+       "      <td>37.769291</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>14</td>\n",
+       "      <td>Store_17</td>\n",
+       "      <td>-122.432345</td>\n",
+       "      <td>37.805218</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>15</td>\n",
+       "      <td>Store_18</td>\n",
+       "      <td>-122.412818</td>\n",
+       "      <td>37.805745</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>16</td>\n",
+       "      <td>Store_19</td>\n",
+       "      <td>-122.398909</td>\n",
+       "      <td>37.797073</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "    OBJECTID      NAME        long        lat\n",
+       "1          1   Store_1 -122.510018  37.772364\n",
+       "2          2   Store_2 -122.488873  37.753764\n",
+       "3          3   Store_3 -122.464927  37.774727\n",
+       "4          4   Store_4 -122.473945  37.743164\n",
+       "5          5   Store_5 -122.449291  37.731545\n",
+       "6          6   Store_6 -122.491745  37.649309\n",
+       "7          7   Store_7 -122.483182  37.701109\n",
+       "8          8  Store_11 -122.433782  37.655364\n",
+       "9          9  Store_12 -122.438982  37.719236\n",
+       "10        10  Store_13 -122.440218  37.745382\n",
+       "11        11  Store_14 -122.421636  37.742964\n",
+       "12        12  Store_15 -122.430982  37.782964\n",
+       "13        13  Store_16 -122.426873  37.769291\n",
+       "14        14  Store_17 -122.432345  37.805218\n",
+       "15        15  Store_18 -122.412818  37.805745\n",
+       "16        16  Store_19 -122.398909  37.797073"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "display(facility_points)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Plot tract"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 179,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7fe4e65ffaf0>"
+      ]
+     },
+     "execution_count": 179,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "study_area.plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To start modeling the problem assuming the arguments expected by `spopt.locate`, we should pass a numpy 2D array as a cost_matrix. So, first we pivot the network_distance dataframe. \n",
+    "\n",
+    "_Note that the columns and rows are in alphabetical order._"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 180,
+   "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>name</th>\n",
+       "      <th>Store_1</th>\n",
+       "      <th>Store_11</th>\n",
+       "      <th>Store_12</th>\n",
+       "      <th>Store_13</th>\n",
+       "      <th>Store_14</th>\n",
+       "      <th>Store_15</th>\n",
+       "      <th>Store_16</th>\n",
+       "      <th>Store_17</th>\n",
+       "      <th>Store_18</th>\n",
+       "      <th>Store_19</th>\n",
+       "      <th>Store_2</th>\n",
+       "      <th>Store_3</th>\n",
+       "      <th>Store_4</th>\n",
+       "      <th>Store_5</th>\n",
+       "      <th>Store_6</th>\n",
+       "      <th>Store_7</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>DestinationName</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>60750101.0</th>\n",
+       "      <td>11495.190454</td>\n",
+       "      <td>20022.666503</td>\n",
+       "      <td>10654.593733</td>\n",
+       "      <td>8232.543149</td>\n",
+       "      <td>7561.399789</td>\n",
+       "      <td>4139.772198</td>\n",
+       "      <td>4805.805279</td>\n",
+       "      <td>2055.530234</td>\n",
+       "      <td>225.609240</td>\n",
+       "      <td>1757.623456</td>\n",
+       "      <td>11522.519829</td>\n",
+       "      <td>7529.985950</td>\n",
+       "      <td>10847.234951</td>\n",
+       "      <td>10604.729605</td>\n",
+       "      <td>20970.277793</td>\n",
+       "      <td>15242.989416</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>60750102.0</th>\n",
+       "      <td>10436.169910</td>\n",
+       "      <td>19392.094770</td>\n",
+       "      <td>10024.022001</td>\n",
+       "      <td>7601.971416</td>\n",
+       "      <td>6930.828057</td>\n",
+       "      <td>3093.851654</td>\n",
+       "      <td>4175.233547</td>\n",
+       "      <td>1257.809690</td>\n",
+       "      <td>1041.911304</td>\n",
+       "      <td>2333.244000</td>\n",
+       "      <td>10509.099285</td>\n",
+       "      <td>6470.965406</td>\n",
+       "      <td>10216.663219</td>\n",
+       "      <td>9974.157873</td>\n",
+       "      <td>20339.706061</td>\n",
+       "      <td>14612.417684</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>60750103.0</th>\n",
+       "      <td>10746.296811</td>\n",
+       "      <td>19404.672860</td>\n",
+       "      <td>10036.600090</td>\n",
+       "      <td>7614.549505</td>\n",
+       "      <td>6943.406146</td>\n",
+       "      <td>3381.778555</td>\n",
+       "      <td>4187.811636</td>\n",
+       "      <td>2046.436590</td>\n",
+       "      <td>744.584403</td>\n",
+       "      <td>1685.517099</td>\n",
+       "      <td>10800.926186</td>\n",
+       "      <td>6778.892307</td>\n",
+       "      <td>10229.241308</td>\n",
+       "      <td>9986.735962</td>\n",
+       "      <td>20352.284150</td>\n",
+       "      <td>14624.995773</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>60750104.0</th>\n",
+       "      <td>11420.492134</td>\n",
+       "      <td>19808.368182</td>\n",
+       "      <td>10440.295413</td>\n",
+       "      <td>8018.244828</td>\n",
+       "      <td>7347.101469</td>\n",
+       "      <td>4044.473877</td>\n",
+       "      <td>4591.506959</td>\n",
+       "      <td>2463.736278</td>\n",
+       "      <td>795.715285</td>\n",
+       "      <td>1282.217412</td>\n",
+       "      <td>11308.221508</td>\n",
+       "      <td>7447.187630</td>\n",
+       "      <td>10632.936630</td>\n",
+       "      <td>10390.431285</td>\n",
+       "      <td>20755.979472</td>\n",
+       "      <td>15028.691095</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>60750105.0</th>\n",
+       "      <td>11379.443952</td>\n",
+       "      <td>19583.920000</td>\n",
+       "      <td>10215.847231</td>\n",
+       "      <td>7793.796646</td>\n",
+       "      <td>7122.653287</td>\n",
+       "      <td>4103.725695</td>\n",
+       "      <td>4367.058776</td>\n",
+       "      <td>3320.283731</td>\n",
+       "      <td>1731.462738</td>\n",
+       "      <td>249.669959</td>\n",
+       "      <td>11083.773326</td>\n",
+       "      <td>7379.539448</td>\n",
+       "      <td>10408.488448</td>\n",
+       "      <td>10165.983103</td>\n",
+       "      <td>20531.531290</td>\n",
+       "      <td>14804.242913</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>...</th>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "      <td>...</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>60816025.0</th>\n",
+       "      <td>17324.066610</td>\n",
+       "      <td>2722.031291</td>\n",
+       "      <td>10884.063331</td>\n",
+       "      <td>14178.007937</td>\n",
+       "      <td>13891.857275</td>\n",
+       "      <td>18418.384867</td>\n",
+       "      <td>16726.951785</td>\n",
+       "      <td>20834.395022</td>\n",
+       "      <td>21441.247824</td>\n",
+       "      <td>20875.680521</td>\n",
+       "      <td>14662.484617</td>\n",
+       "      <td>16569.371114</td>\n",
+       "      <td>12483.322114</td>\n",
+       "      <td>11926.727459</td>\n",
+       "      <td>4968.842581</td>\n",
+       "      <td>8648.054204</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>60816026.0</th>\n",
+       "      <td>15981.172325</td>\n",
+       "      <td>3647.137006</td>\n",
+       "      <td>10299.369046</td>\n",
+       "      <td>13593.313651</td>\n",
+       "      <td>13307.162990</td>\n",
+       "      <td>17833.690581</td>\n",
+       "      <td>16142.257500</td>\n",
+       "      <td>20249.700736</td>\n",
+       "      <td>20856.553539</td>\n",
+       "      <td>20290.986235</td>\n",
+       "      <td>14050.290332</td>\n",
+       "      <td>15963.776829</td>\n",
+       "      <td>11871.527828</td>\n",
+       "      <td>11342.033174</td>\n",
+       "      <td>3625.948296</td>\n",
+       "      <td>7919.659919</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>60816027.0</th>\n",
+       "      <td>14835.342712</td>\n",
+       "      <td>4581.333336</td>\n",
+       "      <td>9637.139433</td>\n",
+       "      <td>12931.084039</td>\n",
+       "      <td>12644.933377</td>\n",
+       "      <td>17171.460969</td>\n",
+       "      <td>15480.027887</td>\n",
+       "      <td>19587.471124</td>\n",
+       "      <td>20194.323926</td>\n",
+       "      <td>19628.756623</td>\n",
+       "      <td>13341.313338</td>\n",
+       "      <td>15301.547216</td>\n",
+       "      <td>11209.298215</td>\n",
+       "      <td>10679.803561</td>\n",
+       "      <td>2290.818683</td>\n",
+       "      <td>7242.830306</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>60816028.0</th>\n",
+       "      <td>13339.491691</td>\n",
+       "      <td>6392.856372</td>\n",
+       "      <td>8577.488412</td>\n",
+       "      <td>11871.433018</td>\n",
+       "      <td>11585.282356</td>\n",
+       "      <td>16111.809948</td>\n",
+       "      <td>14420.376867</td>\n",
+       "      <td>18527.820103</td>\n",
+       "      <td>19134.672905</td>\n",
+       "      <td>18569.105602</td>\n",
+       "      <td>11845.462317</td>\n",
+       "      <td>14241.196195</td>\n",
+       "      <td>10155.147195</td>\n",
+       "      <td>9620.152540</td>\n",
+       "      <td>1846.795647</td>\n",
+       "      <td>5746.979285</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>60816029.0</th>\n",
+       "      <td>15257.855684</td>\n",
+       "      <td>6394.920365</td>\n",
+       "      <td>10253.752405</td>\n",
+       "      <td>13547.697010</td>\n",
+       "      <td>13261.546349</td>\n",
+       "      <td>17788.073940</td>\n",
+       "      <td>16096.640859</td>\n",
+       "      <td>20204.084095</td>\n",
+       "      <td>20810.936898</td>\n",
+       "      <td>20245.369594</td>\n",
+       "      <td>13763.826309</td>\n",
+       "      <td>15918.160188</td>\n",
+       "      <td>11825.911187</td>\n",
+       "      <td>11296.416533</td>\n",
+       "      <td>508.931655</td>\n",
+       "      <td>7665.343278</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "<p>205 rows × 16 columns</p>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "name                  Store_1      Store_11      Store_12      Store_13  \\\n",
+       "DestinationName                                                           \n",
+       "60750101.0       11495.190454  20022.666503  10654.593733   8232.543149   \n",
+       "60750102.0       10436.169910  19392.094770  10024.022001   7601.971416   \n",
+       "60750103.0       10746.296811  19404.672860  10036.600090   7614.549505   \n",
+       "60750104.0       11420.492134  19808.368182  10440.295413   8018.244828   \n",
+       "60750105.0       11379.443952  19583.920000  10215.847231   7793.796646   \n",
+       "...                       ...           ...           ...           ...   \n",
+       "60816025.0       17324.066610   2722.031291  10884.063331  14178.007937   \n",
+       "60816026.0       15981.172325   3647.137006  10299.369046  13593.313651   \n",
+       "60816027.0       14835.342712   4581.333336   9637.139433  12931.084039   \n",
+       "60816028.0       13339.491691   6392.856372   8577.488412  11871.433018   \n",
+       "60816029.0       15257.855684   6394.920365  10253.752405  13547.697010   \n",
+       "\n",
+       "name                 Store_14      Store_15      Store_16      Store_17  \\\n",
+       "DestinationName                                                           \n",
+       "60750101.0        7561.399789   4139.772198   4805.805279   2055.530234   \n",
+       "60750102.0        6930.828057   3093.851654   4175.233547   1257.809690   \n",
+       "60750103.0        6943.406146   3381.778555   4187.811636   2046.436590   \n",
+       "60750104.0        7347.101469   4044.473877   4591.506959   2463.736278   \n",
+       "60750105.0        7122.653287   4103.725695   4367.058776   3320.283731   \n",
+       "...                       ...           ...           ...           ...   \n",
+       "60816025.0       13891.857275  18418.384867  16726.951785  20834.395022   \n",
+       "60816026.0       13307.162990  17833.690581  16142.257500  20249.700736   \n",
+       "60816027.0       12644.933377  17171.460969  15480.027887  19587.471124   \n",
+       "60816028.0       11585.282356  16111.809948  14420.376867  18527.820103   \n",
+       "60816029.0       13261.546349  17788.073940  16096.640859  20204.084095   \n",
+       "\n",
+       "name                 Store_18      Store_19       Store_2       Store_3  \\\n",
+       "DestinationName                                                           \n",
+       "60750101.0         225.609240   1757.623456  11522.519829   7529.985950   \n",
+       "60750102.0        1041.911304   2333.244000  10509.099285   6470.965406   \n",
+       "60750103.0         744.584403   1685.517099  10800.926186   6778.892307   \n",
+       "60750104.0         795.715285   1282.217412  11308.221508   7447.187630   \n",
+       "60750105.0        1731.462738    249.669959  11083.773326   7379.539448   \n",
+       "...                       ...           ...           ...           ...   \n",
+       "60816025.0       21441.247824  20875.680521  14662.484617  16569.371114   \n",
+       "60816026.0       20856.553539  20290.986235  14050.290332  15963.776829   \n",
+       "60816027.0       20194.323926  19628.756623  13341.313338  15301.547216   \n",
+       "60816028.0       19134.672905  18569.105602  11845.462317  14241.196195   \n",
+       "60816029.0       20810.936898  20245.369594  13763.826309  15918.160188   \n",
+       "\n",
+       "name                  Store_4       Store_5       Store_6       Store_7  \n",
+       "DestinationName                                                          \n",
+       "60750101.0       10847.234951  10604.729605  20970.277793  15242.989416  \n",
+       "60750102.0       10216.663219   9974.157873  20339.706061  14612.417684  \n",
+       "60750103.0       10229.241308   9986.735962  20352.284150  14624.995773  \n",
+       "60750104.0       10632.936630  10390.431285  20755.979472  15028.691095  \n",
+       "60750105.0       10408.488448  10165.983103  20531.531290  14804.242913  \n",
+       "...                       ...           ...           ...           ...  \n",
+       "60816025.0       12483.322114  11926.727459   4968.842581   8648.054204  \n",
+       "60816026.0       11871.527828  11342.033174   3625.948296   7919.659919  \n",
+       "60816027.0       11209.298215  10679.803561   2290.818683   7242.830306  \n",
+       "60816028.0       10155.147195   9620.152540   1846.795647   5746.979285  \n",
+       "60816029.0       11825.911187  11296.416533    508.931655   7665.343278  \n",
+       "\n",
+       "[205 rows x 16 columns]"
+      ]
+     },
+     "execution_count": 180,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ntw_dist_piv = network_distance.pivot_table(values=\"distance\", index=\"DestinationName\", columns=\"name\")\n",
+    "ntw_dist_piv"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Here the pivot table is transformed to numpy 2D array such as `spopt.locate` expected. The matrix has a shape of 205x16."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 181,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[11495.19045438, 20022.66650296, 10654.59373325, ...,\n",
+       "        10604.72960533, 20970.27779306, 15242.98941606],\n",
+       "       [10436.16991032, 19392.09477041, 10024.0220007 , ...,\n",
+       "         9974.15787278, 20339.70606051, 14612.41768351],\n",
+       "       [10746.29681106, 19404.67285964, 10036.60008993, ...,\n",
+       "         9986.73596201, 20352.28414974, 14624.99577275],\n",
+       "       ...,\n",
+       "       [14835.34271218,  4581.3333364 ,  9637.13943331, ...,\n",
+       "        10679.80356124,  2290.81868301,  7242.83030602],\n",
+       "       [13339.49169134,  6392.85637207,  8577.48841247, ...,\n",
+       "         9620.15254039,  1846.79564734,  5746.97928517],\n",
+       "       [15257.85568393,  6394.92036466, 10253.75240505, ...,\n",
+       "        11296.41653298,   508.93165475,  7665.34327776]])"
+      ]
+     },
+     "execution_count": 181,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cost_matrix = ntw_dist_piv.to_numpy()\n",
+    "cost_matrix"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Now, as the rows and columns of our cost_matrix are sorted, so we have to sort our facility points and demand points geodataframes too. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 182,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "facility_points_gdf = geopandas.GeoDataFrame(\n",
+    "    facility_points,\n",
+    "    geometry=geopandas.points_from_xy(\n",
+    "        facility_points.long, facility_points.lat\n",
+    "    ),\n",
+    ").sort_values(by=['NAME']).reset_index()\n",
+    "\n",
+    "demand_points_gdf = geopandas.GeoDataFrame(\n",
+    "    demand_points,\n",
+    "    geometry=geopandas.points_from_xy(demand_points.long, demand_points.lat),\n",
+    ").sort_values(by=['NAME']).reset_index()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Set parameter service_dist for maximum service standard of distance or time."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 183,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "service_dist = 8000"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Below, the method is used to plot the results of the four models that we will prepare to solve the problem."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 184,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from matplotlib.patches import Patch\n",
+    "import matplotlib.lines as mlines\n",
+    "from matplotlib_scalebar.scalebar import ScaleBar\n",
+    "\n",
+    "dv_colors = [\n",
+    "    \"saddlebrown\",\n",
+    "    \"darkgoldenrod\",\n",
+    "    \"mediumseagreen\",\n",
+    "    \"lightskyblue\",\n",
+    "    \"lavender\",\n",
+    "    \"darkslategray\",\n",
+    "    \"coral\",\n",
+    "    \"mediumvioletred\",\n",
+    "    \"darkcyan\",\n",
+    "    \"cyan\",\n",
+    "    \"limegreen\",\n",
+    "    \"peachpuff\",\n",
+    "    \"blueviolet\",\n",
+    "    \"fuchsia\",\n",
+    "    \"thistle\",\n",
+    "]\n",
+    "\n",
+    "def plot_results(model, facility_points_gdf, demand_points_gdf, facility_count, title, p):\n",
+    "    \n",
+    "    arr_points = [] \n",
+    "    fac_sites = [] \n",
+    "    \n",
+    "    for i in range(facility_count):\n",
+    "        if model.fac2cli[i]:\n",
+    "            geom = demand_points_gdf.iloc[model.fac2cli[i]][\"geometry\"]\n",
+    "            arr_points.append(geom)\n",
+    "            fac_sites.append(i)\n",
+    "\n",
+    "    \n",
+    "    fig, ax = plt.subplots(figsize=(10, 15))\n",
+    "    legend_elements = []\n",
+    "\n",
+    "    study_area.plot(ax=ax, alpha=.5, fc=\"tan\", ec=\"k\", zorder=1)\n",
+    "    _patch = Patch(alpha=.5, fc=\"tan\", ec=\"k\", label=\"Dissolved Service Areas\")\n",
+    "    legend_elements.append(_patch)\n",
+    "    \n",
+    "    demand_points_gdf.plot(\n",
+    "        ax=ax, fc=\"k\", ec=\"k\", marker=\"s\", markersize=7, zorder=2, lw=.5 \n",
+    "    )\n",
+    "\n",
+    "    facility_points_gdf.plot(\n",
+    "        ax=ax, fc=\"brown\", marker=\"*\", markersize=80, zorder=8\n",
+    "    )\n",
+    "    legend_elements.append(\n",
+    "        mlines.Line2D(\n",
+    "            [],\n",
+    "            [],\n",
+    "            marker=\"*\",\n",
+    "            markerfacecolor=\"brown\",\n",
+    "            markeredgecolor=\"brown\",\n",
+    "            markeredgewidth=.5, \n",
+    "            ms=20,\n",
+    "            lw=0,\n",
+    "            label=f\"Unselected Candidate Store sites ($n$={facility_count})\"\n",
+    "        )\n",
+    "    )\n",
+    "\n",
+    "    _zo, _ms = 4, 4\n",
+    "    \n",
+    "    for i in range(len(arr_points)):\n",
+    "\n",
+    "        cset = dv_colors[i]\n",
+    "        fac = fac_sites[i] \n",
+    "        fname = facility_points_gdf.iloc[[fac]][\"NAME\"]\n",
+    "        fname = f\"{fname.squeeze().replace('_', ' ')}\"\n",
+    "        \n",
+    "        gdf = geopandas.GeoDataFrame(arr_points[i])\n",
+    "        \n",
+    "        label = f\"Demand sites covered by {fname}\"\n",
+    "        gdf.plot(ax=ax, zorder=_zo, ec=\"k\", fc=cset, markersize=100*_ms, lw=.5,) \n",
+    "        legend_elements.append(\n",
+    "            mlines.Line2D(\n",
+    "                [],\n",
+    "                [],\n",
+    "                marker=\"o\",\n",
+    "                markerfacecolor=cset,\n",
+    "                markeredgecolor=\"k\",\n",
+    "                markeredgewidth=.5, \n",
+    "                ms= _ms + 7,\n",
+    "                lw=0,\n",
+    "                label=label\n",
+    "            )\n",
+    "        )\n",
+    "        \n",
+    "        facility_points_gdf.iloc[[fac]].plot(\n",
+    "            ax=ax, marker=\"*\", markersize=1000, zorder=9, fc=cset, ec=\"k\", lw=.5\n",
+    "        )\n",
+    "        legend_elements.append(\n",
+    "            mlines.Line2D(\n",
+    "                [],\n",
+    "                [],\n",
+    "                marker=\"*\",\n",
+    "                markerfacecolor=cset,\n",
+    "                markeredgecolor=\"k\",\n",
+    "                markeredgewidth=.5,\n",
+    "                ms=20,\n",
+    "                lw=0,\n",
+    "                label=fname,\n",
+    "            )\n",
+    "        )\n",
+    "        \n",
+    "        _zo += 1\n",
+    "        _ms -= (1)*(4/p)\n",
+    "     \n",
+    "    plt.title(title, fontsize=20)\n",
+    "    kws = dict(loc=\"upper left\", bbox_to_anchor=(1.05, .7), fontsize=15)\n",
+    "    plt.legend(handles=legend_elements, **kws)\n",
+    "    \n",
+    "    x, y, xyc, arrow_length, c = 0.925, 0.15, \"axes fraction\", 0.1 , \"center\"\n",
+    "    xy, xyt = (x, y), (x, y-arrow_length)\n",
+    "    ap = dict(facecolor=\"black\", width=5, headwidth=10)\n",
+    "    kws = dict(arrowprops=ap, ha=c, va=c, fontsize=20)\n",
+    "    plt.annotate(\"N\", xy=xy, xycoords=xyc, xytext=xyt, **kws)\n",
+    "    \n",
+    "    plt.gca().add_artist(ScaleBar(1))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 185,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for _df in [facility_points_gdf, demand_points_gdf, study_area]:\n",
+    "    _df.set_crs(\"EPSG:4326\", inplace=True)\n",
+    "    _df.to_crs(\"EPSG:7131\", inplace=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## LSCP-B"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 186,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from spopt.locate.coverage import LSCPB"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 187,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "start_1 = time.time()\n",
+    "lscpb = LSCPB.from_cost_matrix(cost_matrix, service_dist, pulp.PULP_CBC_CMD(msg=False))\n",
+    "end_1 = time.time()\n",
+    "\n",
+    "time_spent_1 = end_1 - start_1"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 188,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "start_2 = time.time()\n",
+    "lscpb = lscpb.solve(pulp.PULP_CBC_CMD(msg=False)) \n",
+    "end_2 = time.time()\n",
+    "\n",
+    "time_spent_2 = end_2 - start_2\n",
+    "total_time = time_spent_1 + time_spent_2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 189,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 720x1080 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_results(lscpb, facility_points_gdf, demand_points_gdf, facility_points_gdf.shape[0], \"LSCP-B\", lscpb.lscp_obj_value)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## LSCPB San Francisco Case Study Results"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 190,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "San Francisco Dataset \n",
+      "Demand Nodes: 205   Candidate Facilities: 16    Facilities Needed: 3.0   Computation Time: 0.3546009063720703\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(f\"San Francisco Dataset \\nDemand Nodes: 205   Candidate Facilities: 16    Facilities Needed: {lscpb.lscp_obj_value}   Computation Time: {total_time}\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "interpreter": {
+   "hash": "56b72aab97c5d88c22a6bf5872989e2e65e9296dc12395fbfb8350007c775deb"
+  },
+  "kernelspec": {
+   "display_name": "Python 3.8.13 ('geo_env')",
+   "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": "3.8.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/notebooks/lscp.ipynb b/notebooks/lscp.ipynb
index 858e27ac..bc976fe3 100644
--- a/notebooks/lscp.ipynb
+++ b/notebooks/lscp.ipynb
@@ -906,10 +906,10 @@
  ],
  "metadata": {
   "interpreter": {
-   "hash": "31b88bb145573cdebdaa7fd72fef7949ecb3dda26d5e10d4ccc660a5d07787a7"
+   "hash": "56b72aab97c5d88c22a6bf5872989e2e65e9296dc12395fbfb8350007c775deb"
   },
   "kernelspec": {
-   "display_name": "Python 3.9.9 ('spopt')",
+   "display_name": "Python 3.8.13 ('geo_env')",
    "language": "python",
    "name": "python3"
   },
@@ -923,7 +923,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.9"
+   "version": "3.8.13"
   }
  },
  "nbformat": 4,
diff --git a/notebooks/lscpb.ipynb b/notebooks/lscpb.ipynb
new file mode 100644
index 00000000..73b07a7d
--- /dev/null
+++ b/notebooks/lscpb.ipynb
@@ -0,0 +1,1098 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {
+    "jupyter": {
+     "outputs_hidden": true
+    }
+   },
+   "source": [
+    "# Backup Coverage Location Set Covering Problem (LSCP-B)\n",
+    "\n",
+    "*Authors:* [Erin Olson](https://github.com/erinrolson), [Germano Barcelos](https://github.com/gegen07), [James Gaboardi](https://github.com/jGaboardi), [Levi J. Wolf](https://github.com/ljwolf), [Qunshan Zhao](https://github.com/qszhao)\n",
+    "\n",
+    "The Backup coverage problem is refered to as an extension of the LSCP (location set covering problem) as it seeks a solution to LSCP while selecting a set of facilities that optimizes for backup coverage (Church L., Murray, A. (2018)). If you are unfamiliar with LSCP the following [notebook](https://pysal.org/spopt/notebooks/lscp.html) explains the problem formulation in detail.\n",
+    "\n",
+    "Daskin and Stern (1981) posed the following problem which Church L., Murray, A. (2018) refers to as LSCP-B (location set covering problem with backup):\n",
+    "\n",
+    "_Find the minimum number of facilities and their locations such that each demand is covered, while maximizing the number of backup coverage instances among demand areas._ Church L., Murray, A. (2018)\n",
+    "\n",
+    "**LSCP-B can be written as:**\n",
+    "\n",
+    "\\begin{equation*}\n",
+    "\\textbf{Minimize }\\sum_{j} x_j\n",
+    "\\end{equation*}\n",
+    "\n",
+    "\\begin{equation*}\n",
+    "\\textbf{Maximize }\\sum_{i} q_i\n",
+    "\\end{equation*}\n",
+    "\n",
+    "_Subject to:_\n",
+    "\\begin{equation*}\n",
+    "\\sum_{j\\in N_i} x_j - q_i\\geq 1 \\quad \\forall i\n",
+    "\\end{equation*}\n",
+    "\n",
+    "\\begin{equation*}\n",
+    "x_j \\in \\{0,1\\} \\quad \\forall j\n",
+    "\\end{equation*}\n",
+    "\n",
+    "\\begin{equation*}\n",
+    "q_i \\geq 0 \\quad \\forall i\n",
+    "\\end{equation*}\n",
+    "\n",
+    "_Where:_\n",
+    "\n",
+    "\\begin{array}{lclll}\n",
+    "& & i & \\small = & \\textrm{index referencing nodes of the network as demand} \\\\\n",
+    "& & j & \\small = & \\textrm{index referencing nodes of the network as potential facility sites} \\\\\n",
+    "& & S & \\small = & \\textrm{maximal acceptable service distance or time standard} \\\\\n",
+    "& & d_{ij} & \\small = & \\textrm{shortest distance or travel time between nodes} \\quad i \\quad \\textrm{and} \\quad j \\\\\n",
+    "& & N_i & \\small = & \\{j | d_{ij} < S\\} \\\\\n",
+    "& & x_j & \\small = & \\begin{cases} \n",
+    "          1, \\quad \\text{if a facility is located at node} \\quad j\\\\\n",
+    "          0, \\quad \\text{otherwise} \\\\\n",
+    "       \\end{cases} \\end{array}\n",
+    "\n",
+    "\n",
+    "\n",
+    "\n",
+    "_The excerpt above was quoted from Church L., Murray, A. (2018)_\n",
+    "\n",
+    "\n",
+    "This tutorial solves for both LSCP and LSCP-B using `spopt.locate.coverage.LSCP` and `spopt.locate.coverage.LSCPB` instances that depend on a 2D array representing the costs between facilities candidate sites and demand points. Costs are calculated from a 10x10 lattice with simulated points."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/opt/anaconda3/envs/geo_env/lib/python3.8/site-packages/spaghetti/network.py:36: FutureWarning: The next major release of pysal/spaghetti (2.0.0) will drop support for all ``libpysal.cg`` geometries. This change is a first step in refactoring ``spaghetti`` that is expected to result in dramatically reduced runtimes for network instantiation and operations. Users currently requiring network and point pattern input as ``libpysal.cg`` geometries should prepare for this simply by converting to ``shapely`` geometries.\n",
+      "  warnings.warn(f\"{dep_msg}\", FutureWarning)\n"
+     ]
+    }
+   ],
+   "source": [
+    "from spopt.locate.coverage import LSCP, LSCPB\n",
+    "from spopt.locate.util import simulated_geo_points\n",
+    "\n",
+    "import numpy\n",
+    "import geopandas\n",
+    "import pulp\n",
+    "import spaghetti\n",
+    "from shapely.geometry import Point\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Since the model needs a distance cost matrix we start with defining our variables. In the comments, it's defined what these variables are for except for solver. The solver, assigned below as `pulp.PULP_CBC_CMD`, is an interface to optimization solver developed by [COIN-OR](https://github.com/coin-or/Cbc). If you want to use another optimization interface as Gurobi or CPLEX see this [guide](https://coin-or.github.io/pulp/guides/how_to_configure_solvers.html) that explains how to achieve this."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "CLIENT_COUNT = 100 # quantity demand points\n",
+    "FACILITY_COUNT = 5 # quantity supply points\n",
+    "\n",
+    "SERVICE_RADIUS = 8 # maximum service radius in meters\n",
+    "\n",
+    "# Random seeds for reproducibility\n",
+    "CLIENT_SEED = 5 \n",
+    "FACILITY_SEED = 6 \n",
+    "\n",
+    "solver = pulp.PULP_CBC_CMD(msg=False, warmStart=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Lattice 10x10"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Create a 10x10 lattice with 9 vertical lines in interior."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "lattice = spaghetti.regular_lattice((0, 0, 10, 10), 9, exterior=True)\n",
+    "ntw = spaghetti.Network(in_data=lattice)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Transform spaghetti instance into geodataframe."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "street = spaghetti.element_as_gdf(ntw, arcs=True)\n",
+    "\n",
+    "street_buffered = geopandas.GeoDataFrame(\n",
+    "    geopandas.GeoSeries(street[\"geometry\"].buffer(0.2).unary_union),\n",
+    "    crs=street.crs,\n",
+    "    columns=[\"geometry\"],\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Plotting the network created by spaghetti we can verify the simulation of a district with quarters and streets."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.axes._subplots.AxesSubplot at 0x7f892b1446d0>"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": "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",
+      "text/plain": [
+       "<Figure size 432x288 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "street.plot()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Simulate points in a network\n",
+    "\n",
+    "The function `simulated_geo_points` simulates points inside a network. In this case, it uses a lattice network 10x10 created using the spaghetti package. \n",
+    "Below we use the function defined above and simulate the points inside the lattice bounds."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "client_points = simulated_geo_points(street_buffered, needed=CLIENT_COUNT, seed=CLIENT_SEED)\n",
+    "facility_points = simulated_geo_points(\n",
+    "    street_buffered, needed=FACILITY_COUNT, seed=FACILITY_SEED\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Plotting the 100 client and 5 facility points we can see that the function generates dummy points to an area of 10x10 which is the area created by our lattice created on previous cells."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x7f892b22ba00>"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 432x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(figsize=(6, 6))\n",
+    "street.plot(ax=ax, alpha=0.8, zorder=1, label='streets')\n",
+    "facility_points.plot(ax=ax, color='red', zorder=2, label='facility candidate sites ($n$=5)')\n",
+    "client_points.plot(ax=ax, color='black', label='clients points ($n$=100)')\n",
+    "plt.legend(loc='upper left', bbox_to_anchor=(1.05, 1))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Transform simulated points to real points"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "To use a cost matrix or geodataframes we have to pay attention to certain details. The client and facility points simulated don't currently belong to a network, so if we calculate the network distances now we would receive an incorrect result. Before calculating distances we must snap points to the network and then calculate the distances."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Below we snap points to the lattice created above and create new real points geodataframes."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "ntw.snapobservations(client_points, \"clients\", attribute=True)\n",
+    "clients_snapped = spaghetti.element_as_gdf(\n",
+    "    ntw, pp_name=\"clients\", snapped=True\n",
+    ")\n",
+    "\n",
+    "ntw.snapobservations(facility_points, \"facilities\", attribute=True)\n",
+    "facilities_snapped = spaghetti.element_as_gdf(\n",
+    "    ntw, pp_name=\"facilities\", snapped=True\n",
+    ")\n"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The plot is now visually more organized as the points belong to a network. \n",
+    "The network created is plotted below with facility points and clients points:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<matplotlib.legend.Legend at 0x7f892b63e790>"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 432x432 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "fig, ax = plt.subplots(figsize=(6, 6))\n",
+    "street.plot(ax=ax, alpha=0.8, zorder=1, label='streets')\n",
+    "facilities_snapped.plot(ax=ax, color='red', zorder=2, label='facility candidate sites ($n$=5)')\n",
+    "clients_snapped.plot(ax=ax, color='black', label='clients points ($n$=100)')\n",
+    "plt.legend(loc='upper left', bbox_to_anchor=(1.05, 1))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Calculating the cost matrix "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Calculate distance between clients and facilities."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cost_matrix = ntw.allneighbordistances(\n",
+    "    sourcepattern=ntw.pointpatterns[\"clients\"],\n",
+    "    destpattern=ntw.pointpatterns[\"facilities\"],\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The expected result is a Dijkstra distance between clients and facilities points, so we our case an array 2D 100x5."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([[12.60302601,  3.93598651,  8.16571655,  6.04319467,  5.65607701],\n",
+       "       [13.10096347,  4.43392397,  8.66365401,  6.54113213,  5.15813955],\n",
+       "       [ 6.9095462 ,  4.2425067 ,  2.47223674,  0.34971486,  5.34955682],\n",
+       "       [ 2.98196832,  7.84581224,  3.45534114,  3.57786302,  6.25374871],\n",
+       "       [ 7.5002892 ,  6.32806975,  4.55779979,  6.43527791, 11.75939222],\n",
+       "       [ 0.60209077, 11.42987132,  5.03940023,  7.16192211,  9.8378078 ],\n",
+       "       [ 5.37335867,  6.20113923,  2.43086927,  4.30834738,  9.6324617 ],\n",
+       "       [ 5.40801577,  5.41976478,  3.02929369,  1.15181557,  4.85108725],\n",
+       "       [ 3.68807115,  8.51585171,  2.12538061,  4.24790249,  7.94717417],\n",
+       "       [14.22503627,  4.60274429,  9.78772681,  7.66520493,  4.98931924],\n",
+       "       [10.32521229,  4.99225179,  7.38272288,  9.260201  , 14.58431531],\n",
+       "       [ 6.65436171,  7.98732222,  5.59685112,  3.719373  ,  2.58135531],\n",
+       "       [11.55510375,  1.11193575,  7.11779429,  5.37988496, 10.70399927],\n",
+       "       [10.90832519,  1.75871431,  6.47101573,  6.02666352, 11.35077783],\n",
+       "       [ 9.29354019,  9.53424036,  7.14376926,  5.26629115,  0.05782317],\n",
+       "       [11.25279502,  3.57498553,  6.81548556,  4.69296368,  6.01707799],\n",
+       "       [ 6.14400601, 11.47696651,  9.08649542,  7.2090173 ,  3.09171102],\n",
+       "       [10.43008909,  2.23695041,  5.99277963,  6.50489962, 11.82901393],\n",
+       "       [ 1.79838406, 11.13134457,  4.74087347,  6.86339535,  9.53928104],\n",
+       "       [ 2.93052752,  7.89725303,  3.50678194,  3.62930382,  6.30518951],\n",
+       "       [11.55272282,  6.21976231,  8.61023341, 10.48771153, 15.81182584],\n",
+       "       [ 8.83964081,  3.66742137,  5.89715141,  7.77462952, 13.09874384],\n",
+       "       [ 4.11777697,  9.45073748,  7.06026638,  5.18278826,  7.11794005],\n",
+       "       [ 8.69768642,  8.63527408,  5.75519701,  7.63267513, 12.95678945],\n",
+       "       [ 8.2652832 ,  6.56249735,  4.79222739,  2.66970551,  3.02956617],\n",
+       "       [ 1.71437731,  9.6185832 ,  3.2281121 ,  5.35063398,  8.02651967],\n",
+       "       [ 4.30308213,  6.52469842,  2.13422733,  2.25674921,  5.95602089],\n",
+       "       [ 9.31612329,  8.64908379,  6.25861269,  4.38113458,  0.94297974],\n",
+       "       [ 2.86540683, 13.69318738,  7.30271629,  9.42523817, 12.10112386],\n",
+       "       [ 8.95995574,  2.29291624,  4.52264628,  6.4001244 , 11.72423871],\n",
+       "       [10.54288208,  7.87584258,  6.10557262,  3.98305074,  1.71622094],\n",
+       "       [ 8.58885878,  8.74410173,  5.64636937,  7.52384749, 12.8479618 ],\n",
+       "       [ 2.51163835, 12.82132215,  6.43085106,  8.55337294, 11.22925863],\n",
+       "       [ 5.19213144,  5.63564912,  0.75482198,  1.74285727,  7.06697159],\n",
+       "       [ 4.1276352 , 13.2053253 ,  6.81485421,  8.93737609, 11.61326178],\n",
+       "       [ 3.99217608,  6.83560448,  0.44513338,  2.94281263,  6.75645905],\n",
+       "       [ 5.88198594, 11.21494644,  8.82447535,  6.94699723,  5.35373109],\n",
+       "       [ 8.24225403,  4.58552653,  3.80494457,  1.68242269,  5.006537  ],\n",
+       "       [10.89255004,  6.22551054,  6.45524058,  4.3327187 ,  3.36655299],\n",
+       "       [ 6.58504851, 11.91800902,  9.52753792,  7.6500598 ,  2.65066851],\n",
+       "       [ 5.44204086,  8.77500136,  6.38453026,  4.50705215,  3.79367617],\n",
+       "       [ 5.56289993,  7.26488062,  4.87440953,  2.99693141,  3.6728171 ],\n",
+       "       [ 7.96716366, 10.86061689,  8.4701458 ,  6.59266768,  1.26855337],\n",
+       "       [ 7.9603294 ,  5.3726311 ,  5.01783999,  6.89531811, 12.21943243],\n",
+       "       [ 8.68198919,  4.65097132,  5.73949978,  7.6169779 , 12.94109221],\n",
+       "       [ 9.06064716,  8.39360767,  6.00313657,  4.12565845,  1.19845586],\n",
+       "       [15.325265  ,  4.65822551, 10.88795554,  8.76543366,  6.08954798],\n",
+       "       [ 3.51444772,  7.81851278,  1.95175718,  3.92572094,  7.77355074],\n",
+       "       [ 3.33469883, 14.16247938,  7.77200828,  9.89453017, 12.57041585],\n",
+       "       [ 4.46482284,  6.36295772,  1.40731225,  2.0950085 ,  5.79428018],\n",
+       "       [11.20742649,  1.459613  ,  6.77011704,  5.72756222, 11.05167653],\n",
+       "       [11.15442417,  5.67335639,  6.71711471,  4.59459283,  3.91870714],\n",
+       "       [ 5.17021584,  5.65756471,  0.73290638,  2.6103845 ,  7.93449881],\n",
+       "       [ 5.54400588, 10.87696639,  8.48649529,  6.60901717,  5.28490286],\n",
+       "       [ 5.28695668,  8.04600382,  2.34446727,  4.22194539,  9.5460597 ],\n",
+       "       [ 7.33259845,  6.66555896,  4.27508786,  2.39760974,  2.92650457],\n",
+       "       [ 8.08642618, 10.74135437,  8.35088328,  6.47340516,  1.14929085],\n",
+       "       [ 7.97403829,  2.85374226,  3.53672884,  4.96095042, 10.28506473],\n",
+       "       [ 5.04455411,  6.2884064 ,  2.1020647 ,  3.97954282,  9.30365713],\n",
+       "       [ 8.05520721,  3.2777533 ,  5.1127178 ,  6.99019592, 12.31431023],\n",
+       "       [ 8.033197  ,  3.2997635 ,  5.09070759,  6.96818571, 12.29230002],\n",
+       "       [ 4.88391014,  5.94387041,  3.55339931,  1.6759212 ,  4.62480712],\n",
+       "       [ 3.38092176,  9.44685879,  6.32341117,  5.17890958,  7.85479527],\n",
+       "       [ 5.83945489,  5.17241539,  2.78194429,  0.90446618,  4.41964814],\n",
+       "       [10.25764123,  4.57013932,  5.82033178,  3.69780989,  5.02192421],\n",
+       "       [ 3.16471551,  8.168245  ,  1.7777739 ,  3.90029578,  7.59956747],\n",
+       "       [ 8.83620663,  8.49675387,  5.89371722,  7.77119534, 13.09530965],\n",
+       "       [ 7.60754658,  6.94050708,  4.55003599,  2.67255787,  2.65155644],\n",
+       "       [ 4.14555919,  9.4785197 ,  7.0880486 ,  5.21057048,  5.09015784],\n",
+       "       [ 7.24126831,  4.57422881,  2.80395885,  0.68143697,  5.01783472],\n",
+       "       [ 5.70322513,  8.53100569,  2.76073572,  4.63821384,  9.96232815],\n",
+       "       [ 9.27617639,  9.55160416,  7.16113307,  5.28365495,  0.04045936],\n",
+       "       [ 2.5651854 , 11.39296595,  5.00249486,  7.12501674,  9.80090243],\n",
+       "       [14.22296519,  3.5559257 ,  9.78565573,  7.66313385,  6.03613783],\n",
+       "       [ 8.33806089,  2.48971967,  3.90075143,  5.77822955, 11.10234386],\n",
+       "       [14.34079531,  3.51301476,  9.90348585,  7.78096397,  7.91830771],\n",
+       "       [ 7.55811406,  6.89107456,  4.50060346,  2.62312535,  2.70098897],\n",
+       "       [ 9.54667188,  8.87963238,  6.48916129,  4.61168317,  0.71243114],\n",
+       "       [ 6.99771477,  3.83006578,  2.56040532,  2.43788343,  7.76199775],\n",
+       "       [10.85478728,  4.18774778,  6.41747782,  4.29495594,  5.40431574],\n",
+       "       [ 6.89563349,  8.43732701,  3.95314408,  5.8306222 , 11.15473651],\n",
+       "       [12.29945454,  3.63241504,  7.86214508,  5.7396232 ,  5.95964848],\n",
+       "       [ 6.57929244,  6.75366806,  3.63680304,  5.51428115, 10.83839547],\n",
+       "       [ 8.35675866,  8.47102189,  6.0805508 ,  4.20307268,  1.90234436],\n",
+       "       [11.26183   ,  1.40520949,  6.82452055,  5.67315871, 10.99727302],\n",
+       "       [ 6.92663397,  8.25959447,  5.86912337,  3.99164526,  2.30908306],\n",
+       "       [ 6.97410775,  3.8536728 ,  2.53679829,  3.96088096,  9.28499527],\n",
+       "       [10.00715257,  8.82062799,  6.94964198,  4.92783614,  0.77143554],\n",
+       "       [ 8.83013405,  7.9976465 ,  5.77262346,  3.89514534,  1.59441703],\n",
+       "       [ 6.69445759,  4.63850292,  2.86823295,  4.74571107, 10.06982539],\n",
+       "       [ 2.60649588, 11.43427644,  5.04380534,  7.16632722,  9.84221291],\n",
+       "       [ 9.01806225,  4.31489826,  6.07557284,  7.95305096, 13.27716527],\n",
+       "       [ 7.49191577,  3.84104474,  4.07077477,  5.94825289, 11.2723672 ],\n",
+       "       [ 7.80056437,  9.53239613,  4.85807497,  6.73555308, 12.0596674 ],\n",
+       "       [ 8.85156915,  2.48139135,  4.71112139,  6.58859951, 11.91271382],\n",
+       "       [10.04988811,  2.61715138,  5.61257866,  6.8851006 , 12.20921491],\n",
+       "       [ 3.68039673,  7.65256378,  1.26209268,  3.38461456,  7.08388625],\n",
+       "       [10.04984807,  7.28311243,  7.10735867,  8.98483678, 14.3089511 ],\n",
+       "       [ 8.34309643, 10.48468413,  8.09421303,  6.21673491,  0.8926206 ],\n",
+       "       [14.48203148,  3.65425093, 10.04472202,  7.92220014,  7.77707154]])"
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "cost_matrix"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "We will solve for both LSCP and LSCP-B and plot and compare the results to demonstrate their similarities and differences. \n",
+    "\n",
+    "With ``LSCP.from_cost_matrix`` we model the LSC problem to cover all demand points with $p$ facility points within `max_coverage` meters as service radius using the cost matrix calculated previously.\n",
+    "\n",
+    "With ``LSCPB.from_cost_matrix`` we model the LSC Backup problem to cover all demand points with $p$ facility points within `max_coverage` meters as service radius using the cost matrix calculated previously."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "lscp_from_cost_matrix = LSCP.from_cost_matrix(cost_matrix, SERVICE_RADIUS)\n",
+    "lscp_from_cost_matrix = lscp_from_cost_matrix.solve(solver)\n",
+    "\n",
+    "lscpb_from_cost_matrix = LSCPB.from_cost_matrix(cost_matrix, SERVICE_RADIUS, solver)\n",
+    "lscpb_from_cost_matrix = lscpb_from_cost_matrix.solve(solver)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Expected result is an instance of LSCP and LSCPB."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<spopt.locate.coverage.LSCP at 0x7f892b11fb80>"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "lscp_from_cost_matrix"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<spopt.locate.coverage.LSCPB at 0x7f892b11d0d0>"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "lscpb_from_cost_matrix"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Using a GeoDataFrame"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Assign a predefined location using a geodataframe column"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "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>id</th>\n",
+       "      <th>geometry</th>\n",
+       "      <th>comp_label</th>\n",
+       "      <th>predefined_loc</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>0</td>\n",
+       "      <td>POINT (9.00000 3.25259)</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1</td>\n",
+       "      <td>POINT (0.91963 6.00000)</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>2</td>\n",
+       "      <td>POINT (5.31010 4.00000)</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>3</td>\n",
+       "      <td>POINT (5.18758 6.00000)</td>\n",
+       "      <td>0</td>\n",
+       "      <td>0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>4</td>\n",
+       "      <td>POINT (6.51169 10.00000)</td>\n",
+       "      <td>0</td>\n",
+       "      <td>1</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   id                  geometry  comp_label  predefined_loc\n",
+       "0   0   POINT (9.00000 3.25259)           0               0\n",
+       "1   1   POINT (0.91963 6.00000)           0               0\n",
+       "2   2   POINT (5.31010 4.00000)           0               0\n",
+       "3   3   POINT (5.18758 6.00000)           0               0\n",
+       "4   4  POINT (6.51169 10.00000)           0               1"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "facilities_snapped['predefined_loc'] = numpy.array([0, 0, 0, 0, 1])\n",
+    "facilities_snapped"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "With ``LSCP.from_geodataframe`` we model the LSC problem to cover all demand points with $p$ facility points within `max_coverage` meters as service radius using geodataframes without calculating the cost matrix previously.\n",
+    "\n",
+    "With ``LSCPB.from_geodataframe`` we model the LSC Backup problem to cover all demand points with $p$ facility points within `max_coverage` meters as service radius using geodataframes without calculating the cost matrix previously."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "lscp_from_geodataframe = LSCP.from_geodataframe(\n",
+    "    clients_snapped, facilities_snapped, \"geometry\", \"geometry\", 7, distance_metric=\"euclidean\"\n",
+    ")\n",
+    "lscp_from_geodataframe = lscp_from_geodataframe.solve(solver)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "lscpb_from_geodataframe = LSCPB.from_geodataframe(\n",
+    "    clients_snapped, facilities_snapped, \"geometry\", \"geometry\", 7, solver, distance_metric=\"euclidean\"\n",
+    ")\n",
+    "lscpb_from_geodataframe = lscpb_from_geodataframe.solve(solver)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Expected result is an instance of LSCP and LSCPB"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<spopt.locate.coverage.LSCP at 0x7f892b1215e0>"
+      ]
+     },
+     "execution_count": 18,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "lscp_from_geodataframe"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "<spopt.locate.coverage.LSCPB at 0x7f892b123490>"
+      ]
+     },
+     "execution_count": 19,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "lscpb_from_geodataframe"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "Modelling LSCP and LSCPB with preselected facilities"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "lscp_preselected_from_geodataframe = LSCP.from_geodataframe(\n",
+    "    clients_snapped, facilities_snapped, \"geometry\", \"geometry\", SERVICE_RADIUS, predefined_facility_col=\"predefined_loc\", distance_metric=\"euclidean\"\n",
+    ")\n",
+    "lscp_preselected_from_geodataframe = lscp_preselected_from_geodataframe.solve(solver)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "lscpb_preselected_from_geodataframe = LSCPB.from_geodataframe(\n",
+    "    clients_snapped, facilities_snapped, \"geometry\", \"geometry\", SERVICE_RADIUS, solver, predefined_facility_col=\"predefined_loc\", distance_metric=\"euclidean\"\n",
+    ")\n",
+    "lscpb_preselected_from_geodataframe = lscpb_preselected_from_geodataframe.solve(solver)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Plotting the results"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The cell below describes the plotting of the model results. For each method executed for the LSCP and LSCPB classes (from_cost_matrix, from_geodataframe) there is a corresponding plot. Selected facility sites (stars) are assigned a unique color, demand points covered by a facility are assigned the facility's unique color scheme. Demand points with multiple color rings represents facility coverage overlapping. Small red stars represent candidate facility sites that were not chosen."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from matplotlib.patches import Patch\n",
+    "import matplotlib.lines as mlines\n",
+    "from matplotlib_scalebar.scalebar import ScaleBar\n",
+    "\n",
+    "dv_colors = [\n",
+    "    \"saddlebrown\",\n",
+    "    \"darkgoldenrod\",\n",
+    "    \"mediumseagreen\",\n",
+    "    \"lightskyblue\",\n",
+    "    \"lavender\",\n",
+    "    \"darkslategray\",\n",
+    "    \"coral\",\n",
+    "    \"mediumvioletred\",\n",
+    "    \"darkcyan\",\n",
+    "    \"cyan\",\n",
+    "    \"limegreen\",\n",
+    "    \"peachpuff\",\n",
+    "    \"blueviolet\",\n",
+    "    \"fuchsia\",\n",
+    "    \"thistle\",\n",
+    "]\n",
+    "\n",
+    "def plot_results(model, facility_points_gdf, demand_points_gdf, facility_count, title, p):\n",
+    "    \n",
+    "    arr_points = [] \n",
+    "    fac_sites = [] \n",
+    "    \n",
+    "    for i in range(facility_count):\n",
+    "        if model.fac2cli[i]:\n",
+    "            geom = demand_points_gdf.iloc[model.fac2cli[i]][\"geometry\"]\n",
+    "            arr_points.append(geom)\n",
+    "            fac_sites.append(i)\n",
+    "\n",
+    "    \n",
+    "    fig, ax = plt.subplots(figsize=(10, 15))\n",
+    "    legend_elements = []\n",
+    "\n",
+    "    street.plot(ax=ax, alpha=1, color='black', zorder=1)\n",
+    "    legend_elements.append(mlines.Line2D(\n",
+    "        [],\n",
+    "        [],\n",
+    "        color='black',\n",
+    "        label='streets',\n",
+    "    ))\n",
+    "    \n",
+    "    demand_points_gdf.plot(\n",
+    "        ax=ax, fc=\"k\", ec=\"k\", marker=\"s\", markersize=7, zorder=2, lw=.5\n",
+    "    )\n",
+    "\n",
+    "    facility_points_gdf.plot(\n",
+    "        ax=ax, fc=\"brown\", marker=\"*\", markersize=80, zorder=8\n",
+    "    )\n",
+    "    legend_elements.append(\n",
+    "        mlines.Line2D(\n",
+    "            [],\n",
+    "            [],\n",
+    "            marker=\"*\",\n",
+    "            markerfacecolor=\"brown\",\n",
+    "            markeredgecolor=\"brown\",\n",
+    "            markeredgewidth=.5, \n",
+    "            ms=20,\n",
+    "            lw=0,\n",
+    "            label=f\"Unselected Candidate Store sites ($n$={facility_count})\"\n",
+    "        )\n",
+    "    )\n",
+    "\n",
+    "    _zo, _ms = 4, 4\n",
+    "    \n",
+    "    for i in range(len(arr_points)):\n",
+    "\n",
+    "        cset = dv_colors[i]\n",
+    "        fac = fac_sites[i] \n",
+    "        fname = fac_sites[i]\n",
+    "        fname = f\"Facility y{fname}\" \n",
+    "        \n",
+    "        gdf = geopandas.GeoDataFrame(arr_points[i])\n",
+    "        \n",
+    "        label = f\"Demand sites covered by {fname}\"\n",
+    "        gdf.plot(ax=ax, zorder=_zo, ec=\"k\", fc=cset, markersize=100*_ms, lw=.5,) \n",
+    "        legend_elements.append(\n",
+    "            mlines.Line2D(\n",
+    "                [],\n",
+    "                [],\n",
+    "                marker=\"o\",\n",
+    "                markerfacecolor=cset,\n",
+    "                markeredgecolor=\"k\",\n",
+    "                markeredgewidth=.5, \n",
+    "                ms= _ms + 7,\n",
+    "                lw=0,\n",
+    "                label=label\n",
+    "            )\n",
+    "        )\n",
+    "        \n",
+    "        facility_points_gdf.iloc[[fac]].plot(\n",
+    "            ax=ax, marker=\"*\", markersize=1000, zorder=9, fc=cset, ec=\"k\", lw=.5\n",
+    "        )\n",
+    "        legend_elements.append(\n",
+    "            mlines.Line2D(\n",
+    "                [],\n",
+    "                [],\n",
+    "                marker=\"*\",\n",
+    "                markerfacecolor=cset,\n",
+    "                markeredgecolor=\"k\",\n",
+    "                markeredgewidth=.5,\n",
+    "                ms=20,\n",
+    "                lw=0,\n",
+    "                label=fname,\n",
+    "            )\n",
+    "        )\n",
+    "        \n",
+    "        _zo += 1\n",
+    "        _ms -= (1)*(4/p)\n",
+    "     \n",
+    "    plt.title(title, fontsize=20)\n",
+    "    kws = dict(loc=\"upper left\", bbox_to_anchor=(1.05, 1.0), fontsize=15) \n",
+    "    plt.legend(handles=legend_elements, **kws)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### LSCP and LSCPB built from cost matrix"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 720x1080 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 720x1080 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_results(lscp_from_cost_matrix, facilities_snapped, clients_snapped, facilities_snapped.shape[0], \"LSCP - Cost Matrix\", lscp_from_cost_matrix.problem.objective.value())\n",
+    "plot_results(lscpb_from_cost_matrix, facilities_snapped, clients_snapped, facilities_snapped.shape[0], \"LSCP-B - Cost Matrix\", lscpb_from_cost_matrix.lscp_obj_value)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### LSCP built from geodataframe"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 720x1080 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 720x1080 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_results(lscp_from_geodataframe, facilities_snapped, clients_snapped, facilities_snapped.shape[0], \"LSCP - Geodataframe\", lscp_from_geodataframe.problem.objective.value())\n",
+    "plot_results(lscpb_from_geodataframe, facilities_snapped, clients_snapped, facilities_snapped.shape[0], \"LSCP-B - Geodataframe\", lscpb_from_geodataframe.lscp_obj_value)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "The model results for the methods from_cost_matrix() and from_geodataframe() are distinctly different. This result is expected as the distance between facility and demand points is calculated using different metrics. The cost matrix is calculated with dijkstra distance while the distance using geodataframe is calculated with euclidean distance. \n",
+    "\n",
+    "Why do the results for from_geodataframe() require just one facility to cover all of the demand points? It can be explained by the nature of the problem. The problem was configured in a synthetic manner, the street is created with 10x10 lattice and the max_coverage parameter is 8 meters, so this result is expected. You can change the max_coverage parameter to 2 meters and you will obtain a different result, but be aware of how many points will be able to be covered."
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### LSCP and LSCPB with preselected facilities"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 720x1080 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 720x1080 with 1 Axes>"
+      ]
+     },
+     "metadata": {
+      "needs_background": "light"
+     },
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "plot_results(lscp_preselected_from_geodataframe, facilities_snapped, clients_snapped, facilities_snapped.shape[0], \"LSCP - Preselected Facilities\", lscp_preselected_from_geodataframe.problem.objective.value())\n",
+    "plot_results(lscpb_preselected_from_geodataframe, facilities_snapped, clients_snapped, facilities_snapped.shape[0], \"LSCP-B - Preselected Facilities\", lscpb_preselected_from_geodataframe.lscp_obj_value)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## References\n",
+    "\n",
+    "- [Church, R. L., & Murray, A. T. (2018). Location covering models: History, applications and advancements (1st edition 2018). Springer](https://www.springer.com/gb/book/9783319998459)\n",
+    "- [Toregas, C., Swain, R., ReVelle, C., &amp; Bergman, L. (1971). The location of emergency service facilities. Operations Research, 19(6), 1363–1373.](https://pubsonline.informs.org/doi/abs/10.1287/opre.19.6.1363)\n",
+    "- [Daskin MS, Stern EH (1981) A hierarchical objective set covering model for emergency medical\n",
+    "service vehicle deployment.](https://daskin.engin.umich.edu/wp-content/uploads/sites/133/2014/07/daskinandstern_ts1981_.pdf)"
+   ]
+  }
+ ],
+ "metadata": {
+  "interpreter": {
+   "hash": "56b72aab97c5d88c22a6bf5872989e2e65e9296dc12395fbfb8350007c775deb"
+  },
+  "kernelspec": {
+   "display_name": "Python 3.8.13 ('geo_env')",
+   "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": "3.8.13"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}
diff --git a/spopt/locate/__init__.py b/spopt/locate/__init__.py
index 9cfe3564..77437b6e 100644
--- a/spopt/locate/__init__.py
+++ b/spopt/locate/__init__.py
@@ -1,5 +1,5 @@
 from .base import BaseOutputMixin, CoveragePercentageMixin, MeanDistanceMixin
-from .coverage import LSCP, MCLP
+from .coverage import LSCP, MCLP, LSCPB
 from .p_median import PMedian
 from .p_center import PCenter
 from .util import simulated_geo_points
diff --git a/spopt/locate/base.py b/spopt/locate/base.py
index ad646f27..014502d6 100644
--- a/spopt/locate/base.py
+++ b/spopt/locate/base.py
@@ -75,7 +75,10 @@ def client_facility_array(self) -> None:
                 for fac_site in self.fac2cli[i]:
                     self.cli2fac[fac_site].append(i)
         else:
-            raise AttributeError("The attribute `fac2cli` is not set. See `facility_client_array` method to set the attribute")
+            raise AttributeError(
+                "The attribute `fac2cli` is not set. See `facility_client_array` method to set the attribute"
+            )
+
 
 class CoveragePercentageMixin:
     """
@@ -103,8 +106,9 @@ def uncovered_clients(self) -> None:
 
             self.n_cli_uncov = self.aij.shape[0] - len(set_cov)
         else:
-            raise AttributeError("The attribute `fac2cli` is not set. See `facility_client_array` method to set the attribute")
-
+            raise AttributeError(
+                "The attribute `fac2cli` is not set. See `facility_client_array` method to set the attribute"
+            )
 
     def get_percentage(self):
         """
@@ -113,7 +117,10 @@ def get_percentage(self):
         if hasattr(self, "n_cli_uncov"):
             self.percentage = 1 - (self.n_cli_uncov / self.aij.shape[0])
         else:
-            raise AttributeError("The attribute `n_cli_uncov` is not set. See `uncovered_clients` method to set the attribute.")
+            raise AttributeError(
+                "The attribute `n_cli_uncov` is not set. See `uncovered_clients` method to set the attribute."
+            )
+
 
 class MeanDistanceMixin:
     """
@@ -291,6 +298,59 @@ def add_set_covering_constraint(
                 "before setting constraints must set facility variable"
             )
 
+    @staticmethod
+    def add_backup_covering_constraint(
+        obj: T_FacModel,
+        model: pulp.LpProblem,
+        ni: np.array,
+        range_facility: range,
+        range_client: range,
+    ) -> None:
+        """
+        backup covering constraint:
+        - coverage_0 + facility_1 + facility_3 + facility_4 + facility_6 + facility_7 + facility_9 >= 1
+
+        Parameters
+        ----------
+        obj: T_FacModel
+            bounded type of LocateSolver class
+        model: pulp.LpProblem
+            optimization model problem
+        ni: np.array
+            two-dimensional array that defines candidate sites between facility points within a distance to supply {i}
+            demand point
+        range_facility: range
+            range of facility points quantity
+        range_client: range
+            range of demand points quantity
+        Returns
+        -------
+        None
+
+        """
+        if hasattr(obj, "fac_vars"):
+            fac_vars = getattr(obj, "fac_vars")
+            cli_vars = getattr(obj, "cli_vars")
+            for i in range_client:
+                if sum(ni[i]) >= 2:
+                    model += (
+                        pulp.lpSum(
+                            [int(ni[i][j]) * fac_vars[j] for j in range_facility]
+                        )
+                        >= 1 + 1 * cli_vars[i]
+                    )
+                else:
+                    model += (
+                        pulp.lpSum(
+                            [int(ni[i][j]) * fac_vars[j] for j in range_facility]
+                        )
+                        >= 1 + 0 * cli_vars[i]
+                    )
+        else:
+            raise AttributeError(
+                "before setting constraints must set facility variable"
+            )
+
     @staticmethod
     def add_facility_constraint(
         obj: T_FacModel, model: pulp.LpProblem, p_facilities: int
diff --git a/spopt/locate/coverage.py b/spopt/locate/coverage.py
index cd2e201a..7b242a9d 100644
--- a/spopt/locate/coverage.py
+++ b/spopt/locate/coverage.py
@@ -36,7 +36,7 @@ class LSCP(LocateSolver, BaseOutputMixin):
     cli2fac: np.array
         2-d MxN, where m is number of clients and n is number of facilities. Each row represent a client and has an array containing facility index meaning that the client is covered by the facility ith.
     aij: np.array
-        Cost matrix 2-d array 
+        Cost matrix 2-d array
     """
 
     def __init__(self, name: str, problem: pulp.LpProblem):
@@ -314,6 +314,323 @@ def solve(self, solver: pulp.LpSolver, results: bool = True):
         return self
 
 
+class LSCPB(LocateSolver, BaseOutputMixin):
+    """
+    LSCPB class implements Location Set Covering Problem - Backup optimization model and solves it.
+
+    Parameters
+    ----------
+    name: str
+        Problem name
+    problem: pulp.LpProblem
+        Pulp instance of optimization model that contains constraints, variables and objective function.
+
+    Attributes
+    ----------
+    name: str
+        Problem name
+    problem: pulp.LpProblem
+        Pulp instance of optimization model that contains constraints, variables and objective function.
+    lscp_obj_value: float
+        Objective value returned from solved LSCP instance.
+    fac2cli : np.array
+        2-d array MxN, where m is number of facilities and n is number of clients. Each row represents a facility and has an array containing clients index meaning that the facility-i cover the entire array.
+    cli2fac: np.array
+        2-d MxN, where m is number of clients and n is number of facilities. Each row represent a client and has an array containing facility index meaning that the client is covered by the facility ith.
+    aij: np.array
+        Cost matrix 2-d array
+    """
+
+    def __init__(self, name: str, problem: pulp.LpProblem, lscp_obj_value=0.0):
+        self.lscp_obj_value = lscp_obj_value
+        super().__init__(name, problem)
+
+    def __add_obj(self) -> None:
+        """
+        Add objective function to model:
+        (Coverage Variable)
+        Maximize U1 + U2 + U3 + U4 + U5 + ... + Uj
+
+        Returns
+        -------
+        None
+        """
+        cov_vars = getattr(self, "cli_vars")
+        self.problem += pulp.lpSum(cov_vars), "objective function"
+
+    @classmethod
+    def from_cost_matrix(
+        cls,
+        cost_matrix: np.array,
+        service_radius: float,
+        solver: pulp.LpSolver,
+        predefined_facilities_arr: np.array = None,
+        name: str = "LSCP-B",
+    ):
+        """
+        Create a LSCPB object based on a cost matrix.
+
+        Parameters
+        ----------
+        cost_matrix: np.array
+            two-dimensional distance array between facility points and demand point
+        service_radius: float
+            maximum acceptable service distance by problem
+        name: str, default="LSCP-B"
+            name of the problem
+
+        Returns
+        -------
+        LSCPB object
+
+        Examples
+        --------
+        >>> from spopt.locate.coverage import LSCPB, LSCP
+        >>> from spopt.locate.util import simulated_geo_points
+        >>> import pulp
+        >>> import spaghetti
+
+        Create regular lattice
+
+        >>> lattice = spaghetti.regular_lattice((0, 0, 10, 10), 9, exterior=True)
+        >>> ntw = spaghetti.Network(in_data=lattice)
+        >>> street = spaghetti.element_as_gdf(ntw, arcs=True)
+        >>> street_buffered = geopandas.GeoDataFrame(
+        ...                            geopandas.GeoSeries(street["geometry"].buffer(0.2).unary_union),
+        ...                            crs=street.crs,
+        ...                            columns=["geometry"])
+
+        Simulate points belong to lattice
+
+        >>> demand_points = simulated_geo_points(street_buffered, needed=100, seed=5)
+        >>> facility_points = simulated_geo_points(street_buffered, needed=5, seed=6)
+
+        Snap points to the network
+
+        >>> ntw.snapobservations(demand_points, "clients", attribute=True)
+        >>> clients_snapped = spaghetti.element_as_gdf(ntw, pp_name="clients", snapped=True)
+        >>> ntw.snapobservations(facility_points, "facilities", attribute=True)
+        >>> facilities_snapped = spaghetti.element_as_gdf(ntw, pp_name="facilities", snapped=True)
+
+        Calculate the cost matrix
+        >>> cost_matrix = ntw.allneighbordistances(
+        ...    sourcepattern=ntw.pointpatterns["clients"],
+        ...    destpattern=ntw.pointpatterns["facilities"])
+
+        Create LSCPB instance from cost matrix
+
+        >>> lscpb_from_cost_matrix = LSCPB.from_cost_matrix(cost_matrix, max_coverage=8, pulp.PULP_CBC_CMD(msg=False)
+        >>> lscpb_from_cost_matrix = lscpb_from_cost_matrix.solve(pulp.PULP_CBC_CMD(msg=False))
+
+        Get facility lookup demand coverage array
+
+        >>> lscpb_from_cost_matrix.fac2cli
+
+        """
+        if predefined_facilities_arr is not None:
+            lscp = LSCP.from_cost_matrix(
+                cost_matrix, service_radius, predefined_facilities_arr
+            )
+        else:
+            lscp = LSCP.from_cost_matrix(cost_matrix, service_radius)
+        lscp.solve(solver)
+
+        r_fac = range(cost_matrix.shape[1])
+        r_cli = range(cost_matrix.shape[0])
+
+        model = pulp.LpProblem(name, pulp.LpMaximize)
+
+        lscpb = LSCPB(name, model)
+        lscpb.lscp_obj_value = lscp.problem.objective.value()
+
+        FacilityModelBuilder.add_facility_integer_variable(lscpb, r_fac, "x[{i}]")
+        FacilityModelBuilder.add_client_integer_variable(lscpb, r_cli, "u[{i}]")
+
+        lscpb.aij = np.zeros(cost_matrix.shape)
+        lscpb.aij[cost_matrix <= service_radius] = 1
+
+        if predefined_facilities_arr is not None:
+            FacilityModelBuilder.add_predefined_facility_constraint(
+                lscpb, lscpb.problem, predefined_facilities_arr
+            )
+
+        lscpb.__add_obj()
+        FacilityModelBuilder.add_facility_constraint(
+            lscpb, lscpb.problem, lscpb.lscp_obj_value
+        )
+        FacilityModelBuilder.add_backup_covering_constraint(
+            lscpb, lscpb.problem, lscpb.aij, r_fac, r_cli
+        )
+
+        return lscpb
+
+    @classmethod
+    def from_geodataframe(
+        cls,
+        gdf_demand: GeoDataFrame,
+        gdf_fac: GeoDataFrame,
+        demand_col: str,
+        facility_col: str,
+        service_radius: float,
+        solver: pulp.LpSolver,
+        predefined_facility_col: str = None,
+        distance_metric: str = "euclidean",
+        name: str = "LSCP-B",
+    ):
+        """
+        Create a LSCPB object based on geodataframes. Calculate the cost matrix between demand and facility,
+        and then use from_cost_matrix method.
+
+        Parameters
+        ----------
+        gdf_demand: geopandas.GeoDataFrame
+            demand geodataframe with point geometry
+        gdf_fac: geopandas.GeoDataframe
+            facility geodataframe with point geometry
+        demand_col: str
+            demand geometry column name
+        facility_col: str
+            facility candidate sites geometry column name
+        service_radius: float
+            maximum acceptable service distance by problem
+        distance_metric: str, default="euclidean"
+            metrics supported by :method: `scipy.spatial.distance.cdist` used for the distance calculations
+        name: str, default="LSCP"
+            name of the problem
+
+        Returns
+        -------
+        LSCPB object
+
+        Examples
+        --------
+        >>> from spopt.locate.coverage import LSCB, LSCP
+        >>> from spopt.locate.util import simulated_geo_points
+        >>> import pulp
+        >>> import spaghetti
+
+        Create regular lattice
+
+        >>> lattice = spaghetti.regular_lattice((0, 0, 10, 10), 9, exterior=True)
+        >>> ntw = spaghetti.Network(in_data=lattice)
+        >>> street = spaghetti.element_as_gdf(ntw, arcs=True)
+        >>> street_buffered = geopandas.GeoDataFrame(
+        ...                            geopandas.GeoSeries(street["geometry"].buffer(0.2).unary_union),
+        ...                            crs=street.crs,
+        ...                            columns=["geometry"])
+
+        Simulate points belong to lattice
+
+        >>> demand_points = simulated_geo_points(street_buffered, needed=100, seed=5)
+        >>> facility_points = simulated_geo_points(street_buffered, needed=5, seed=6)
+
+        Snap points to the network
+
+        >>> ntw.snapobservations(demand_points, "clients", attribute=True)
+        >>> clients_snapped = spaghetti.element_as_gdf(ntw, pp_name="clients", snapped=True)
+        >>> ntw.snapobservations(facility_points, "facilities", attribute=True)
+        >>> facilities_snapped = spaghetti.element_as_gdf(ntw, pp_name="facilities", snapped=True)
+
+        Create LSCPB instance from cost matrix
+
+        >>> lscpb_from_geodataframe = LSCPB.from_geodataframe(clients_snapped, facilities_snapped,
+        ...                                                "geometry", "geometry",
+        ...                                                 max_coverage=8, pulp.PULP_CBC_CMD(msg=False), distance_metric="euclidean")
+        >>> lscpb_from_geodataframe = lscpb_from_geodataframe.solve(pulp.PULP_CBC_CMD(msg=False))
+
+        Get facility lookup demand coverage array
+
+        >>> lscpb_from_geodataframe.fac2cli
+
+        """
+
+        predefined_facilities_arr = None
+        if predefined_facility_col is not None:
+            predefined_facilities_arr = gdf_fac[predefined_facility_col].to_numpy()
+
+        dem = gdf_demand[demand_col]
+        fac = gdf_fac[facility_col]
+
+        dem_type_geom = dem.geom_type.unique()
+        fac_type_geom = fac.geom_type.unique()
+
+        if len(dem_type_geom) > 1 or not "Point" in dem_type_geom:
+            warnings.warn(
+                "Demand geodataframe contains mixed type geometries or is not a point. Be sure deriving centroid from geometries doesn't affect the results.",
+                Warning,
+            )
+            dem = dem.centroid
+
+        if len(fac_type_geom) > 1 or not "Point" in fac_type_geom:
+            warnings.warn(
+                "Facility geodataframe contains mixed type geometries or is not a point. Be sure deriving centroid from geometries doesn't affect the results.",
+                Warning,
+            )
+            fac = fac.centroid
+
+        dem_data = np.array([dem.x.to_numpy(), dem.y.to_numpy()]).T
+        fac_data = np.array([fac.x.to_numpy(), fac.y.to_numpy()]).T
+
+        if gdf_demand.crs != gdf_fac.crs:
+            raise ValueError(
+                f"geodataframes crs are different: gdf_demand-{gdf_demand.crs}, gdf_fac-{gdf_fac.crs}"
+            )
+
+        distances = cdist(dem_data, fac_data, distance_metric)
+
+        return cls.from_cost_matrix(
+            distances, service_radius, solver, predefined_facilities_arr, name
+        )
+
+    def facility_client_array(self) -> None:
+        """
+        Create an array 2d MxN, where m is number of facilities and n is number of clients. Each row represent a facility and has an array containing clients index meaning that the facility-i cover the entire array.
+
+        Returns
+        -------
+        None
+        """
+
+        fac_vars = getattr(self, "fac_vars")
+        len_fac_vars = len(fac_vars)
+
+        self.fac2cli = []
+
+        for j in range(len_fac_vars):
+            array_cli = []
+            if fac_vars[j].value() > 0:
+                for i in range(self.aij.shape[0]):
+                    if self.aij[i][j] > 0:
+                        array_cli.append(i)
+
+            self.fac2cli.append(array_cli)
+
+    def solve(self, solver: pulp.LpSolver, results: bool = True):
+        """
+        Solve the LSCPB model
+
+        Parameters
+        ----------
+        solver: pulp.LpSolver
+            solver supported by pulp package
+
+        results: bool
+            if True it will create metainfo - which facilities cover which demand and vice-versa, and the uncovered demand - about the model results
+
+        Returns
+        -------
+        LSCPB object
+        """
+        self.problem.solve(solver)
+        self.check_status()
+
+        if results:
+            self.facility_client_array()
+            self.client_facility_array()
+
+        return self
+
+
 class MCLP(LocateSolver, BaseOutputMixin, CoveragePercentageMixin):
     """
     MCLP class implements Maximal Coverage Location optimization model and solve it.
@@ -336,7 +653,7 @@ class MCLP(LocateSolver, BaseOutputMixin, CoveragePercentageMixin):
     cli2fac: np.array
         2-d MxN, where m is number of clients and n is number of facilities. Each row represent a client and has an array containing facility index meaning that the client is covered by the facility ith.
     aij: np.array
-        Cost matrix 2-d array 
+        Cost matrix 2-d array
     n_cli_uncov: int
         Specify how many clients points are not covered.
     """
diff --git a/spopt/tests/data/lscpb_cli2fac.pkl b/spopt/tests/data/lscpb_cli2fac.pkl
new file mode 100644
index 00000000..63980f1a
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diff --git a/spopt/tests/data/lscpb_fac2cli.pkl b/spopt/tests/data/lscpb_fac2cli.pkl
new file mode 100644
index 00000000..006fb26b
Binary files /dev/null and b/spopt/tests/data/lscpb_fac2cli.pkl differ
diff --git a/spopt/tests/data/lscpb_geodataframe_cli2fac.pkl b/spopt/tests/data/lscpb_geodataframe_cli2fac.pkl
new file mode 100644
index 00000000..704f03ae
Binary files /dev/null and b/spopt/tests/data/lscpb_geodataframe_cli2fac.pkl differ
diff --git a/spopt/tests/data/lscpb_geodataframe_fac2cli.pkl b/spopt/tests/data/lscpb_geodataframe_fac2cli.pkl
new file mode 100644
index 00000000..35671efe
Binary files /dev/null and b/spopt/tests/data/lscpb_geodataframe_fac2cli.pkl differ
diff --git a/spopt/tests/data/lscpb_preselected_loc_geodataframe_fac2cli.pkl b/spopt/tests/data/lscpb_preselected_loc_geodataframe_fac2cli.pkl
new file mode 100644
index 00000000..cf1e809f
Binary files /dev/null and b/spopt/tests/data/lscpb_preselected_loc_geodataframe_fac2cli.pkl differ
diff --git a/spopt/tests/test_lscpb.py b/spopt/tests/test_lscpb.py
new file mode 100644
index 00000000..4ab8fffd
--- /dev/null
+++ b/spopt/tests/test_lscpb.py
@@ -0,0 +1,318 @@
+import numpy
+import geopandas
+import pandas
+import pulp
+import spaghetti
+from shapely.geometry import Point, Polygon
+
+from spopt.locate import LSCPB
+from spopt.locate.base import FacilityModelBuilder, LocateSolver
+from spopt.locate.util import simulated_geo_points
+import unittest
+import os
+import pickle
+import platform
+
+operating_system = platform.platform()[:7].lower()
+if operating_system == "windows":
+    WINDOWS = True
+else:
+    WINDOWS = False
+
+
+class TestSyntheticLocate(unittest.TestCase):
+    def setUp(self) -> None:
+        self.dirpath = os.path.join(os.path.dirname(__file__), "./data/")
+
+        lattice = spaghetti.regular_lattice((0, 0, 10, 10), 9, exterior=True)
+        ntw = spaghetti.Network(in_data=lattice)
+        gdf = spaghetti.element_as_gdf(ntw, arcs=True)
+        street = geopandas.GeoDataFrame(
+            geopandas.GeoSeries(gdf["geometry"].buffer(0.2).unary_union),
+            crs=gdf.crs,
+            columns=["geometry"],
+        )
+
+        client_count = 100
+        facility_count = 5
+
+        self.client_points = simulated_geo_points(street, needed=client_count, seed=5)
+        self.facility_points = simulated_geo_points(
+            street, needed=facility_count, seed=6
+        )
+
+        ntw = spaghetti.Network(in_data=lattice)
+
+        ntw.snapobservations(self.client_points, "clients", attribute=True)
+        ntw.snapobservations(self.facility_points, "facilities", attribute=True)
+
+        self.clients_snapped = spaghetti.element_as_gdf(
+            ntw, pp_name="clients", snapped=True
+        )
+
+        self.facilities_snapped = spaghetti.element_as_gdf(
+            ntw, pp_name="facilities", snapped=True
+        )
+
+        self.cost_matrix = ntw.allneighbordistances(
+            sourcepattern=ntw.pointpatterns["clients"],
+            destpattern=ntw.pointpatterns["facilities"],
+        )
+
+        self.ai = numpy.random.randint(1, 12, client_count)
+
+        self.clients_snapped["weights"] = self.ai
+
+    def test_lscpb_from_cost_matrix(self):
+        lscpb = LSCPB.from_cost_matrix(
+            self.cost_matrix, 10, pulp.PULP_CBC_CMD(msg=False)
+        )
+        result = lscpb.solve(pulp.PULP_CBC_CMD(msg=False))
+        self.assertIsInstance(result, LSCPB)
+
+    def test_lscpb_facility_client_array_from_cost_matrix(self):
+        with open(self.dirpath + "lscpb_fac2cli.pkl", "rb") as f:
+            lscpb_objective = pickle.load(f)
+
+        lscpb = LSCPB.from_cost_matrix(
+            self.cost_matrix, 8, pulp.PULP_CBC_CMD(msg=False)
+        )
+        lscpb = lscpb.solve(pulp.PULP_CBC_CMD(msg=False))
+        lscpb.facility_client_array()
+
+        numpy.testing.assert_array_equal(lscpb.fac2cli, lscpb_objective)
+
+    def test_lscpb_client_facility_array_from_cost_matrix(self):
+        with open(self.dirpath + "lscpb_cli2fac.pkl", "rb") as f:
+            lscpb_objective = pickle.load(f)
+
+        lscpb = LSCPB.from_cost_matrix(
+            self.cost_matrix, 8, pulp.PULP_CBC_CMD(msg=False)
+        )
+        lscpb = lscpb.solve(pulp.PULP_CBC_CMD(msg=False))
+        lscpb.facility_client_array()
+        lscpb.client_facility_array()
+
+        numpy.testing.assert_array_equal(lscpb.cli2fac, lscpb_objective)
+
+    def test_lscpb_from_geodataframe(self):
+        lscpb = LSCPB.from_geodataframe(
+            self.clients_snapped,
+            self.facilities_snapped,
+            "geometry",
+            "geometry",
+            10,
+            pulp.PULP_CBC_CMD(msg=False),
+        )
+        result = lscpb.solve(pulp.PULP_CBC_CMD(msg=False))
+        self.assertIsInstance(result, LSCPB)
+
+    def test_lscpb_facility_client_array_from_geodataframe(self):
+        with open(self.dirpath + "lscpb_geodataframe_fac2cli.pkl", "rb") as f:
+            lscpb_objective = pickle.load(f)
+
+        lscpb = LSCPB.from_geodataframe(
+            self.clients_snapped,
+            self.facilities_snapped,
+            "geometry",
+            "geometry",
+            8,
+            pulp.PULP_CBC_CMD(msg=False),
+        )
+        lscpb = lscpb.solve(pulp.PULP_CBC_CMD(msg=False))
+        lscpb.facility_client_array()
+
+        numpy.testing.assert_array_equal(lscpb.fac2cli, lscpb_objective)
+
+    def test_lscpb_client_facility_array_from_geodataframe(self):
+        with open(self.dirpath + "lscpb_geodataframe_cli2fac.pkl", "rb") as f:
+            lscpb_objective = pickle.load(f)
+
+        lscpb = LSCPB.from_geodataframe(
+            self.clients_snapped,
+            self.facilities_snapped,
+            "geometry",
+            "geometry",
+            8,
+            pulp.PULP_CBC_CMD(msg=False),
+        )
+        lscpb = lscpb.solve(pulp.PULP_CBC_CMD(msg=False))
+        lscpb.facility_client_array()
+        lscpb.client_facility_array()
+
+        numpy.testing.assert_array_equal(lscpb.cli2fac, lscpb_objective)
+
+    def test_lscpb_preselected_facility_client_array_from_geodataframe(self):
+        with open(
+            self.dirpath + "lscpb_preselected_loc_geodataframe_fac2cli.pkl", "rb"
+        ) as f:
+            lscpb_objective = pickle.load(f)
+
+        fac_snapped = self.facilities_snapped.copy()
+        fac_snapped["predefined_loc"] = numpy.array([0, 0, 0, 0, 1])
+
+        lscpb = LSCPB.from_geodataframe(
+            gdf_demand=self.clients_snapped,
+            gdf_fac=fac_snapped,
+            demand_col="geometry",
+            facility_col="geometry",
+            service_radius=8,
+            solver=pulp.PULP_CBC_CMD(msg=False, warmStart=True),
+            predefined_facility_col="predefined_loc",
+        )
+        lscpb = lscpb.solve(pulp.PULP_CBC_CMD(msg=False, warmStart=True))
+        lscpb.facility_client_array()
+
+        numpy.testing.assert_array_equal(lscpb.fac2cli, lscpb_objective)
+
+
+class TestRealWorldLocate(unittest.TestCase):
+    def setUp(self) -> None:
+        self.dirpath = os.path.join(os.path.dirname(__file__), "./data/")
+        network_distance = pandas.read_csv(
+            self.dirpath
+            + "SF_network_distance_candidateStore_16_censusTract_205_new.csv"
+        )
+
+        ntw_dist_piv = network_distance.pivot_table(
+            values="distance", index="DestinationName", columns="name"
+        )
+
+        self.cost_matrix = ntw_dist_piv.to_numpy()
+
+        demand_points = pandas.read_csv(
+            self.dirpath + "SF_demand_205_centroid_uniform_weight.csv"
+        )
+        facility_points = pandas.read_csv(self.dirpath + "SF_store_site_16_longlat.csv")
+
+        self.facility_points_gdf = (
+            geopandas.GeoDataFrame(
+                facility_points,
+                geometry=geopandas.points_from_xy(
+                    facility_points.long, facility_points.lat
+                ),
+            )
+            .sort_values(by=["NAME"])
+            .reset_index()
+        )
+
+        self.demand_points_gdf = (
+            geopandas.GeoDataFrame(
+                demand_points,
+                geometry=geopandas.points_from_xy(
+                    demand_points.long, demand_points.lat
+                ),
+            )
+            .sort_values(by=["NAME"])
+            .reset_index()
+        )
+
+        self.service_dist = 5000.0
+        self.p_facility = 4
+        self.ai = self.demand_points_gdf["POP2000"].to_numpy()
+
+    def test_optimality_lscpb_from_cost_matrix(self):
+        lscpb = LSCPB.from_cost_matrix(
+            self.cost_matrix, self.service_dist, pulp.PULP_CBC_CMD(msg=False)
+        )
+        lscpb = lscpb.solve(pulp.PULP_CBC_CMD(msg=False))
+
+        self.assertEqual(lscpb.problem.status, pulp.LpStatusOptimal)
+
+    def test_infeasibility_lscpb_from_cost_matrix(self):
+        with self.assertRaises(RuntimeError):
+            lscpb = LSCPB.from_cost_matrix(
+                self.cost_matrix, 20, pulp.PULP_CBC_CMD(msg=False)
+            )
+            lscpb.solve(pulp.PULP_CBC_CMD(msg=False))
+
+    def test_optimality_lscpb_from_geodataframe(self):
+        lscpb = LSCPB.from_geodataframe(
+            self.demand_points_gdf,
+            self.facility_points_gdf,
+            "geometry",
+            "geometry",
+            self.service_dist,
+            pulp.PULP_CBC_CMD(msg=False),
+        )
+        lscpb = lscpb.solve(pulp.PULP_CBC_CMD(msg=False))
+        self.assertEqual(lscpb.problem.status, pulp.LpStatusOptimal)
+
+    def test_infeasibility_lscpb_from_geodataframe(self):
+        with self.assertRaises(RuntimeError):
+            lscpb = LSCPB.from_geodataframe(
+                self.demand_points_gdf,
+                self.facility_points_gdf,
+                "geometry",
+                "geometry",
+                0,
+                pulp.PULP_CBC_CMD(msg=False),
+            )
+            lscpb.solve(pulp.PULP_CBC_CMD(msg=False))
+
+
+class TestErrorsWarnings(unittest.TestCase):
+    def setUp(self) -> None:
+
+        pol1 = Polygon([(0, 0), (1, 0), (1, 1)])
+        pol2 = Polygon([(0, 0), (1, 0), (1, 1), (0, 1)])
+        pol3 = Polygon([(2, 0), (3, 0), (3, 1), (2, 1)])
+        polygon_dict = {"geometry": [pol1, pol2, pol3]}
+
+        point = Point(10, 10)
+        point_dict = {"weight": 4, "geometry": [point]}
+
+        self.gdf_fac = geopandas.GeoDataFrame(polygon_dict, crs="EPSG:4326")
+        self.gdf_dem = geopandas.GeoDataFrame(point_dict, crs="EPSG:4326")
+
+        self.gdf_dem_crs = self.gdf_dem.to_crs("EPSG:3857")
+
+        self.gdf_dem_buffered = self.gdf_dem.copy()
+        self.gdf_dem_buffered["geometry"] = self.gdf_dem.buffer(2)
+
+    def test_error_lscpb_different_crs(self):
+        with self.assertRaises(ValueError):
+            dummy_class = LSCPB.from_geodataframe(
+                self.gdf_dem_crs,
+                self.gdf_fac,
+                "geometry",
+                "geometry",
+                10,
+                pulp.PULP_CBC_CMD(msg=False),
+            )
+
+    def test_warning_lscpb_facility_geodataframe(self):
+        with self.assertWarns(Warning):
+            dummy_class = LSCPB.from_geodataframe(
+                self.gdf_dem,
+                self.gdf_fac,
+                "geometry",
+                "geometry",
+                100,
+                pulp.PULP_CBC_CMD(msg=False),
+            )
+
+    def test_warning_lscpb_demand_geodataframe(self):
+        with self.assertWarns(Warning):
+            dummy_class = LSCPB.from_geodataframe(
+                self.gdf_dem_buffered,
+                self.gdf_fac,
+                "geometry",
+                "geometry",
+                100,
+                pulp.PULP_CBC_CMD(msg=False),
+            )
+
+    def test_attribute_error_add_facility_constraint(self):
+        with self.assertRaises(AttributeError):
+            dummy_class = LSCPB("dummy", pulp.LpProblem("name"))
+            dummy_p_facility = 1
+            dummy_fac_r = 0
+            dummy_cli_r = 0
+            FacilityModelBuilder.add_backup_covering_constraint(
+                dummy_class,
+                dummy_class.problem,
+                dummy_p_facility,
+                dummy_fac_r,
+                dummy_cli_r,
+            )