example_sim_call_center_series.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Different aspects of a complex call center model"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Importing modules"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Data collection\n",
    "import pandas as pd\n",
    "\n",
    "# Plotting modules\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib.ticker as formater\n",
    "import seaborn as sns\n",
    "\n",
    "# Simulation\n",
    "from queuesim import SimProcess, run_parallel\n",
    "from queuesim.models import impatience_and_retry_model_build\n",
    "\n",
    "# Analytic calcution\n",
    "from queuesim.analytic import erlang_c_table, erlang_c_ext_table\n",
    "\n",
    "# Defining general plot style\n",
    "sns.set()\n",
    "percent_formater = formater.PercentFormatter(xmax=1, decimals=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Optional: Interactive diagram mode\n",
    "# Run \"pip install ipympl\" first\n",
    "# %matplotlib ipympl"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Impatience of the callers"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Mean inter-arrival time\n",
    "mean_i = 100\n",
    "\n",
    "# Mean service time\n",
    "mean_s_range = range(60, 121, 2)\n",
    "\n",
    "# Mean waiting time tolerance range\n",
    "mean_wt = 300\n",
    "\n",
    "# Number of operators\n",
    "c = 1\n",
    "\n",
    "# Number of arrivals to be simulated\n",
    "count = 100_000"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Simulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "31 parallel processes started.\n",
      "All processes terminated, runtime: 12.4 seconds.\n",
      "Results have been collected.\n"
     ]
    }
   ],
   "source": [
    "models, simulators = run_parallel([SimProcess(impatience_and_retry_model_build(mean_i, mean_s, mean_wt, 0, 1, c, count)) for mean_s in mean_s_range])"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Processing results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mu</th>\n",
       "      <th>rho_offered</th>\n",
       "      <th>E[N_Q]</th>\n",
       "      <th>E[N]</th>\n",
       "      <th>E[W]</th>\n",
       "      <th>E[V]</th>\n",
       "      <th>P(A)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.016667</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.437283</td>\n",
       "      <td>0.964680</td>\n",
       "      <td>38.783468</td>\n",
       "      <td>91.310927</td>\n",
       "      <td>0.12832</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.016129</td>\n",
       "      <td>0.62</td>\n",
       "      <td>0.449204</td>\n",
       "      <td>0.984604</td>\n",
       "      <td>39.782060</td>\n",
       "      <td>93.309424</td>\n",
       "      <td>0.13362</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.015625</td>\n",
       "      <td>0.64</td>\n",
       "      <td>0.488262</td>\n",
       "      <td>1.038611</td>\n",
       "      <td>43.122392</td>\n",
       "      <td>98.048840</td>\n",
       "      <td>0.14135</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.015152</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.514738</td>\n",
       "      <td>1.077735</td>\n",
       "      <td>45.411459</td>\n",
       "      <td>101.661880</td>\n",
       "      <td>0.15204</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.014706</td>\n",
       "      <td>0.68</td>\n",
       "      <td>0.531298</td>\n",
       "      <td>1.104389</td>\n",
       "      <td>47.027320</td>\n",
       "      <td>104.562312</td>\n",
       "      <td>0.15666</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.014286</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.557929</td>\n",
       "      <td>1.141968</td>\n",
       "      <td>49.087097</td>\n",
       "      <td>107.493609</td>\n",
       "      <td>0.16331</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.013889</td>\n",
       "      <td>0.72</td>\n",
       "      <td>0.599320</td>\n",
       "      <td>1.196417</td>\n",
       "      <td>52.356973</td>\n",
       "      <td>111.712709</td>\n",
       "      <td>0.17447</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.013514</td>\n",
       "      <td>0.74</td>\n",
       "      <td>0.617025</td>\n",
       "      <td>1.224142</td>\n",
       "      <td>54.007902</td>\n",
       "      <td>114.715033</td>\n",
       "      <td>0.17986</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.013158</td>\n",
       "      <td>0.76</td>\n",
       "      <td>0.648342</td>\n",
       "      <td>1.266020</td>\n",
       "      <td>56.685393</td>\n",
       "      <td>118.410822</td>\n",
       "      <td>0.18857</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.012821</td>\n",
       "      <td>0.78</td>\n",
       "      <td>0.679703</td>\n",
       "      <td>1.306832</td>\n",
       "      <td>59.251363</td>\n",
       "      <td>121.780475</td>\n",
       "      <td>0.19545</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.012500</td>\n",
       "      <td>0.80</td>\n",
       "      <td>0.711415</td>\n",
       "      <td>1.351002</td>\n",
       "      <td>61.538216</td>\n",
       "      <td>125.132458</td>\n",
       "      <td>0.20582</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.012195</td>\n",
       "      <td>0.82</td>\n",
       "      <td>0.735320</td>\n",
       "      <td>1.383585</td>\n",
       "      <td>63.933253</td>\n",
       "      <td>128.829339</td>\n",
       "      <td>0.21435</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.011905</td>\n",
       "      <td>0.84</td>\n",
       "      <td>0.748274</td>\n",
       "      <td>1.402282</td>\n",
       "      <td>65.139642</td>\n",
       "      <td>130.717415</td>\n",
       "      <td>0.21756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.011628</td>\n",
       "      <td>0.86</td>\n",
       "      <td>0.782022</td>\n",
       "      <td>1.445667</td>\n",
       "      <td>67.693244</td>\n",
       "      <td>134.129490</td>\n",
       "      <td>0.22745</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.011364</td>\n",
       "      <td>0.88</td>\n",
       "      <td>0.809071</td>\n",
       "      <td>1.479985</td>\n",
       "      <td>69.989883</td>\n",
       "      <td>137.048231</td>\n",
       "      <td>0.23241</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.011111</td>\n",
       "      <td>0.90</td>\n",
       "      <td>0.848512</td>\n",
       "      <td>1.533694</td>\n",
       "      <td>73.071162</td>\n",
       "      <td>141.516209</td>\n",
       "      <td>0.24413</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.010870</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.873682</td>\n",
       "      <td>1.565566</td>\n",
       "      <td>75.463512</td>\n",
       "      <td>144.806882</td>\n",
       "      <td>0.25079</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.010638</td>\n",
       "      <td>0.94</td>\n",
       "      <td>0.896939</td>\n",
       "      <td>1.596703</td>\n",
       "      <td>77.110364</td>\n",
       "      <td>147.040004</td>\n",
       "      <td>0.25638</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.010417</td>\n",
       "      <td>0.96</td>\n",
       "      <td>0.933436</td>\n",
       "      <td>1.642691</td>\n",
       "      <td>80.047126</td>\n",
       "      <td>150.673489</td>\n",
       "      <td>0.26478</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.010204</td>\n",
       "      <td>0.98</td>\n",
       "      <td>0.948425</td>\n",
       "      <td>1.661516</td>\n",
       "      <td>81.552622</td>\n",
       "      <td>152.971103</td>\n",
       "      <td>0.27242</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.010000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>0.965739</td>\n",
       "      <td>1.686545</td>\n",
       "      <td>82.847342</td>\n",
       "      <td>154.987489</td>\n",
       "      <td>0.27832</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0.009804</td>\n",
       "      <td>1.02</td>\n",
       "      <td>1.004606</td>\n",
       "      <td>1.735123</td>\n",
       "      <td>85.892415</td>\n",
       "      <td>158.873486</td>\n",
       "      <td>0.28544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0.009615</td>\n",
       "      <td>1.04</td>\n",
       "      <td>1.027547</td>\n",
       "      <td>1.760657</td>\n",
       "      <td>88.026459</td>\n",
       "      <td>161.466799</td>\n",
       "      <td>0.29406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.009434</td>\n",
       "      <td>1.06</td>\n",
       "      <td>1.055779</td>\n",
       "      <td>1.794189</td>\n",
       "      <td>90.355427</td>\n",
       "      <td>164.488024</td>\n",
       "      <td>0.30320</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0.009259</td>\n",
       "      <td>1.08</td>\n",
       "      <td>1.082078</td>\n",
       "      <td>1.828237</td>\n",
       "      <td>92.203167</td>\n",
       "      <td>166.907184</td>\n",
       "      <td>0.30883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.009091</td>\n",
       "      <td>1.10</td>\n",
       "      <td>1.108475</td>\n",
       "      <td>1.861264</td>\n",
       "      <td>94.583666</td>\n",
       "      <td>170.009336</td>\n",
       "      <td>0.31465</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0.008929</td>\n",
       "      <td>1.12</td>\n",
       "      <td>1.139321</td>\n",
       "      <td>1.899749</td>\n",
       "      <td>96.857673</td>\n",
       "      <td>172.895822</td>\n",
       "      <td>0.32063</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.008772</td>\n",
       "      <td>1.14</td>\n",
       "      <td>1.171492</td>\n",
       "      <td>1.938170</td>\n",
       "      <td>99.359101</td>\n",
       "      <td>175.995280</td>\n",
       "      <td>0.32984</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0.008621</td>\n",
       "      <td>1.16</td>\n",
       "      <td>1.182316</td>\n",
       "      <td>1.952896</td>\n",
       "      <td>100.435227</td>\n",
       "      <td>177.749243</td>\n",
       "      <td>0.33573</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.008475</td>\n",
       "      <td>1.18</td>\n",
       "      <td>1.207866</td>\n",
       "      <td>1.982599</td>\n",
       "      <td>102.315136</td>\n",
       "      <td>179.763869</td>\n",
       "      <td>0.34115</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>0.008333</td>\n",
       "      <td>1.20</td>\n",
       "      <td>1.242380</td>\n",
       "      <td>2.025817</td>\n",
       "      <td>105.006222</td>\n",
       "      <td>183.159253</td>\n",
       "      <td>0.34765</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          mu  rho_offered    E[N_Q]      E[N]        E[W]        E[V]     P(A)\n",
       "0   0.016667         0.60  0.437283  0.964680   38.783468   91.310927  0.12832\n",
       "1   0.016129         0.62  0.449204  0.984604   39.782060   93.309424  0.13362\n",
       "2   0.015625         0.64  0.488262  1.038611   43.122392   98.048840  0.14135\n",
       "3   0.015152         0.66  0.514738  1.077735   45.411459  101.661880  0.15204\n",
       "4   0.014706         0.68  0.531298  1.104389   47.027320  104.562312  0.15666\n",
       "5   0.014286         0.70  0.557929  1.141968   49.087097  107.493609  0.16331\n",
       "6   0.013889         0.72  0.599320  1.196417   52.356973  111.712709  0.17447\n",
       "7   0.013514         0.74  0.617025  1.224142   54.007902  114.715033  0.17986\n",
       "8   0.013158         0.76  0.648342  1.266020   56.685393  118.410822  0.18857\n",
       "9   0.012821         0.78  0.679703  1.306832   59.251363  121.780475  0.19545\n",
       "10  0.012500         0.80  0.711415  1.351002   61.538216  125.132458  0.20582\n",
       "11  0.012195         0.82  0.735320  1.383585   63.933253  128.829339  0.21435\n",
       "12  0.011905         0.84  0.748274  1.402282   65.139642  130.717415  0.21756\n",
       "13  0.011628         0.86  0.782022  1.445667   67.693244  134.129490  0.22745\n",
       "14  0.011364         0.88  0.809071  1.479985   69.989883  137.048231  0.23241\n",
       "15  0.011111         0.90  0.848512  1.533694   73.071162  141.516209  0.24413\n",
       "16  0.010870         0.92  0.873682  1.565566   75.463512  144.806882  0.25079\n",
       "17  0.010638         0.94  0.896939  1.596703   77.110364  147.040004  0.25638\n",
       "18  0.010417         0.96  0.933436  1.642691   80.047126  150.673489  0.26478\n",
       "19  0.010204         0.98  0.948425  1.661516   81.552622  152.971103  0.27242\n",
       "20  0.010000         1.00  0.965739  1.686545   82.847342  154.987489  0.27832\n",
       "21  0.009804         1.02  1.004606  1.735123   85.892415  158.873486  0.28544\n",
       "22  0.009615         1.04  1.027547  1.760657   88.026459  161.466799  0.29406\n",
       "23  0.009434         1.06  1.055779  1.794189   90.355427  164.488024  0.30320\n",
       "24  0.009259         1.08  1.082078  1.828237   92.203167  166.907184  0.30883\n",
       "25  0.009091         1.10  1.108475  1.861264   94.583666  170.009336  0.31465\n",
       "26  0.008929         1.12  1.139321  1.899749   96.857673  172.895822  0.32063\n",
       "27  0.008772         1.14  1.171492  1.938170   99.359101  175.995280  0.32984\n",
       "28  0.008621         1.16  1.182316  1.952896  100.435227  177.749243  0.33573\n",
       "29  0.008475         1.18  1.207866  1.982599  102.315136  179.763869  0.34115\n",
       "30  0.008333         1.20  1.242380  2.025817  105.006222  183.159253  0.34765"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mu = [1 / model['meanS'] for model in models]\n",
    "rho_offered = [model['meanS'] / model['meanI'] / model['c'] for model in models]\n",
    "ENQ = [model['Process'].statistic_queue_length.mean for model in models]\n",
    "EN = [model['Process'].statistic_wip.mean for model in models]\n",
    "EW = [model['Dispose'].statistic_client_waiting.mean for model in models]\n",
    "EV = [model['Dispose'].statistic_client_residence.mean for model in models]\n",
    "PA = [1 - model['Process'].statistic_success.data['Success'] / model['Process'].statistic_success.count for model in models]\n",
    "\n",
    "results = pd.DataFrame({'mu': mu, 'rho_offered': rho_offered, 'E[N_Q]': ENQ, 'E[N]': EN, 'E[W]': EW, 'E[V]': EV, 'P(A)': PA})\n",
    "\n",
    "results"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calculating Erlang C formula results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "erlang_c_results = erlang_c_table([(1 / mean_i, mu, c) for mu in results[results[\"rho_offered\"] < 1][\"mu\"]])\n",
    "erlang_c_ext_results = erlang_c_ext_table([(1 / mean_i, mu, 1 / mean_wt, c, c * 100) for mu in results[\"mu\"]])"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plotting results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x23685312a10>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1600x900 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(16, 9))\n",
    "\n",
    "ax.plot(results['rho_offered'], results['E[W]'], 'r', label=\"E[W] simulation results\")\n",
    "ax.plot(erlang_c_results['rho'], erlang_c_results['E[W]'], 'k', label=\"E[W] Erlang C formula results\")\n",
    "ax.plot(erlang_c_ext_results['rho_offered'], erlang_c_ext_results['E[W]'], 'b', label=\"E[W] extended Erlang C formula results\")\n",
    "ax.xaxis.set_major_formatter(percent_formater)\n",
    "ax.set_ylim(0, max(results['E[W]'] * 1.5))\n",
    "ax.set_xlabel(\"Offered utilization\")\n",
    "ax.set_ylabel(\"Mean waiting time E[W]\")\n",
    "lines1, labels1 = ax.get_legend_handles_labels()\n",
    "\n",
    "ax2 = ax.twinx()\n",
    "ax2.plot(results['rho_offered'], results['P(A)'], 'r:', label=\"P(A) simulation results\")\n",
    "ax2.plot(erlang_c_ext_results['rho_offered'], erlang_c_ext_results['P(A)'], 'b:', label=\"P(A) extended Erlang C formula results\")\n",
    "ax2.yaxis.set_major_formatter(percent_formater)\n",
    "ax2.set_ylabel(\"Waiting cancel probability P(A)\")\n",
    "lines2, labels2 = ax2.get_legend_handles_labels()\n",
    "\n",
    "ax.set_title(\"Mean waiting time as a function of the utilization\")\n",
    "ax.legend(lines1 + lines2, labels1 + labels2)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Calculating E[W] using the simple Erlang C formula (not respecting the impatience) gives completely wrong results. So the effect of impatience cannot be ignored. The extended Erlang C formula and the simulation results have a good match. We see the waiting time cancelation probability P(A) is increasing at an increasing offered utilization. The mean waiting time E[W] is also increasing but not in the same magnitude as it would without impatience. If there are waiting time cancelations, the system can also be operated with an offered utilization of more than 100%."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Retry"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Model parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Mean inter-arrival time\n",
    "mean_i = 100\n",
    "\n",
    "# Mean service time\n",
    "mean_s_range = range(60, 121, 2)\n",
    "\n",
    "# Mean waiting time tolerance range\n",
    "mean_wt = 300\n",
    "\n",
    "# Retry\n",
    "retry_probability = 0.2\n",
    "mean_retry_delay = 600\n",
    "\n",
    "# Number of operators\n",
    "c = 1\n",
    "\n",
    "# Number of arrivals to be simulated\n",
    "count = 100_000\n"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Simulation"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "31 parallel processes started.\n",
      "All processes terminated, runtime: 12.6 seconds.\n",
      "Results have been collected.\n"
     ]
    }
   ],
   "source": [
    "models, simulators = run_parallel([SimProcess(impatience_and_retry_model_build(mean_i, mean_s, mean_wt, retry_probability, mean_retry_delay, c, count)) for mean_s in mean_s_range])"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Processing results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>mu</th>\n",
       "      <th>rho_offered</th>\n",
       "      <th>E[N_Q]</th>\n",
       "      <th>E[N]</th>\n",
       "      <th>E[W]</th>\n",
       "      <th>E[V]</th>\n",
       "      <th>P(A)</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0.016667</td>\n",
       "      <td>0.60</td>\n",
       "      <td>0.452359</td>\n",
       "      <td>0.984662</td>\n",
       "      <td>40.554216</td>\n",
       "      <td>93.932469</td>\n",
       "      <td>0.130377</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>0.016129</td>\n",
       "      <td>0.62</td>\n",
       "      <td>0.486537</td>\n",
       "      <td>1.034575</td>\n",
       "      <td>43.226590</td>\n",
       "      <td>98.005732</td>\n",
       "      <td>0.141524</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>0.015625</td>\n",
       "      <td>0.64</td>\n",
       "      <td>0.508825</td>\n",
       "      <td>1.069184</td>\n",
       "      <td>45.366063</td>\n",
       "      <td>101.587624</td>\n",
       "      <td>0.145652</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.015152</td>\n",
       "      <td>0.66</td>\n",
       "      <td>0.549981</td>\n",
       "      <td>1.125013</td>\n",
       "      <td>48.500077</td>\n",
       "      <td>105.807534</td>\n",
       "      <td>0.157802</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.014706</td>\n",
       "      <td>0.68</td>\n",
       "      <td>0.571444</td>\n",
       "      <td>1.156958</td>\n",
       "      <td>50.651291</td>\n",
       "      <td>109.301413</td>\n",
       "      <td>0.163750</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>0.014286</td>\n",
       "      <td>0.70</td>\n",
       "      <td>0.605763</td>\n",
       "      <td>1.204653</td>\n",
       "      <td>53.518630</td>\n",
       "      <td>113.437496</td>\n",
       "      <td>0.173529</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>0.013889</td>\n",
       "      <td>0.72</td>\n",
       "      <td>0.651309</td>\n",
       "      <td>1.264585</td>\n",
       "      <td>57.422691</td>\n",
       "      <td>118.764652</td>\n",
       "      <td>0.183993</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>0.013514</td>\n",
       "      <td>0.74</td>\n",
       "      <td>0.667919</td>\n",
       "      <td>1.288200</td>\n",
       "      <td>58.756558</td>\n",
       "      <td>120.860843</td>\n",
       "      <td>0.188581</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>0.013158</td>\n",
       "      <td>0.76</td>\n",
       "      <td>0.712261</td>\n",
       "      <td>1.347645</td>\n",
       "      <td>62.347296</td>\n",
       "      <td>125.726146</td>\n",
       "      <td>0.200306</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>0.012821</td>\n",
       "      <td>0.78</td>\n",
       "      <td>0.747595</td>\n",
       "      <td>1.391005</td>\n",
       "      <td>65.280939</td>\n",
       "      <td>129.267031</td>\n",
       "      <td>0.209741</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>0.012500</td>\n",
       "      <td>0.80</td>\n",
       "      <td>0.784169</td>\n",
       "      <td>1.442449</td>\n",
       "      <td>68.403020</td>\n",
       "      <td>133.991452</td>\n",
       "      <td>0.216240</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>0.012195</td>\n",
       "      <td>0.82</td>\n",
       "      <td>0.807095</td>\n",
       "      <td>1.473668</td>\n",
       "      <td>70.253941</td>\n",
       "      <td>136.633790</td>\n",
       "      <td>0.223679</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>0.011905</td>\n",
       "      <td>0.84</td>\n",
       "      <td>0.845007</td>\n",
       "      <td>1.517720</td>\n",
       "      <td>74.328424</td>\n",
       "      <td>141.872870</td>\n",
       "      <td>0.234042</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>0.011628</td>\n",
       "      <td>0.86</td>\n",
       "      <td>0.876196</td>\n",
       "      <td>1.563418</td>\n",
       "      <td>76.179408</td>\n",
       "      <td>144.820684</td>\n",
       "      <td>0.242997</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>0.011364</td>\n",
       "      <td>0.88</td>\n",
       "      <td>0.900904</td>\n",
       "      <td>1.594821</td>\n",
       "      <td>78.593203</td>\n",
       "      <td>148.281376</td>\n",
       "      <td>0.249406</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>0.011111</td>\n",
       "      <td>0.90</td>\n",
       "      <td>0.955359</td>\n",
       "      <td>1.663547</td>\n",
       "      <td>82.358185</td>\n",
       "      <td>152.692725</td>\n",
       "      <td>0.261847</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>0.010870</td>\n",
       "      <td>0.92</td>\n",
       "      <td>0.967260</td>\n",
       "      <td>1.677934</td>\n",
       "      <td>83.981804</td>\n",
       "      <td>155.041757</td>\n",
       "      <td>0.266067</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>0.010638</td>\n",
       "      <td>0.94</td>\n",
       "      <td>1.012988</td>\n",
       "      <td>1.735695</td>\n",
       "      <td>87.897895</td>\n",
       "      <td>160.397908</td>\n",
       "      <td>0.276020</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>0.010417</td>\n",
       "      <td>0.96</td>\n",
       "      <td>1.055727</td>\n",
       "      <td>1.790335</td>\n",
       "      <td>90.891748</td>\n",
       "      <td>163.975842</td>\n",
       "      <td>0.287283</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>0.010204</td>\n",
       "      <td>0.98</td>\n",
       "      <td>1.066018</td>\n",
       "      <td>1.799176</td>\n",
       "      <td>92.449255</td>\n",
       "      <td>165.888745</td>\n",
       "      <td>0.289715</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>0.010000</td>\n",
       "      <td>1.00</td>\n",
       "      <td>1.116938</td>\n",
       "      <td>1.866071</td>\n",
       "      <td>96.082750</td>\n",
       "      <td>170.688037</td>\n",
       "      <td>0.300072</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>0.009804</td>\n",
       "      <td>1.02</td>\n",
       "      <td>1.165065</td>\n",
       "      <td>1.922580</td>\n",
       "      <td>99.526987</td>\n",
       "      <td>174.593822</td>\n",
       "      <td>0.312541</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>0.009615</td>\n",
       "      <td>1.04</td>\n",
       "      <td>1.185624</td>\n",
       "      <td>1.947551</td>\n",
       "      <td>101.834262</td>\n",
       "      <td>177.729765</td>\n",
       "      <td>0.317035</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>0.009434</td>\n",
       "      <td>1.06</td>\n",
       "      <td>1.195599</td>\n",
       "      <td>1.958402</td>\n",
       "      <td>103.318958</td>\n",
       "      <td>179.934869</td>\n",
       "      <td>0.320920</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>0.009259</td>\n",
       "      <td>1.08</td>\n",
       "      <td>1.252147</td>\n",
       "      <td>2.023579</td>\n",
       "      <td>107.603225</td>\n",
       "      <td>184.585897</td>\n",
       "      <td>0.333054</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>0.009091</td>\n",
       "      <td>1.10</td>\n",
       "      <td>1.285112</td>\n",
       "      <td>2.063210</td>\n",
       "      <td>110.111866</td>\n",
       "      <td>187.640154</td>\n",
       "      <td>0.341477</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>0.008929</td>\n",
       "      <td>1.12</td>\n",
       "      <td>1.308188</td>\n",
       "      <td>2.095032</td>\n",
       "      <td>111.949075</td>\n",
       "      <td>190.355860</td>\n",
       "      <td>0.346542</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>0.008772</td>\n",
       "      <td>1.14</td>\n",
       "      <td>1.327022</td>\n",
       "      <td>2.118273</td>\n",
       "      <td>113.327679</td>\n",
       "      <td>192.229524</td>\n",
       "      <td>0.354588</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>0.008621</td>\n",
       "      <td>1.16</td>\n",
       "      <td>1.340664</td>\n",
       "      <td>2.134913</td>\n",
       "      <td>115.073938</td>\n",
       "      <td>194.782471</td>\n",
       "      <td>0.359138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>0.008475</td>\n",
       "      <td>1.18</td>\n",
       "      <td>1.380330</td>\n",
       "      <td>2.181864</td>\n",
       "      <td>118.533169</td>\n",
       "      <td>199.070594</td>\n",
       "      <td>0.367462</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>30</th>\n",
       "      <td>0.008333</td>\n",
       "      <td>1.20</td>\n",
       "      <td>1.438062</td>\n",
       "      <td>2.248014</td>\n",
       "      <td>122.419182</td>\n",
       "      <td>203.143224</td>\n",
       "      <td>0.378087</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          mu  rho_offered    E[N_Q]      E[N]        E[W]        E[V]  \\\n",
       "0   0.016667         0.60  0.452359  0.984662   40.554216   93.932469   \n",
       "1   0.016129         0.62  0.486537  1.034575   43.226590   98.005732   \n",
       "2   0.015625         0.64  0.508825  1.069184   45.366063  101.587624   \n",
       "3   0.015152         0.66  0.549981  1.125013   48.500077  105.807534   \n",
       "4   0.014706         0.68  0.571444  1.156958   50.651291  109.301413   \n",
       "5   0.014286         0.70  0.605763  1.204653   53.518630  113.437496   \n",
       "6   0.013889         0.72  0.651309  1.264585   57.422691  118.764652   \n",
       "7   0.013514         0.74  0.667919  1.288200   58.756558  120.860843   \n",
       "8   0.013158         0.76  0.712261  1.347645   62.347296  125.726146   \n",
       "9   0.012821         0.78  0.747595  1.391005   65.280939  129.267031   \n",
       "10  0.012500         0.80  0.784169  1.442449   68.403020  133.991452   \n",
       "11  0.012195         0.82  0.807095  1.473668   70.253941  136.633790   \n",
       "12  0.011905         0.84  0.845007  1.517720   74.328424  141.872870   \n",
       "13  0.011628         0.86  0.876196  1.563418   76.179408  144.820684   \n",
       "14  0.011364         0.88  0.900904  1.594821   78.593203  148.281376   \n",
       "15  0.011111         0.90  0.955359  1.663547   82.358185  152.692725   \n",
       "16  0.010870         0.92  0.967260  1.677934   83.981804  155.041757   \n",
       "17  0.010638         0.94  1.012988  1.735695   87.897895  160.397908   \n",
       "18  0.010417         0.96  1.055727  1.790335   90.891748  163.975842   \n",
       "19  0.010204         0.98  1.066018  1.799176   92.449255  165.888745   \n",
       "20  0.010000         1.00  1.116938  1.866071   96.082750  170.688037   \n",
       "21  0.009804         1.02  1.165065  1.922580   99.526987  174.593822   \n",
       "22  0.009615         1.04  1.185624  1.947551  101.834262  177.729765   \n",
       "23  0.009434         1.06  1.195599  1.958402  103.318958  179.934869   \n",
       "24  0.009259         1.08  1.252147  2.023579  107.603225  184.585897   \n",
       "25  0.009091         1.10  1.285112  2.063210  110.111866  187.640154   \n",
       "26  0.008929         1.12  1.308188  2.095032  111.949075  190.355860   \n",
       "27  0.008772         1.14  1.327022  2.118273  113.327679  192.229524   \n",
       "28  0.008621         1.16  1.340664  2.134913  115.073938  194.782471   \n",
       "29  0.008475         1.18  1.380330  2.181864  118.533169  199.070594   \n",
       "30  0.008333         1.20  1.438062  2.248014  122.419182  203.143224   \n",
       "\n",
       "        P(A)  \n",
       "0   0.130377  \n",
       "1   0.141524  \n",
       "2   0.145652  \n",
       "3   0.157802  \n",
       "4   0.163750  \n",
       "5   0.173529  \n",
       "6   0.183993  \n",
       "7   0.188581  \n",
       "8   0.200306  \n",
       "9   0.209741  \n",
       "10  0.216240  \n",
       "11  0.223679  \n",
       "12  0.234042  \n",
       "13  0.242997  \n",
       "14  0.249406  \n",
       "15  0.261847  \n",
       "16  0.266067  \n",
       "17  0.276020  \n",
       "18  0.287283  \n",
       "19  0.289715  \n",
       "20  0.300072  \n",
       "21  0.312541  \n",
       "22  0.317035  \n",
       "23  0.320920  \n",
       "24  0.333054  \n",
       "25  0.341477  \n",
       "26  0.346542  \n",
       "27  0.354588  \n",
       "28  0.359138  \n",
       "29  0.367462  \n",
       "30  0.378087  "
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "mu = [1 / model['meanS'] for model in models]\n",
    "rho_offered = [model['meanS'] / model['meanI'] / model['c'] for model in models]\n",
    "ENQ = [model['Process'].statistic_queue_length.mean for model in models]\n",
    "EN = [model['Process'].statistic_wip.mean for model in models]\n",
    "EW = [model['Dispose'].statistic_client_waiting.mean for model in models]\n",
    "EV = [model['Dispose'].statistic_client_residence.mean for model in models]\n",
    "PA = [1 - model['Process'].statistic_success.data['Success'] / model['Process'].statistic_success.count for model in models]\n",
    "\n",
    "results = pd.DataFrame({'mu': mu, 'rho_offered': rho_offered, 'E[N_Q]': ENQ, 'E[N]': EN, 'E[W]': EW, 'E[V]': EV, 'P(A)': PA})\n",
    "\n",
    "results"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calculating Erlang C formula results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "erlang_c_ext_results = erlang_c_ext_table([(1 / mean_i, mu, 1 / mean_wt, c, c * 100) for mu in results[\"mu\"]])"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Using the simple Erlang C formula was already in the model above no good idea anymore. So when adding also retry, we have left of the simple Erlang C formula here. The extended Erlang C formula can handle impatience but no retry. So deviations between the simulation and the formula results can be expected."
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Plotting results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.legend.Legend at 0x236842a0dd0>"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1600x900 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, ax = plt.subplots(figsize=(16, 9))\n",
    "\n",
    "ax.plot(results['rho_offered'], results['E[W]'], 'r', label=\"E[W] simulation results\")\n",
    "ax.plot(erlang_c_ext_results['rho_offered'], erlang_c_ext_results['E[W]'], 'b', label=\"E[W] extended Erlang C formula results\")\n",
    "ax.xaxis.set_major_formatter(percent_formater)\n",
    "ax.set_ylim(0, max(results['E[W]'] * 1.5))\n",
    "ax.set_xlabel(\"Offered utilization\")\n",
    "ax.set_ylabel(\"Mean waiting time E[W]\")\n",
    "lines1, labels1 = ax.get_legend_handles_labels()\n",
    "\n",
    "ax2 = ax.twinx()\n",
    "ax2.plot(results['rho_offered'], results['P(A)'], 'r:', label=\"P(A) simulation results\")\n",
    "ax2.plot(erlang_c_ext_results['rho_offered'], erlang_c_ext_results['P(A)'], 'b:', label=\"P(A) extended Erlang C formula results\")\n",
    "ax2.yaxis.set_major_formatter(percent_formater)\n",
    "ax2.set_ylabel(\"Waiting cancel probability P(A)\")\n",
    "lines2, labels2 = ax2.get_legend_handles_labels()\n",
    "\n",
    "ax.set_title(\"Mean waiting time as a function of the utilization\")\n",
    "ax.legend(lines1 + lines2, labels1 + labels2)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Only 20% of the callers who have canceled waiting are staring a new call attempt later. This increases the average waiting times as can be seen significantly compared to the results of the extended Erlang C formula (which does not map retry)."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.11.0"
  },
  "orig_nbformat": 4
 },
 "nbformat": 4,
 "nbformat_minor": 2
}