{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Päivitetty 2025-08-26 / Aki Taanila\n"
     ]
    }
   ],
   "source": [
    "from datetime import datetime\n",
    "print(f'Päivitetty {datetime.now().date()} / Aki Taanila')"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Asiakaspalvelupisteen simulointi\n",
    "\n",
    "Asiakaspalvelupisteen jonon muodostukseen vaikuttaa kaksi tekijää:\n",
    "\n",
    "- Asiakkaiden saapuminen palvelupisteeseen.\n",
    "- Palvelun kesto.\n",
    "\n",
    "Asiakkaiden saapumista voidaan monissa tapauksissa mallintaa onnistuneesti eksponentiaalisella jakaumalla. Tällöin tarvitaan tieto siitä, kuinka paljon asiakkaita saapuu keskimäärin tarkasteltavassa aikavälissä.\n",
    "\n",
    "Palvelun kestoa voidaan monissa tapauksissa mallintaa onnistuneesti normaalijakaumalla. Tällöin tarvitaan palveluajan keskiarvo ja keskihajonta."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "KESKIARVO_ASIAKAS = 5 #asiakkaiden väli minuutteina\n",
    "KESKIARVO_PALVELU = 2 #minuuttia\n",
    "KESKIHAJONTA_PALVELU = 0.5\n",
    "ASIAKKAITA = 1000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "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>seuraava_asiakas</th>\n",
       "      <th>saapumis_aika</th>\n",
       "      <th>palvelun_kesto</th>\n",
       "      <th>palvelun_aloitus</th>\n",
       "      <th>palvelun_lopetus</th>\n",
       "      <th>jonotus</th>\n",
       "      <th>kokonais_aika</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>1.958794</td>\n",
       "      <td>1.958794</td>\n",
       "      <td>2.579687</td>\n",
       "      <td>1.958794</td>\n",
       "      <td>4.538481</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.579687</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>6.997735</td>\n",
       "      <td>8.956529</td>\n",
       "      <td>1.406137</td>\n",
       "      <td>8.956529</td>\n",
       "      <td>10.362666</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.406137</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>1.839778</td>\n",
       "      <td>10.796307</td>\n",
       "      <td>1.093231</td>\n",
       "      <td>10.796307</td>\n",
       "      <td>11.889538</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.093231</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>0.994624</td>\n",
       "      <td>11.790931</td>\n",
       "      <td>2.324703</td>\n",
       "      <td>11.889538</td>\n",
       "      <td>14.214241</td>\n",
       "      <td>0.098607</td>\n",
       "      <td>2.423310</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0.485868</td>\n",
       "      <td>12.276799</td>\n",
       "      <td>2.793450</td>\n",
       "      <td>14.214241</td>\n",
       "      <td>17.007691</td>\n",
       "      <td>1.937442</td>\n",
       "      <td>4.730892</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",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>995</th>\n",
       "      <td>0.152206</td>\n",
       "      <td>5229.004513</td>\n",
       "      <td>1.559721</td>\n",
       "      <td>5231.021350</td>\n",
       "      <td>5232.581071</td>\n",
       "      <td>2.016837</td>\n",
       "      <td>3.576558</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>996</th>\n",
       "      <td>0.861298</td>\n",
       "      <td>5229.865811</td>\n",
       "      <td>1.340054</td>\n",
       "      <td>5232.581071</td>\n",
       "      <td>5233.921125</td>\n",
       "      <td>2.715260</td>\n",
       "      <td>4.055314</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>997</th>\n",
       "      <td>1.068574</td>\n",
       "      <td>5230.934385</td>\n",
       "      <td>1.818091</td>\n",
       "      <td>5233.921125</td>\n",
       "      <td>5235.739216</td>\n",
       "      <td>2.986740</td>\n",
       "      <td>4.804831</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>998</th>\n",
       "      <td>4.659112</td>\n",
       "      <td>5235.593497</td>\n",
       "      <td>1.024468</td>\n",
       "      <td>5235.739216</td>\n",
       "      <td>5236.763684</td>\n",
       "      <td>0.145719</td>\n",
       "      <td>1.170187</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>999</th>\n",
       "      <td>0.269651</td>\n",
       "      <td>5235.863147</td>\n",
       "      <td>1.567194</td>\n",
       "      <td>5236.763684</td>\n",
       "      <td>5238.330877</td>\n",
       "      <td>0.900536</td>\n",
       "      <td>2.467730</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>1000 rows × 7 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "     seuraava_asiakas  saapumis_aika  palvelun_kesto  palvelun_aloitus  \\\n",
       "0            1.958794       1.958794        2.579687          1.958794   \n",
       "1            6.997735       8.956529        1.406137          8.956529   \n",
       "2            1.839778      10.796307        1.093231         10.796307   \n",
       "3            0.994624      11.790931        2.324703         11.889538   \n",
       "4            0.485868      12.276799        2.793450         14.214241   \n",
       "..                ...            ...             ...               ...   \n",
       "995          0.152206    5229.004513        1.559721       5231.021350   \n",
       "996          0.861298    5229.865811        1.340054       5232.581071   \n",
       "997          1.068574    5230.934385        1.818091       5233.921125   \n",
       "998          4.659112    5235.593497        1.024468       5235.739216   \n",
       "999          0.269651    5235.863147        1.567194       5236.763684   \n",
       "\n",
       "     palvelun_lopetus   jonotus  kokonais_aika  \n",
       "0            4.538481  0.000000       2.579687  \n",
       "1           10.362666  0.000000       1.406137  \n",
       "2           11.889538  0.000000       1.093231  \n",
       "3           14.214241  0.098607       2.423310  \n",
       "4           17.007691  1.937442       4.730892  \n",
       "..                ...       ...            ...  \n",
       "995       5232.581071  2.016837       3.576558  \n",
       "996       5233.921125  2.715260       4.055314  \n",
       "997       5235.739216  2.986740       4.804831  \n",
       "998       5236.763684  0.145719       1.170187  \n",
       "999       5238.330877  0.900536       2.467730  \n",
       "\n",
       "[1000 rows x 7 columns]"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Alustan satunnaislukugeneraattorin:\n",
    "rng = np.random.default_rng()\n",
    "\n",
    "simulointi = pd.DataFrame(index = range(ASIAKKAITA))\n",
    "simulointi['seuraava_asiakas'] = rng.exponential(KESKIARVO_ASIAKAS, size=ASIAKKAITA)\n",
    "\n",
    "simulointi['saapumis_aika'] = simulointi['seuraava_asiakas'].cumsum()\n",
    "simulointi['palvelun_kesto'] = rng.normal(loc = KESKIARVO_PALVELU, scale = KESKIHAJONTA_PALVELU,\n",
    "                                               size = ASIAKKAITA)\n",
    "\n",
    "simulointi['palvelun_aloitus'] = simulointi['saapumis_aika']\n",
    "simulointi['palvelun_lopetus'] = simulointi['saapumis_aika'] + simulointi['palvelun_kesto']\n",
    "\n",
    "for i in range(1, len(simulointi)):\n",
    "    if simulointi.loc[i, 'saapumis_aika'] < simulointi.loc[i-1, 'palvelun_lopetus']:\n",
    "        simulointi.loc[i, 'palvelun_aloitus'] = simulointi.loc[i-1,'palvelun_lopetus']\n",
    "    simulointi['palvelun_lopetus'] = simulointi['palvelun_aloitus'] + simulointi['palvelun_kesto']\n",
    "    \n",
    "simulointi['jonotus'] = simulointi['palvelun_aloitus'] - simulointi['saapumis_aika']\n",
    "simulointi['kokonais_aika'] = simulointi['jonotus'] + simulointi['palvelun_kesto']\n",
    "simulointi"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "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>jonotus</th>\n",
       "      <th>kokonais_aika</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1000.000000</td>\n",
       "      <td>1000.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>0.605394</td>\n",
       "      <td>2.574680</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>1.026023</td>\n",
       "      <td>1.138684</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.406923</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>1.817784</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>2.294527</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>1.032675</td>\n",
       "      <td>3.058039</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>6.995624</td>\n",
       "      <td>8.502975</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "           jonotus  kokonais_aika\n",
       "count  1000.000000    1000.000000\n",
       "mean      0.605394       2.574680\n",
       "std       1.026023       1.138684\n",
       "min       0.000000       0.406923\n",
       "25%       0.000000       1.817784\n",
       "50%       0.000000       2.294527\n",
       "75%       1.032675       3.058039\n",
       "max       6.995624       8.502975"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "simulointi[['jonotus', 'kokonais_aika']].describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: >"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Tästä näkee nousevana trendinä, jos jono kasvaa ajan kuluessa\n",
    "simulointi[['jonotus', 'kokonais_aika']].plot()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([<Axes: ylabel='Frequency'>, <Axes: ylabel='Frequency'>],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "simulointi[['kokonais_aika', 'jonotus']].plot.hist(subplots=True, sharex=True, sharey=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lisätietoa satunnaislukujen tuottamisesta: https://numpy.org/doc/stable/reference/random/index.html"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "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": "3.13.2"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}