From 09cfda21a2cba39929709a89520d161aea63f351 Mon Sep 17 00:00:00 2001
From: Luciano Silva do Lago <luciano.slago@gmail.com>
Date: Sun, 7 Jun 2026 20:18:15 -0300
Subject: [PATCH] =?UTF-8?q?refactor:=20nova=20m=C3=A9trica=20PAX=20*=20Dia?=
 =?UTF-8?q?s=5FOperados=20para=20relev=C3=A2ncia=20de=20rotas?=
MIME-Version: 1.0
Content-Type: text/plain; charset=UTF-8
Content-Transfer-Encoding: 8bit

---
 create_nb.py  |  15 ++--
 modelos.ipynb | 198 ++++++++++++++++++++++++++------------------------
 2 files changed, 112 insertions(+), 101 deletions(-)

diff --git a/create_nb.py b/create_nb.py
index b46a105..aec8d42 100644
--- a/create_nb.py
+++ b/create_nb.py
@@ -127,13 +127,16 @@ estatisticas_trechos = demanda_diaria_completa.groupby('Trecho').agg(
     Dias_Operados=('PAX', lambda x: (x > 0).sum())
 ).reset_index()
 
-# Nova métrica: PAX/Dias_Operados (evitando divisão por zero)
+# Média PAX por dias operados (usado para o Fleet Assignment Model)
 estatisticas_trechos['Media_PAX_Dias_Operados'] = estatisticas_trechos.apply(
     lambda row: row['Total_PAX'] / row['Dias_Operados'] if row['Dias_Operados'] > 0 else 0, axis=1
 )
 
-# Ordenar pelas rotas com maior Média PAX por dias operados
-estatisticas_trechos = estatisticas_trechos.sort_values(by='Media_PAX_Dias_Operados', ascending=False)
+# Nova métrica solicitada: PAX * Dias_Operados
+estatisticas_trechos['Score_Relevancia'] = estatisticas_trechos['Total_PAX'] * estatisticas_trechos['Dias_Operados']
+
+# Ordenar pelas rotas com maior métrica (PAX * Dias_Operados)
+estatisticas_trechos = estatisticas_trechos.sort_values(by='Score_Relevancia', ascending=False)
 
 # Definir número de trechos alvo
 NUM_TRECHOS = 5
@@ -143,9 +146,9 @@ display(top_trechos)
 
 # Gráfico
 plt.figure(figsize=(10, 6))
-sns.barplot(data=top_trechos, x='Trecho', y='Media_PAX_Dias_Operados', hue='Trecho', palette='viridis', legend=False)
-plt.title(f'Top {NUM_TRECHOS} Trechos Mais Relevantes (PAX / Dias Operados)')
-plt.ylabel('Média de PAX por Dia Operado')
+sns.barplot(data=top_trechos, x='Trecho', y='Score_Relevancia', hue='Trecho', palette='viridis', legend=False)
+plt.title(f'Top {NUM_TRECHOS} Trechos Mais Relevantes (PAX * Dias Operados)')
+plt.ylabel('Score de Relevância (PAX * Dias Operados)')
 plt.xlabel('Trecho (Origem - Destino)')
 plt.xticks(rotation=45)
 plt.tight_layout()
diff --git a/modelos.ipynb b/modelos.ipynb
index f6618e5..a698730 100644
--- a/modelos.ipynb
+++ b/modelos.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "490738bc",
+   "id": "3814c78f",
    "metadata": {},
    "source": [
     "# Alocação de Frotas (Fleet Scheduling) - Aeronaves C-97\n",
@@ -21,13 +21,13 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "14292d89",
+   "id": "47c2c468",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-06-07T23:16:26.495905Z",
-     "iopub.status.busy": "2026-06-07T23:16:26.495251Z",
-     "iopub.status.idle": "2026-06-07T23:16:26.997172Z",
-     "shell.execute_reply": "2026-06-07T23:16:26.996519Z"
+     "iopub.execute_input": "2026-06-07T23:18:13.940499Z",
+     "iopub.status.busy": "2026-06-07T23:18:13.939868Z",
+     "iopub.status.idle": "2026-06-07T23:18:14.482559Z",
+     "shell.execute_reply": "2026-06-07T23:18:14.481932Z"
     }
    },
    "outputs": [],
@@ -52,7 +52,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "02401ef8",
+   "id": "c61fc14a",
    "metadata": {},
    "source": [
     "## 1. Leitura e Limpeza dos Dados\n",
@@ -62,13 +62,13 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "b18a653b",
+   "id": "132e1793",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-06-07T23:16:26.998926Z",
-     "iopub.status.busy": "2026-06-07T23:16:26.998670Z",
-     "iopub.status.idle": "2026-06-07T23:16:27.370579Z",
-     "shell.execute_reply": "2026-06-07T23:16:27.369986Z"
+     "iopub.execute_input": "2026-06-07T23:18:14.484142Z",
+     "iopub.status.busy": "2026-06-07T23:18:14.483920Z",
+     "iopub.status.idle": "2026-06-07T23:18:14.852925Z",
+     "shell.execute_reply": "2026-06-07T23:18:14.851875Z"
     }
    },
    "outputs": [],
@@ -100,7 +100,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "259a9e7a",
+   "id": "0694381c",
    "metadata": {},
    "source": [
     "## 2. Análise dos Esquadrões e Matrículas (Aeronaves)\n",
@@ -110,13 +110,13 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "409555a8",
+   "id": "8cc5a607",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-06-07T23:16:27.372062Z",
-     "iopub.status.busy": "2026-06-07T23:16:27.371936Z",
-     "iopub.status.idle": "2026-06-07T23:16:27.383786Z",
-     "shell.execute_reply": "2026-06-07T23:16:27.383217Z"
+     "iopub.execute_input": "2026-06-07T23:18:14.854417Z",
+     "iopub.status.busy": "2026-06-07T23:18:14.854270Z",
+     "iopub.status.idle": "2026-06-07T23:18:14.868015Z",
+     "shell.execute_reply": "2026-06-07T23:18:14.867338Z"
     }
    },
    "outputs": [
@@ -175,7 +175,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f4b3847d",
+   "id": "e4c88ec8",
    "metadata": {},
    "source": [
     "## 3. Análise Estatística das Demandas Diárias\n",
@@ -186,13 +186,13 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "07fc4526",
+   "id": "92323d95",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-06-07T23:16:27.385108Z",
-     "iopub.status.busy": "2026-06-07T23:16:27.384987Z",
-     "iopub.status.idle": "2026-06-07T23:16:27.656394Z",
-     "shell.execute_reply": "2026-06-07T23:16:27.655862Z"
+     "iopub.execute_input": "2026-06-07T23:18:14.869527Z",
+     "iopub.status.busy": "2026-06-07T23:18:14.869395Z",
+     "iopub.status.idle": "2026-06-07T23:18:15.140701Z",
+     "shell.execute_reply": "2026-06-07T23:18:15.140134Z"
     }
    },
    "outputs": [
@@ -223,53 +223,59 @@
        "      <th>Total_PAX</th>\n",
        "      <th>Dias_Operados</th>\n",
        "      <th>Media_PAX_Dias_Operados</th>\n",
+       "      <th>Score_Relevancia</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
-       "      <th>303</th>\n",
-       "      <td>SBJU-SBNT</td>\n",
-       "      <td>0.109589</td>\n",
-       "      <td>2.093696</td>\n",
-       "      <td>40.0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>40.0</td>\n",
+       "      <th>223</th>\n",
+       "      <td>SBGL-SBBR</td>\n",
+       "      <td>0.980822</td>\n",
+       "      <td>4.097998</td>\n",
+       "      <td>358.0</td>\n",
+       "      <td>38</td>\n",
+       "      <td>9.421053</td>\n",
+       "      <td>13604.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>149</th>\n",
-       "      <td>SBCJ-SBBE</td>\n",
-       "      <td>0.065753</td>\n",
-       "      <td>1.256217</td>\n",
-       "      <td>24.0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>24.0</td>\n",
+       "      <th>69</th>\n",
+       "      <td>SBBR-SBGL</td>\n",
+       "      <td>0.794521</td>\n",
+       "      <td>3.483710</td>\n",
+       "      <td>290.0</td>\n",
+       "      <td>34</td>\n",
+       "      <td>8.529412</td>\n",
+       "      <td>9860.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>324</th>\n",
-       "      <td>SBMA-SBBR</td>\n",
-       "      <td>0.065753</td>\n",
-       "      <td>1.256217</td>\n",
-       "      <td>24.0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>24.0</td>\n",
+       "      <th>72</th>\n",
+       "      <td>SBBR-SBGR</td>\n",
+       "      <td>0.487671</td>\n",
+       "      <td>2.420831</td>\n",
+       "      <td>178.0</td>\n",
+       "      <td>21</td>\n",
+       "      <td>8.476190</td>\n",
+       "      <td>3738.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>300</th>\n",
-       "      <td>SBJI-SBVH</td>\n",
-       "      <td>0.057534</td>\n",
-       "      <td>1.099190</td>\n",
-       "      <td>21.0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>21.0</td>\n",
+       "      <th>272</th>\n",
+       "      <td>SBGR-SBBR</td>\n",
+       "      <td>0.476712</td>\n",
+       "      <td>2.481277</td>\n",
+       "      <td>174.0</td>\n",
+       "      <td>21</td>\n",
+       "      <td>8.285714</td>\n",
+       "      <td>3654.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
-       "      <th>540</th>\n",
-       "      <td>SBVH-SBBR</td>\n",
-       "      <td>0.057534</td>\n",
-       "      <td>1.099190</td>\n",
-       "      <td>21.0</td>\n",
-       "      <td>1</td>\n",
-       "      <td>21.0</td>\n",
+       "      <th>237</th>\n",
+       "      <td>SBGL-SBGR</td>\n",
+       "      <td>0.460274</td>\n",
+       "      <td>2.575601</td>\n",
+       "      <td>168.0</td>\n",
+       "      <td>19</td>\n",
+       "      <td>8.842105</td>\n",
+       "      <td>3192.0</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
@@ -277,18 +283,18 @@
       ],
       "text/plain": [
        "        Trecho  Media_PAX_Diario  Desvio_Padrao_PAX  Total_PAX  Dias_Operados  \\\n",
-       "303  SBJU-SBNT          0.109589           2.093696       40.0              1   \n",
-       "149  SBCJ-SBBE          0.065753           1.256217       24.0              1   \n",
-       "324  SBMA-SBBR          0.065753           1.256217       24.0              1   \n",
-       "300  SBJI-SBVH          0.057534           1.099190       21.0              1   \n",
-       "540  SBVH-SBBR          0.057534           1.099190       21.0              1   \n",
+       "223  SBGL-SBBR          0.980822           4.097998      358.0             38   \n",
+       "69   SBBR-SBGL          0.794521           3.483710      290.0             34   \n",
+       "72   SBBR-SBGR          0.487671           2.420831      178.0             21   \n",
+       "272  SBGR-SBBR          0.476712           2.481277      174.0             21   \n",
+       "237  SBGL-SBGR          0.460274           2.575601      168.0             19   \n",
        "\n",
-       "     Media_PAX_Dias_Operados  \n",
-       "303                     40.0  \n",
-       "149                     24.0  \n",
-       "324                     24.0  \n",
-       "300                     21.0  \n",
-       "540                     21.0  "
+       "     Media_PAX_Dias_Operados  Score_Relevancia  \n",
+       "223                 9.421053           13604.0  \n",
+       "69                  8.529412            9860.0  \n",
+       "72                  8.476190            3738.0  \n",
+       "272                 8.285714            3654.0  \n",
+       "237                 8.842105            3192.0  "
       ]
      },
      "metadata": {},
@@ -296,7 +302,7 @@
     },
     {
      "data": {
-      "image/png": "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",
+      "image/png": "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",
       "text/plain": [
        "<Figure size 1000x600 with 1 Axes>"
       ]
@@ -327,13 +333,16 @@
     "    Dias_Operados=('PAX', lambda x: (x > 0).sum())\n",
     ").reset_index()\n",
     "\n",
-    "# Nova métrica: PAX/Dias_Operados (evitando divisão por zero)\n",
+    "# Média PAX por dias operados (usado para o Fleet Assignment Model)\n",
     "estatisticas_trechos['Media_PAX_Dias_Operados'] = estatisticas_trechos.apply(\n",
     "    lambda row: row['Total_PAX'] / row['Dias_Operados'] if row['Dias_Operados'] > 0 else 0, axis=1\n",
     ")\n",
     "\n",
-    "# Ordenar pelas rotas com maior Média PAX por dias operados\n",
-    "estatisticas_trechos = estatisticas_trechos.sort_values(by='Media_PAX_Dias_Operados', ascending=False)\n",
+    "# Nova métrica solicitada: PAX * Dias_Operados\n",
+    "estatisticas_trechos['Score_Relevancia'] = estatisticas_trechos['Total_PAX'] * estatisticas_trechos['Dias_Operados']\n",
+    "\n",
+    "# Ordenar pelas rotas com maior métrica (PAX * Dias_Operados)\n",
+    "estatisticas_trechos = estatisticas_trechos.sort_values(by='Score_Relevancia', ascending=False)\n",
     "\n",
     "# Definir número de trechos alvo\n",
     "NUM_TRECHOS = 5\n",
@@ -343,9 +352,9 @@
     "\n",
     "# Gráfico\n",
     "plt.figure(figsize=(10, 6))\n",
-    "sns.barplot(data=top_trechos, x='Trecho', y='Media_PAX_Dias_Operados', hue='Trecho', palette='viridis', legend=False)\n",
-    "plt.title(f'Top {NUM_TRECHOS} Trechos Mais Relevantes (PAX / Dias Operados)')\n",
-    "plt.ylabel('Média de PAX por Dia Operado')\n",
+    "sns.barplot(data=top_trechos, x='Trecho', y='Score_Relevancia', hue='Trecho', palette='viridis', legend=False)\n",
+    "plt.title(f'Top {NUM_TRECHOS} Trechos Mais Relevantes (PAX * Dias Operados)')\n",
+    "plt.ylabel('Score de Relevância (PAX * Dias Operados)')\n",
     "plt.xlabel('Trecho (Origem - Destino)')\n",
     "plt.xticks(rotation=45)\n",
     "plt.tight_layout()\n",
@@ -354,7 +363,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3b70d27a",
+   "id": "9abfe029",
    "metadata": {},
    "source": [
     "## 4. Fleet Assignment Model (FAM)\n",
@@ -371,13 +380,13 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "862dd955",
+   "id": "e7df1520",
    "metadata": {
     "execution": {
-     "iopub.execute_input": "2026-06-07T23:16:27.657968Z",
-     "iopub.status.busy": "2026-06-07T23:16:27.657797Z",
-     "iopub.status.idle": "2026-06-07T23:16:27.763485Z",
-     "shell.execute_reply": "2026-06-07T23:16:27.762884Z"
+     "iopub.execute_input": "2026-06-07T23:18:15.142206Z",
+     "iopub.status.busy": "2026-06-07T23:18:15.142079Z",
+     "iopub.status.idle": "2026-06-07T23:18:15.243488Z",
+     "shell.execute_reply": "2026-06-07T23:18:15.242947Z"
     }
    },
    "outputs": [
@@ -387,25 +396,24 @@
      "text": [
       "== RESULTADO DO FLEET ASSIGNMENT ==\n",
       "Status: Optimal\n",
-      "Distância Total Minimizada: 31712.50 km\n",
+      "Distância Total Minimizada: 7722.27 km\n",
       "\n",
       "Alocações (Voos Diários):\n",
       "\n",
-      "Trecho: SBJU-SBNT (Voos necessários: 2)\n",
-      " -> ETA2 (Base SBNT): 1 voo(s)\n",
+      "Trecho: SBGL-SBBR (Voos necessários: 1)\n",
+      " -> ETA3 (Base SBGL): 1 voo(s)\n",
+      "\n",
+      "Trecho: SBBR-SBGL (Voos necessários: 1)\n",
+      " -> ETA3 (Base SBGL): 1 voo(s)\n",
+      "\n",
+      "Trecho: SBBR-SBGR (Voos necessários: 1)\n",
       " -> ETA6 (Base SBBR): 1 voo(s)\n",
       "\n",
-      "Trecho: SBCJ-SBBE (Voos necessários: 1)\n",
-      " -> ETA1 (Base SBBE): 1 voo(s)\n",
-      "\n",
-      "Trecho: SBMA-SBBR (Voos necessários: 1)\n",
+      "Trecho: SBGR-SBBR (Voos necessários: 1)\n",
       " -> ETA6 (Base SBBR): 1 voo(s)\n",
       "\n",
-      "Trecho: SBJI-SBVH (Voos necessários: 1)\n",
-      " -> ETA7 (Base SBMN): 1 voo(s)\n",
-      "\n",
-      "Trecho: SBVH-SBBR (Voos necessários: 1)\n",
-      " -> ETA6 (Base SBBR): 1 voo(s)\n"
+      "Trecho: SBGL-SBGR (Voos necessários: 1)\n",
+      " -> ETA3 (Base SBGL): 1 voo(s)\n"
      ]
     }
    ],