268 lines
9.7 KiB
Plaintext
268 lines
9.7 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "google",
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"metadata": {},
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"source": [
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"##### Copyright 2022 Google LLC."
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]
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},
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{
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"cell_type": "markdown",
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"id": "apache",
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"metadata": {},
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"source": [
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"Licensed under the Apache License, Version 2.0 (the \"License\");\n",
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"you may not use this file except in compliance with the License.\n",
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"You may obtain a copy of the License at\n",
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"\n",
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" http://www.apache.org/licenses/LICENSE-2.0\n",
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"\n",
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"Unless required by applicable law or agreed to in writing, software\n",
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"distributed under the License is distributed on an \"AS IS\" BASIS,\n",
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"WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.\n",
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"See the License for the specific language governing permissions and\n",
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"limitations under the License.\n"
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]
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},
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{
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"cell_type": "markdown",
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"id": "basename",
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"metadata": {},
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"source": [
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"# vrp_pickup_delivery"
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]
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},
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{
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"cell_type": "markdown",
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"id": "link",
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"metadata": {},
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"source": [
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"<table align=\"left\">\n",
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"<td>\n",
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"<a href=\"https://colab.research.google.com/github/google/or-tools/blob/main/examples/notebook/constraint_solver/vrp_pickup_delivery.ipynb\"><img src=\"https://raw.githubusercontent.com/google/or-tools/main/tools/colab_32px.png\"/>Run in Google Colab</a>\n",
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"</td>\n",
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"<td>\n",
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"<a href=\"https://github.com/google/or-tools/blob/main/ortools/constraint_solver/samples/vrp_pickup_delivery.py\"><img src=\"https://raw.githubusercontent.com/google/or-tools/main/tools/github_32px.png\"/>View source on GitHub</a>\n",
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"</td>\n",
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"</table>"
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]
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},
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{
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"cell_type": "markdown",
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"id": "doc",
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"metadata": {},
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"source": [
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"First, you must install [ortools](https://pypi.org/project/ortools/) package in this colab."
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "install",
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"metadata": {},
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"outputs": [],
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"source": [
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"!pip install ortools"
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]
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},
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{
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"cell_type": "markdown",
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"id": "description",
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"metadata": {},
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"source": [
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"\n",
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"Simple Pickup Delivery Problem (PDP).\n"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "code",
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"metadata": {},
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"outputs": [],
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"source": [
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"from ortools.constraint_solver import routing_enums_pb2\n",
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"from ortools.constraint_solver import pywrapcp\n",
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"\n",
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"\n",
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"def create_data_model():\n",
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" \"\"\"Stores the data for the problem.\"\"\"\n",
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" data = {}\n",
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" data['distance_matrix'] = [\n",
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" [\n",
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" 0, 548, 776, 696, 582, 274, 502, 194, 308, 194, 536, 502, 388, 354,\n",
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" 468, 776, 662\n",
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" ],\n",
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" [\n",
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" 548, 0, 684, 308, 194, 502, 730, 354, 696, 742, 1084, 594, 480, 674,\n",
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" 1016, 868, 1210\n",
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" ],\n",
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" [\n",
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" 776, 684, 0, 992, 878, 502, 274, 810, 468, 742, 400, 1278, 1164,\n",
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" 1130, 788, 1552, 754\n",
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" ],\n",
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" [\n",
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" 696, 308, 992, 0, 114, 650, 878, 502, 844, 890, 1232, 514, 628, 822,\n",
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" 1164, 560, 1358\n",
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" ],\n",
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" [\n",
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" 582, 194, 878, 114, 0, 536, 764, 388, 730, 776, 1118, 400, 514, 708,\n",
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" 1050, 674, 1244\n",
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" ],\n",
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" [\n",
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" 274, 502, 502, 650, 536, 0, 228, 308, 194, 240, 582, 776, 662, 628,\n",
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" 514, 1050, 708\n",
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" ],\n",
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" [\n",
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" 502, 730, 274, 878, 764, 228, 0, 536, 194, 468, 354, 1004, 890, 856,\n",
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" 514, 1278, 480\n",
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" ],\n",
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" [\n",
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" 194, 354, 810, 502, 388, 308, 536, 0, 342, 388, 730, 468, 354, 320,\n",
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" 662, 742, 856\n",
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" ],\n",
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" [\n",
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" 308, 696, 468, 844, 730, 194, 194, 342, 0, 274, 388, 810, 696, 662,\n",
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" 320, 1084, 514\n",
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" ],\n",
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" [\n",
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" 194, 742, 742, 890, 776, 240, 468, 388, 274, 0, 342, 536, 422, 388,\n",
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" 274, 810, 468\n",
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" ],\n",
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" [\n",
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" 536, 1084, 400, 1232, 1118, 582, 354, 730, 388, 342, 0, 878, 764,\n",
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" 730, 388, 1152, 354\n",
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" ],\n",
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" [\n",
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" 502, 594, 1278, 514, 400, 776, 1004, 468, 810, 536, 878, 0, 114,\n",
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" 308, 650, 274, 844\n",
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" ],\n",
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" [\n",
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" 388, 480, 1164, 628, 514, 662, 890, 354, 696, 422, 764, 114, 0, 194,\n",
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" 536, 388, 730\n",
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" ],\n",
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" [\n",
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" 354, 674, 1130, 822, 708, 628, 856, 320, 662, 388, 730, 308, 194, 0,\n",
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" 342, 422, 536\n",
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" ],\n",
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" [\n",
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" 468, 1016, 788, 1164, 1050, 514, 514, 662, 320, 274, 388, 650, 536,\n",
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" 342, 0, 764, 194\n",
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" ],\n",
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" [\n",
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" 776, 868, 1552, 560, 674, 1050, 1278, 742, 1084, 810, 1152, 274,\n",
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" 388, 422, 764, 0, 798\n",
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" ],\n",
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" [\n",
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" 662, 1210, 754, 1358, 1244, 708, 480, 856, 514, 468, 354, 844, 730,\n",
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" 536, 194, 798, 0\n",
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" ],\n",
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" ]\n",
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" data['pickups_deliveries'] = [\n",
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" [1, 6],\n",
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" [2, 10],\n",
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" [4, 3],\n",
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" [5, 9],\n",
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" [7, 8],\n",
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" [15, 11],\n",
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" [13, 12],\n",
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" [16, 14],\n",
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" ]\n",
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" data['num_vehicles'] = 4\n",
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" data['depot'] = 0\n",
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" return data\n",
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"\n",
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"\n",
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"def print_solution(data, manager, routing, solution):\n",
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" \"\"\"Prints solution on console.\"\"\"\n",
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" print(f'Objective: {solution.ObjectiveValue()}')\n",
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" total_distance = 0\n",
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" for vehicle_id in range(data['num_vehicles']):\n",
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" index = routing.Start(vehicle_id)\n",
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" plan_output = 'Route for vehicle {}:\\n'.format(vehicle_id)\n",
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" route_distance = 0\n",
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" while not routing.IsEnd(index):\n",
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" plan_output += ' {} -> '.format(manager.IndexToNode(index))\n",
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" previous_index = index\n",
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" index = solution.Value(routing.NextVar(index))\n",
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" route_distance += routing.GetArcCostForVehicle(\n",
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" previous_index, index, vehicle_id)\n",
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" plan_output += '{}\\n'.format(manager.IndexToNode(index))\n",
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" plan_output += 'Distance of the route: {}m\\n'.format(route_distance)\n",
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" print(plan_output)\n",
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" total_distance += route_distance\n",
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" print('Total Distance of all routes: {}m'.format(total_distance))\n",
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"\n",
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"\n",
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"def main():\n",
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" \"\"\"Entry point of the program.\"\"\"\n",
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" # Instantiate the data problem.\n",
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" data = create_data_model()\n",
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"\n",
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" # Create the routing index manager.\n",
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" manager = pywrapcp.RoutingIndexManager(len(data['distance_matrix']),\n",
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" data['num_vehicles'], data['depot'])\n",
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"\n",
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" # Create Routing Model.\n",
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" routing = pywrapcp.RoutingModel(manager)\n",
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"\n",
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"\n",
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" # Define cost of each arc.\n",
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" def distance_callback(from_index, to_index):\n",
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" \"\"\"Returns the manhattan distance between the two nodes.\"\"\"\n",
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" # Convert from routing variable Index to distance matrix NodeIndex.\n",
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" from_node = manager.IndexToNode(from_index)\n",
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" to_node = manager.IndexToNode(to_index)\n",
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" return data['distance_matrix'][from_node][to_node]\n",
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"\n",
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" transit_callback_index = routing.RegisterTransitCallback(distance_callback)\n",
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" routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index)\n",
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"\n",
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" # Add Distance constraint.\n",
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" dimension_name = 'Distance'\n",
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" routing.AddDimension(\n",
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" transit_callback_index,\n",
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" 0, # no slack\n",
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" 3000, # vehicle maximum travel distance\n",
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" True, # start cumul to zero\n",
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" dimension_name)\n",
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" distance_dimension = routing.GetDimensionOrDie(dimension_name)\n",
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" distance_dimension.SetGlobalSpanCostCoefficient(100)\n",
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"\n",
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" # Define Transportation Requests.\n",
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" for request in data['pickups_deliveries']:\n",
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" pickup_index = manager.NodeToIndex(request[0])\n",
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" delivery_index = manager.NodeToIndex(request[1])\n",
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" routing.AddPickupAndDelivery(pickup_index, delivery_index)\n",
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" routing.solver().Add(\n",
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" routing.VehicleVar(pickup_index) == routing.VehicleVar(\n",
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" delivery_index))\n",
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" routing.solver().Add(\n",
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" distance_dimension.CumulVar(pickup_index) <=\n",
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" distance_dimension.CumulVar(delivery_index))\n",
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"\n",
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" # Setting first solution heuristic.\n",
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" search_parameters = pywrapcp.DefaultRoutingSearchParameters()\n",
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" search_parameters.first_solution_strategy = (\n",
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" routing_enums_pb2.FirstSolutionStrategy.PARALLEL_CHEAPEST_INSERTION)\n",
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"\n",
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" # Solve the problem.\n",
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" solution = routing.SolveWithParameters(search_parameters)\n",
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"\n",
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" # Print solution on console.\n",
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" if solution:\n",
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" print_solution(data, manager, routing, solution)\n",
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"\n",
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"\n",
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"main()\n",
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"\n"
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]
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}
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],
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"metadata": {},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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