251 lines
9.9 KiB
Plaintext
251 lines
9.9 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 2023 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_solution_callback"
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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_solution_callback.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_solution_callback.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 Vehicles Routing Problem (VRP).\n",
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"\n",
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" This is a sample using the routing library python wrapper to solve a VRP\n",
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" problem.\n",
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"\n",
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" The solver stop after improving its solution 15 times or after 5 seconds.\n",
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"\n",
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" Distances are in meters.\n",
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"\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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" # fmt: off\n",
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" [0, 548, 776, 696, 582, 274, 502, 194, 308, 194, 536, 502, 388, 354, 468, 776, 662],\n",
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" [548, 0, 684, 308, 194, 502, 730, 354, 696, 742, 1084, 594, 480, 674, 1016, 868, 1210],\n",
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" [776, 684, 0, 992, 878, 502, 274, 810, 468, 742, 400, 1278, 1164, 1130, 788, 1552, 754],\n",
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" [696, 308, 992, 0, 114, 650, 878, 502, 844, 890, 1232, 514, 628, 822, 1164, 560, 1358],\n",
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" [582, 194, 878, 114, 0, 536, 764, 388, 730, 776, 1118, 400, 514, 708, 1050, 674, 1244],\n",
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" [274, 502, 502, 650, 536, 0, 228, 308, 194, 240, 582, 776, 662, 628, 514, 1050, 708],\n",
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" [502, 730, 274, 878, 764, 228, 0, 536, 194, 468, 354, 1004, 890, 856, 514, 1278, 480],\n",
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" [194, 354, 810, 502, 388, 308, 536, 0, 342, 388, 730, 468, 354, 320, 662, 742, 856],\n",
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" [308, 696, 468, 844, 730, 194, 194, 342, 0, 274, 388, 810, 696, 662, 320, 1084, 514],\n",
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" [194, 742, 742, 890, 776, 240, 468, 388, 274, 0, 342, 536, 422, 388, 274, 810, 468],\n",
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" [536, 1084, 400, 1232, 1118, 582, 354, 730, 388, 342, 0, 878, 764, 730, 388, 1152, 354],\n",
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" [502, 594, 1278, 514, 400, 776, 1004, 468, 810, 536, 878, 0, 114, 308, 650, 274, 844],\n",
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" [388, 480, 1164, 628, 514, 662, 890, 354, 696, 422, 764, 114, 0, 194, 536, 388, 730],\n",
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" [354, 674, 1130, 822, 708, 628, 856, 320, 662, 388, 730, 308, 194, 0, 342, 422, 536],\n",
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" [468, 1016, 788, 1164, 1050, 514, 514, 662, 320, 274, 388, 650, 536, 342, 0, 764, 194],\n",
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" [776, 868, 1552, 560, 674, 1050, 1278, 742, 1084, 810, 1152, 274, 388, 422, 764, 0, 798],\n",
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" [662, 1210, 754, 1358, 1244, 708, 480, 856, 514, 468, 354, 844, 730, 536, 194, 798, 0],\n",
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" # fmt: on\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(\n",
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" routing_manager: pywrapcp.RoutingIndexManager, routing_model: pywrapcp.RoutingModel\n",
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"):\n",
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" \"\"\"Prints solution on console.\"\"\"\n",
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" print(\"################\")\n",
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" print(f\"Solution objective: {routing_model.CostVar().Value()}\")\n",
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" total_distance = 0\n",
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" for vehicle_id in range(routing_manager.GetNumberOfVehicles()):\n",
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" index = routing_model.Start(vehicle_id)\n",
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" plan_output = f\"Route for vehicle {vehicle_id}:\\n\"\n",
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" route_distance = 0\n",
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" while not routing_model.IsEnd(index):\n",
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" plan_output += f\" {routing_manager.IndexToNode(index)} ->\"\n",
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" previous_index = index\n",
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" index = routing_model.NextVar(index).Value()\n",
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" route_distance += routing_model.GetArcCostForVehicle(\n",
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" previous_index, index, vehicle_id\n",
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" )\n",
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" plan_output += f\" {routing_manager.IndexToNode(index)}\\n\"\n",
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" plan_output += f\"Distance of the route: {route_distance}m\\n\"\n",
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" print(plan_output)\n",
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" total_distance += route_distance\n",
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" print(f\"Total Distance of all routes: {total_distance}m\")\n",
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"\n",
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"\n",
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"\n",
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"class SolutionCallback:\n",
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" \"\"\"Create a solution callback.\"\"\"\n",
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"\n",
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" def __init__(\n",
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" self,\n",
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" manager: pywrapcp.RoutingIndexManager,\n",
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" model: pywrapcp.RoutingModel,\n",
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" limit: int,\n",
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" ):\n",
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" self._routing_manager = manager\n",
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" self._routing_model = model\n",
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" self._counter = 0\n",
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" self._counter_limit = limit\n",
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" self.objectives = []\n",
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"\n",
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" def __call__(self):\n",
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" objective = int(self._routing_model.CostVar().Value())\n",
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" if not self.objectives or objective < self.objectives[-1]:\n",
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" self.objectives.append(objective)\n",
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" print_solution(self._routing_manager, self._routing_model)\n",
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" self._counter += 1\n",
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" if self._counter > self._counter_limit:\n",
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" self._routing_model.solver().FinishCurrentSearch()\n",
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"\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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" routing_manager = pywrapcp.RoutingIndexManager(\n",
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" len(data[\"distance_matrix\"]), data[\"num_vehicles\"], data[\"depot\"]\n",
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" )\n",
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"\n",
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" # Create Routing Model.\n",
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" routing_model = pywrapcp.RoutingModel(routing_manager)\n",
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"\n",
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"\n",
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" # Create and register a transit callback.\n",
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" def distance_callback(from_index, to_index):\n",
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" \"\"\"Returns the 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 = routing_manager.IndexToNode(from_index)\n",
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" to_node = routing_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_model.RegisterTransitCallback(distance_callback)\n",
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"\n",
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" # Define cost of each arc.\n",
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" routing_model.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_model.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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" )\n",
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" distance_dimension = routing_model.GetDimensionOrDie(dimension_name)\n",
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" distance_dimension.SetGlobalSpanCostCoefficient(100)\n",
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"\n",
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" # Attach a solution callback.\n",
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" solution_callback = SolutionCallback(routing_manager, routing_model, 15)\n",
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" routing_model.AddAtSolutionCallback(solution_callback)\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.PATH_CHEAPEST_ARC\n",
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" )\n",
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" search_parameters.local_search_metaheuristic = (\n",
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" routing_enums_pb2.LocalSearchMetaheuristic.GUIDED_LOCAL_SEARCH\n",
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" )\n",
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" search_parameters.time_limit.FromSeconds(5)\n",
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"\n",
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" # Solve the problem.\n",
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" solution = routing_model.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(f\"Best objective: {solution_callback.objectives[-1]}\")\n",
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" else:\n",
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" print(\"No solution found !\")\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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