228 lines
9.6 KiB
Plaintext
228 lines
9.6 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"# Copyright 2010-2018 Google LLC\n",
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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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"# [START program]\n",
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"\"\"\"Vehicles Routing Problem (VRP) with Resource Constraints.\"\"\"\n",
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"\n",
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"# [START import]\n",
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"from __future__ import print_function\n",
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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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"# [END import]\n",
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"\n",
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"\n",
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"# [START data_model]\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['time_matrix'] = [\n",
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" [0, 6, 9, 8, 7, 3, 6, 2, 3, 2, 6, 6, 4, 4, 5, 9, 7],\n",
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" [6, 0, 8, 3, 2, 6, 8, 4, 8, 8, 13, 7, 5, 8, 12, 10, 14],\n",
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" [9, 8, 0, 11, 10, 6, 3, 9, 5, 8, 4, 15, 14, 13, 9, 18, 9],\n",
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" [8, 3, 11, 0, 1, 7, 10, 6, 10, 10, 14, 6, 7, 9, 14, 6, 16],\n",
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" [7, 2, 10, 1, 0, 6, 9, 4, 8, 9, 13, 4, 6, 8, 12, 8, 14],\n",
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" [3, 6, 6, 7, 6, 0, 2, 3, 2, 2, 7, 9, 7, 7, 6, 12, 8],\n",
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" [6, 8, 3, 10, 9, 2, 0, 6, 2, 5, 4, 12, 10, 10, 6, 15, 5],\n",
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" [2, 4, 9, 6, 4, 3, 6, 0, 4, 4, 8, 5, 4, 3, 7, 8, 10],\n",
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" [3, 8, 5, 10, 8, 2, 2, 4, 0, 3, 4, 9, 8, 7, 3, 13, 6],\n",
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" [2, 8, 8, 10, 9, 2, 5, 4, 3, 0, 4, 6, 5, 4, 3, 9, 5],\n",
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" [6, 13, 4, 14, 13, 7, 4, 8, 4, 4, 0, 10, 9, 8, 4, 13, 4],\n",
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" [6, 7, 15, 6, 4, 9, 12, 5, 9, 6, 10, 0, 1, 3, 7, 3, 10],\n",
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" [4, 5, 14, 7, 6, 7, 10, 4, 8, 5, 9, 1, 0, 2, 6, 4, 8],\n",
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" [4, 8, 13, 9, 8, 7, 10, 3, 7, 4, 8, 3, 2, 0, 4, 5, 6],\n",
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" [5, 12, 9, 14, 12, 6, 6, 7, 3, 3, 4, 7, 6, 4, 0, 9, 2],\n",
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" [9, 10, 18, 6, 8, 12, 15, 8, 13, 9, 13, 3, 4, 5, 9, 0, 9],\n",
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" [7, 14, 9, 16, 14, 8, 5, 10, 6, 5, 4, 10, 8, 6, 2, 9, 0],\n",
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" ]\n",
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" data['time_windows'] = [\n",
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" (0, 5), # depot\n",
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" (7, 12), # 1\n",
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" (10, 15), # 2\n",
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" (5, 14), # 3\n",
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" (5, 13), # 4\n",
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" (0, 5), # 5\n",
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" (5, 10), # 6\n",
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" (0, 10), # 7\n",
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" (5, 10), # 8\n",
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" (0, 5), # 9\n",
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" (10, 16), # 10\n",
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" (10, 15), # 11\n",
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" (0, 5), # 12\n",
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" (5, 10), # 13\n",
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" (7, 12), # 14\n",
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" (10, 15), # 15\n",
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" (5, 15), # 16\n",
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" ]\n",
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" data['num_vehicles'] = 4\n",
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" # [START resources_data]\n",
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" data['vehicle_load_time'] = 5\n",
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" data['vehicle_unload_time'] = 5\n",
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" data['depot_capacity'] = 2\n",
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" # [END resources_data]\n",
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" data['depot'] = 0\n",
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" return data\n",
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" # [END data_model]\n",
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"\n",
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"\n",
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"# [START solution_printer]\n",
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"def print_solution(data, manager, routing, assignment):\n",
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" \"\"\"Prints assignment on console.\"\"\"\n",
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" time_dimension = routing.GetDimensionOrDie('Time')\n",
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" total_time = 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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" while not routing.IsEnd(index):\n",
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" time_var = time_dimension.CumulVar(index)\n",
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" plan_output += '{0} Time({1},{2}) -> '.format(\n",
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" manager.IndexToNode(index), assignment.Min(time_var),\n",
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" assignment.Max(time_var))\n",
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" index = assignment.Value(routing.NextVar(index))\n",
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" time_var = time_dimension.CumulVar(index)\n",
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" plan_output += '{0} Time({1},{2})\\n'.format(manager.IndexToNode(index),\n",
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" assignment.Min(time_var),\n",
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" assignment.Max(time_var))\n",
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" plan_output += 'Time of the route: {}min\\n'.format(\n",
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" assignment.Min(time_var))\n",
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" print(plan_output)\n",
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" total_time += assignment.Min(time_var)\n",
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" print('Total time of all routes: {}min'.format(total_time))\n",
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" # [END solution_printer]\n",
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"\n",
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"\n",
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"\"\"\"Solve the VRP with time windows.\"\"\"\n",
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"# Instantiate the data problem.\n",
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"# [START data]\n",
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"data = create_data_model()\n",
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"# [END data]\n",
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"\n",
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"# Create the routing index manager.\n",
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"# [START index_manager]\n",
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"manager = pywrapcp.RoutingIndexManager(len(data['time_matrix']),\n",
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" data['num_vehicles'], data['depot'])\n",
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"# [END index_manager]\n",
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"\n",
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"# Create Routing Model.\n",
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"# [START routing_model]\n",
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"routing = pywrapcp.RoutingModel(manager)\n",
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"\n",
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"# [END routing_model]\n",
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"\n",
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"# Create and register a transit callback.\n",
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"# [START transit_callback]\n",
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"def time_callback(from_index, to_index):\n",
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" \"\"\"Returns the travel time between the two nodes.\"\"\"\n",
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" # Convert from routing variable Index to time 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['time_matrix'][from_node][to_node]\n",
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"\n",
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"transit_callback_index = routing.RegisterTransitCallback(time_callback)\n",
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"# [END transit_callback]\n",
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"\n",
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"# Define cost of each arc.\n",
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"# [START arc_cost]\n",
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"routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index)\n",
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"# [END arc_cost]\n",
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"\n",
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"# Add Time Windows constraint.\n",
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"# [START time_windows_constraint]\n",
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"time = 'Time'\n",
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"routing.AddDimension(\n",
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" transit_callback_index,\n",
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" 60, # allow waiting time\n",
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" 60, # maximum time per vehicle\n",
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" False, # Don't force start cumul to zero.\n",
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" time)\n",
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"time_dimension = routing.GetDimensionOrDie(time)\n",
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"# Add time window constraints for each location except depot.\n",
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"for location_idx, time_window in enumerate(data['time_windows']):\n",
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" if location_idx == 0:\n",
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" continue\n",
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" index = manager.NodeToIndex(location_idx)\n",
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" time_dimension.CumulVar(index).SetRange(time_window[0], time_window[1])\n",
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"# Add time window constraints for each vehicle start node.\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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" time_dimension.CumulVar(index).SetRange(data['time_windows'][0][0],\n",
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" data['time_windows'][0][1])\n",
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"# [END time_windows_constraint]\n",
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"\n",
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"# Add resource constraints at the depot.\n",
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"# [START depot_load_time]\n",
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"solver = routing.solver()\n",
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"intervals = []\n",
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"for i in range(data['num_vehicles']):\n",
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" # Add time windows at start of routes\n",
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" intervals.append(\n",
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" solver.FixedDurationIntervalVar(\n",
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" time_dimension.CumulVar(routing.Start(i)),\n",
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" data['vehicle_load_time'], 'depot_interval'))\n",
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" # Add time windows at end of routes.\n",
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" intervals.append(\n",
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" solver.FixedDurationIntervalVar(\n",
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" time_dimension.CumulVar(routing.End(i)),\n",
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" data['vehicle_unload_time'], 'depot_interval'))\n",
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"# [END depot_load_time]\n",
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"\n",
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"# [START depot_capacity]\n",
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"depot_usage = [1 for i in range(len(intervals))]\n",
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"solver.Add(\n",
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" solver.Cumulative(intervals, depot_usage, data['depot_capacity'],\n",
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" 'depot'))\n",
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"# [END depot_capacity]\n",
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"\n",
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"# Instantiate route start and end times to produce feasible times.\n",
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"# [START depot_start_end_times]\n",
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"for i in range(data['num_vehicles']):\n",
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" routing.AddVariableMinimizedByFinalizer(\n",
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" time_dimension.CumulVar(routing.Start(i)))\n",
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" routing.AddVariableMinimizedByFinalizer(\n",
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" time_dimension.CumulVar(routing.End(i)))\n",
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"# [END depot_start_end_times]\n",
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"\n",
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"# Setting first solution heuristic.\n",
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"# [START parameters]\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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"# [END parameters]\n",
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"\n",
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"# Solve the problem.\n",
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"# [START solve]\n",
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"assignment = routing.SolveWithParameters(search_parameters)\n",
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"# [END solve]\n",
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"\n",
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"# Print solution on console.\n",
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"# [START print_solution]\n",
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"if assignment:\n",
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" print_solution(data, manager, routing, assignment)\n",
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"# [END print_solution]\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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]
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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": 4
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}
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