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#!/usr/bin/env python3 |
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"""Vehicles Routing Problem (VRP). |
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Some point are on the same physical location |
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No more than two vehicle to visit a physical location |
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""" |
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from ortools.constraint_solver import routing_enums_pb2 |
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from ortools.constraint_solver import pywrapcp |
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def create_data_model(): |
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"""Stores the data for the problem.""" |
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data = {} |
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data['distance_matrix'] = [ |
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[ |
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0, 548, 776, 696, 582, 274, 502, 194, 308, 194, 536, 502, 388, 354, |
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468, 776, 662 |
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], |
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[ |
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548, 0, 684, 308, 194, 502, 730, 354, 696, 742, 1084, 594, 480, |
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674, 1016, 868, 1210 |
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], |
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[ |
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776, 684, 0, 992, 878, 502, 274, 810, 468, 742, 400, 1278, 1164, |
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1130, 788, 1552, 754 |
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], |
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[ |
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696, 308, 992, 0, 114, 650, 878, 502, 844, 890, 1232, 514, 628, |
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822, 1164, 560, 1358 |
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], |
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[ |
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582, 194, 878, 114, 0, 536, 764, 388, 730, 776, 1118, 400, 514, |
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708, 1050, 674, 1244 |
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], |
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[ |
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274, 502, 502, 650, 536, 0, 228, 308, 194, 240, 582, 776, 662, 628, |
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514, 1050, 708 |
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], |
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[ |
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502, 730, 274, 878, 764, 228, 0, 536, 194, 468, 354, 1004, 890, |
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856, 514, 1278, 480 |
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], |
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[ |
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194, 354, 810, 502, 388, 308, 536, 0, 342, 388, 730, 468, 354, 320, |
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662, 742, 856 |
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], |
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[ |
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308, 696, 468, 844, 730, 194, 194, 342, 0, 274, 388, 810, 696, 662, |
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320, 1084, 514 |
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], |
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[ |
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194, 742, 742, 890, 776, 240, 468, 388, 274, 0, 342, 536, 422, 388, |
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274, 810, 468 |
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], |
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[ |
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536, 1084, 400, 1232, 1118, 582, 354, 730, 388, 342, 0, 878, 764, |
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730, 388, 1152, 354 |
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], |
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[ |
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502, 594, 1278, 514, 400, 776, 1004, 468, 810, 536, 878, 0, 114, |
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308, 650, 274, 844 |
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], |
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[ |
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388, 480, 1164, 628, 514, 662, 890, 354, 696, 422, 764, 114, 0, |
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194, 536, 388, 730 |
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], |
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[ |
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354, 674, 1130, 822, 708, 628, 856, 320, 662, 388, 730, 308, 194, |
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0, 342, 422, 536 |
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], |
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[ |
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468, 1016, 788, 1164, 1050, 514, 514, 662, 320, 274, 388, 650, 536, |
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342, 0, 764, 194 |
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], |
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[ |
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776, 868, 1552, 560, 674, 1050, 1278, 742, 1084, 810, 1152, 274, |
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388, 422, 764, 0, 798 |
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], |
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[ |
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662, 1210, 754, 1358, 1244, 708, 480, 856, 514, 468, 354, 844, 730, |
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536, 194, 798, 0 |
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], |
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] |
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data['locations'] = [ |
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[1,2,3,4,5], |
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[6,7,8,9,10], |
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[11,12,13,14,15,16], |
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] |
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data['num_vehicles'] = 4 |
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data['depot'] = 0 |
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return data |
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def print_solution(data, manager, routing, solution): |
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"""Prints solution on console.""" |
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print(f"locations: {data['locations']}") |
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print(f'Objective: {solution.ObjectiveValue()}') |
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max_route_distance = 0 |
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for vehicle_id in range(data['num_vehicles']): |
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plan_output = f'Route for vehicle {vehicle_id}:\n' |
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route_distance = 0 |
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index = routing.Start(vehicle_id) |
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while not routing.IsEnd(index): |
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node = manager.IndexToNode(index) |
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plan_output += f' N:{node} -> ' |
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previous_index = index |
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index = solution.Value(routing.NextVar(index)) |
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route_distance += routing.GetArcCostForVehicle( |
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previous_index, index, vehicle_id) |
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node = manager.IndexToNode(index) |
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plan_output += f'N:{node}\n' |
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plan_output += f'Distance of the route: {route_distance}m\n' |
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print(plan_output) |
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max_route_distance = max(route_distance, max_route_distance) |
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print(f'Maximum of the route distances: {max_route_distance}m') |
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def main(): |
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"""Solve the CVRP problem.""" |
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# Instantiate the data problem. |
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data = create_data_model() |
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# Create the routing index manager. |
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manager = pywrapcp.RoutingIndexManager(len(data['distance_matrix']), |
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data['num_vehicles'], data['depot']) |
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# Create Routing Model. |
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routing = pywrapcp.RoutingModel(manager) |
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# Create and register a transit callback. |
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def distance_callback(from_index, to_index): |
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"""Returns the distance between the two nodes.""" |
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# Convert from routing variable Index to distance matrix NodeIndex. |
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from_node = manager.IndexToNode(from_index) |
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to_node = manager.IndexToNode(to_index) |
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return data['distance_matrix'][from_node][to_node] |
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transit_callback_index = routing.RegisterTransitCallback(distance_callback) |
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# Define cost of each arc. |
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routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index) |
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# Add Distance constraint. |
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dimension_name = 'Distance' |
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routing.AddDimension( |
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transit_callback_index, |
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0, # no slack |
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3_000, # vehicle maximum travel distance |
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True, # start cumul to zero |
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dimension_name) |
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distance_dimension = routing.GetDimensionOrDie(dimension_name) |
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distance_dimension.SetGlobalSpanCostCoefficient(10) |
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b_vl = {} |
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solver = routing.solver() |
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for v in range(manager.GetNumberOfVehicles()): |
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for l in range(len(data['locations'])): |
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print(f'build b_vl[{v},{l}]...') |
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test = [] |
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for location in data['locations'][l]: |
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cond = routing.VehicleVar(manager.NodeToIndex(location)) == v |
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test.append(cond) |
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#test.append(cond.Var()) |
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b_vl[(v, l)] = solver.Sum(test) > 0 |
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for l in range(len(data['locations'])): |
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solver.Add(solver.Sum([b_vl[(v, l)] |
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for v in range(manager.GetNumberOfVehicles())]) <= 2) |
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# Setting first solution heuristic. |
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search_parameters = pywrapcp.DefaultRoutingSearchParameters() |
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search_parameters.first_solution_strategy = ( |
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routing_enums_pb2.FirstSolutionStrategy.PATH_CHEAPEST_ARC) |
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search_parameters.local_search_metaheuristic = ( |
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routing_enums_pb2.LocalSearchMetaheuristic.GUIDED_LOCAL_SEARCH) |
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# search_parameters.log_search = True |
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search_parameters.time_limit.FromSeconds(5) |
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# Solve the problem. |
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solution = routing.SolveWithParameters(search_parameters) |
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# Print solution on console. |
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if solution: |
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print_solution(data, manager, routing, solution) |
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else: |
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print('No solution found !') |
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if __name__ == '__main__': |
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main() |