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| """Simple Vehicles Routing Problem (VRP).
This is a sample using the routing library python wrapper to solve a VRP problem. A description of the problem can be found here: http://en.wikipedia.org/wiki/Vehicle_routing_problem.
Distances are in meters. """
from ortools.constraint_solver import routing_enums_pb2 from ortools.constraint_solver import pywrapcp
def create_data_model(): """Stores the data for the problem.""" data = {} data["distance_matrix"] = [ [0, 548, 776, 696, 582, 274, 502, 194, 308, 194, 536, 502, 388, 354, 468, 776, 662], [548, 0, 684, 308, 194, 502, 730, 354, 696, 742, 1084, 594, 480, 674, 1016, 868, 1210], [776, 684, 0, 992, 878, 502, 274, 810, 468, 742, 400, 1278, 1164, 1130, 788, 1552, 754], [696, 308, 992, 0, 114, 650, 878, 502, 844, 890, 1232, 514, 628, 822, 1164, 560, 1358], [582, 194, 878, 114, 0, 536, 764, 388, 730, 776, 1118, 400, 514, 708, 1050, 674, 1244], [274, 502, 502, 650, 536, 0, 228, 308, 194, 240, 582, 776, 662, 628, 514, 1050, 708], [502, 730, 274, 878, 764, 228, 0, 536, 194, 468, 354, 1004, 890, 856, 514, 1278, 480], [194, 354, 810, 502, 388, 308, 536, 0, 342, 388, 730, 468, 354, 320, 662, 742, 856], [308, 696, 468, 844, 730, 194, 194, 342, 0, 274, 388, 810, 696, 662, 320, 1084, 514], [194, 742, 742, 890, 776, 240, 468, 388, 274, 0, 342, 536, 422, 388, 274, 810, 468], [536, 1084, 400, 1232, 1118, 582, 354, 730, 388, 342, 0, 878, 764, 730, 388, 1152, 354], [502, 594, 1278, 514, 400, 776, 1004, 468, 810, 536, 878, 0, 114, 308, 650, 274, 844], [388, 480, 1164, 628, 514, 662, 890, 354, 696, 422, 764, 114, 0, 194, 536, 388, 730], [354, 674, 1130, 822, 708, 628, 856, 320, 662, 388, 730, 308, 194, 0, 342, 422, 536], [468, 1016, 788, 1164, 1050, 514, 514, 662, 320, 274, 388, 650, 536, 342, 0, 764, 194], [776, 868, 1552, 560, 674, 1050, 1278, 742, 1084, 810, 1152, 274, 388, 422, 764, 0, 798], [662, 1210, 754, 1358, 1244, 708, 480, 856, 514, 468, 354, 844, 730, 536, 194, 798, 0], ] data["num_vehicles"] = 4 data["depot"] = 0 return data
def print_solution(data, manager, routing, solution): """Prints solution on console.""" print(f"Objective: {solution.ObjectiveValue()}") max_route_distance = 0 for vehicle_id in range(data["num_vehicles"]): index = routing.Start(vehicle_id) plan_output = f"Route for vehicle {vehicle_id}:\n" route_distance = 0 while not routing.IsEnd(index): plan_output += f" {manager.IndexToNode(index)} -> " previous_index = index index = solution.Value(routing.NextVar(index)) route_distance += routing.GetArcCostForVehicle( previous_index, index, vehicle_id ) plan_output += f"{manager.IndexToNode(index)}\n" plan_output += f"Distance of the route: {route_distance}m\n" print(plan_output) max_route_distance = max(route_distance, max_route_distance) print(f"Maximum of the route distances: {max_route_distance}m")
def main(): """Entry point of the program.""" data = create_data_model()
manager = pywrapcp.RoutingIndexManager( len(data["distance_matrix"]), data["num_vehicles"], data["depot"] )
routing = pywrapcp.RoutingModel(manager)
def distance_callback(from_index, to_index): """Returns the distance between the two nodes.""" from_node = manager.IndexToNode(from_index) to_node = manager.IndexToNode(to_index) return data["distance_matrix"][from_node][to_node]
transit_callback_index = routing.RegisterTransitCallback(distance_callback)
routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index)
dimension_name = "Distance" routing.AddDimension( transit_callback_index, 0, 3000, True, dimension_name, ) distance_dimension = routing.GetDimensionOrDie(dimension_name) distance_dimension.SetGlobalSpanCostCoefficient(100)
search_parameters = pywrapcp.DefaultRoutingSearchParameters() search_parameters.first_solution_strategy = ( routing_enums_pb2.FirstSolutionStrategy.PATH_CHEAPEST_ARC )
search_parameters.log_search = True
solution = routing.SolveWithParameters(search_parameters)
if solution: print_solution(data, manager, routing, solution) else: print("No solution found !")
if __name__ == "__main__": main()
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