200 lines
7.4 KiB
Python
Executable File
200 lines
7.4 KiB
Python
Executable File
#!/usr/bin/env python3
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# Copyright 2010-2022 Google LLC
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# [START program]
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"""Vehicle Routing Problem (VRP) with breaks.
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This is a sample using the routing library python wrapper to solve a VRP
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problem.
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A description of the problem can be found here:
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http://en.wikipedia.org/wiki/Vehicle_routing_problem.
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Durations are in minutes.
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"""
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# [START import]
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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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# [END import]
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# [START data_model]
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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['num_vehicles'] = 4
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data['depot'] = 0
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data['time_matrix'] = [
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[0, 27, 38, 34, 29, 13, 25, 9, 15, 9, 26, 25, 19, 17, 23, 38, 33],
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[27, 0, 34, 15, 9, 25, 36, 17, 34, 37, 54, 29, 24, 33, 50, 43, 60],
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[38, 34, 0, 49, 43, 25, 13, 40, 23, 37, 20, 63, 58, 56, 39, 77, 37],
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[34, 15, 49, 0, 5, 32, 43, 25, 42, 44, 61, 25, 31, 41, 58, 28, 67],
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[29, 9, 43, 5, 0, 26, 38, 19, 36, 38, 55, 20, 25, 35, 52, 33, 62],
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[13, 25, 25, 32, 26, 0, 11, 15, 9, 12, 29, 38, 33, 31, 25, 52, 35],
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[25, 36, 13, 43, 38, 11, 0, 26, 9, 23, 17, 50, 44, 42, 25, 63, 24],
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[9, 17, 40, 25, 19, 15, 26, 0, 17, 19, 36, 23, 17, 16, 33, 37, 42],
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[15, 34, 23, 42, 36, 9, 9, 17, 0, 13, 19, 40, 34, 33, 16, 54, 25],
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[9, 37, 37, 44, 38, 12, 23, 19, 13, 0, 17, 26, 21, 19, 13, 40, 23],
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[26, 54, 20, 61, 55, 29, 17, 36, 19, 17, 0, 43, 38, 36, 19, 57, 17],
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[25, 29, 63, 25, 20, 38, 50, 23, 40, 26, 43, 0, 5, 15, 32, 13, 42],
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[19, 24, 58, 31, 25, 33, 44, 17, 34, 21, 38, 5, 0, 9, 26, 19, 36],
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[17, 33, 56, 41, 35, 31, 42, 16, 33, 19, 36, 15, 9, 0, 17, 21, 26],
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[23, 50, 39, 58, 52, 25, 25, 33, 16, 13, 19, 32, 26, 17, 0, 38, 9],
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[38, 43, 77, 28, 33, 52, 63, 37, 54, 40, 57, 13, 19, 21, 38, 0, 39],
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[33, 60, 37, 67, 62, 35, 24, 42, 25, 23, 17, 42, 36, 26, 9, 39, 0],
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]
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# 15 min of service time
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data['service_time'] = [15] * len(data['time_matrix'])
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data['service_time'][data['depot']] = 0
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assert len(data['time_matrix']) == len(data['service_time'])
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return data
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# [END data_model]
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# [START solution_printer]
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def print_solution(manager, routing, solution):
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"""Prints solution on console."""
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print(f'Objective: {solution.ObjectiveValue()}')
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print('Breaks:')
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intervals = solution.IntervalVarContainer()
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for i in range(intervals.Size()):
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brk = intervals.Element(i)
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if brk.PerformedValue():
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print(f'{brk.Var().Name()}: ' +
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f'Start({brk.StartValue()}) Duration({brk.DurationValue()})')
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else:
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print(f'{brk.Var().Name()}: Unperformed')
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time_dimension = routing.GetDimensionOrDie('Time')
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total_time = 0
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for vehicle_id in range(manager.GetNumberOfVehicles()):
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index = routing.Start(vehicle_id)
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plan_output = f'Route for vehicle {vehicle_id}:\n'
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while not routing.IsEnd(index):
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time_var = time_dimension.CumulVar(index)
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plan_output += f'{manager.IndexToNode(index)} '
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plan_output += f'Time({solution.Value(time_var)}) -> '
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index = solution.Value(routing.NextVar(index))
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time_var = time_dimension.CumulVar(index)
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plan_output += f'{manager.IndexToNode(index)} '
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plan_output += f'Time({solution.Value(time_var)})\n'
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plan_output += f'Time of the route: {solution.Value(time_var)}min\n'
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print(plan_output)
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total_time += solution.Value(time_var)
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print(f'Total time of all routes: {total_time}min')
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# [END solution_printer]
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def main():
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"""Solve the VRP with time windows."""
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# Instantiate the data problem.
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# [START data]
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data = create_data_model()
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# [END data]
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# Create the routing index manager.
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# [START index_manager]
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manager = pywrapcp.RoutingIndexManager(len(data['time_matrix']),
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data['num_vehicles'], data['depot'])
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# [END index_manager]
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# Create Routing Model.
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# [START routing_model]
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routing = pywrapcp.RoutingModel(manager)
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# [END routing_model]
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# Create and register a transit callback.
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# [START transit_callback]
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def time_callback(from_index, to_index):
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"""Returns the travel time + service time between the two nodes."""
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# Convert from routing variable Index to time 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['time_matrix'][from_node][to_node] + data['service_time'][
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from_node]
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transit_callback_index = routing.RegisterTransitCallback(time_callback)
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# [END transit_callback]
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# Define cost of each arc.
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# [START arc_cost]
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routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index)
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# [END arc_cost]
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# Add Time Windows constraint.
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time = 'Time'
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routing.AddDimension(
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transit_callback_index,
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10, # needed optional waiting time to place break
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180, # maximum time per vehicle
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True, # Force start cumul to zero.
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time)
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time_dimension = routing.GetDimensionOrDie(time)
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time_dimension.SetGlobalSpanCostCoefficient(10)
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# Breaks
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# [START break_constraint]
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# warning: Need a pre-travel array using the solver's index order.
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node_visit_transit = [0] * routing.Size()
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for index in range(routing.Size()):
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node = manager.IndexToNode(index)
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node_visit_transit[index] = data['service_time'][node]
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break_intervals = {}
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for v in range(manager.GetNumberOfVehicles()):
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break_intervals[v] = [
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routing.solver().FixedDurationIntervalVar(
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50, # start min
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60, # start max
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10, # duration: 10 min
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False, # optional: no
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f'Break for vehicle {v}')
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]
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time_dimension.SetBreakIntervalsOfVehicle(
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break_intervals[v], # breaks
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v, # vehicle index
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node_visit_transit)
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# [END break_constraint]
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# Setting first solution heuristic.
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# [START parameters]
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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(2)
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# [END parameters]
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# Solve the problem.
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# [START solve]
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solution = routing.SolveWithParameters(search_parameters)
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# [END solve]
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# Print solution on console.
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# [START print_solution]
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if solution:
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print_solution(manager, routing, solution)
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else:
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print('No solution found !')
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# [END print_solution]
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if __name__ == '__main__':
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main()
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# [END program]
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