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ortools-clone/ortools/constraint_solver/samples/vrp_breaks.py
Corentin Le Molgat 1af55b2be3 Add license boilerplate
2022-06-21 11:25:29 +02:00

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#!/usr/bin/env python3
# Copyright 2010-2022 Google LLC
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# [START program]
"""Vehicle Routing Problem (VRP) with breaks.
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.
Durations are in minutes.
"""
# [START import]
from ortools.constraint_solver import routing_enums_pb2
from ortools.constraint_solver import pywrapcp
# [END import]
# [START data_model]
def create_data_model():
"""Stores the data for the problem."""
data = {}
data['num_vehicles'] = 4
data['depot'] = 0
data['time_matrix'] = [
[0, 27, 38, 34, 29, 13, 25, 9, 15, 9, 26, 25, 19, 17, 23, 38, 33],
[27, 0, 34, 15, 9, 25, 36, 17, 34, 37, 54, 29, 24, 33, 50, 43, 60],
[38, 34, 0, 49, 43, 25, 13, 40, 23, 37, 20, 63, 58, 56, 39, 77, 37],
[34, 15, 49, 0, 5, 32, 43, 25, 42, 44, 61, 25, 31, 41, 58, 28, 67],
[29, 9, 43, 5, 0, 26, 38, 19, 36, 38, 55, 20, 25, 35, 52, 33, 62],
[13, 25, 25, 32, 26, 0, 11, 15, 9, 12, 29, 38, 33, 31, 25, 52, 35],
[25, 36, 13, 43, 38, 11, 0, 26, 9, 23, 17, 50, 44, 42, 25, 63, 24],
[9, 17, 40, 25, 19, 15, 26, 0, 17, 19, 36, 23, 17, 16, 33, 37, 42],
[15, 34, 23, 42, 36, 9, 9, 17, 0, 13, 19, 40, 34, 33, 16, 54, 25],
[9, 37, 37, 44, 38, 12, 23, 19, 13, 0, 17, 26, 21, 19, 13, 40, 23],
[26, 54, 20, 61, 55, 29, 17, 36, 19, 17, 0, 43, 38, 36, 19, 57, 17],
[25, 29, 63, 25, 20, 38, 50, 23, 40, 26, 43, 0, 5, 15, 32, 13, 42],
[19, 24, 58, 31, 25, 33, 44, 17, 34, 21, 38, 5, 0, 9, 26, 19, 36],
[17, 33, 56, 41, 35, 31, 42, 16, 33, 19, 36, 15, 9, 0, 17, 21, 26],
[23, 50, 39, 58, 52, 25, 25, 33, 16, 13, 19, 32, 26, 17, 0, 38, 9],
[38, 43, 77, 28, 33, 52, 63, 37, 54, 40, 57, 13, 19, 21, 38, 0, 39],
[33, 60, 37, 67, 62, 35, 24, 42, 25, 23, 17, 42, 36, 26, 9, 39, 0],
]
# 15 min of service time
data['service_time'] = [15] * len(data['time_matrix'])
data['service_time'][data['depot']] = 0
assert len(data['time_matrix']) == len(data['service_time'])
return data
# [END data_model]
# [START solution_printer]
def print_solution(manager, routing, solution):
"""Prints solution on console."""
print(f'Objective: {solution.ObjectiveValue()}')
print('Breaks:')
intervals = solution.IntervalVarContainer()
for i in range(intervals.Size()):
brk = intervals.Element(i)
if brk.PerformedValue():
print(f'{brk.Var().Name()}: ' +
f'Start({brk.StartValue()}) Duration({brk.DurationValue()})')
else:
print(f'{brk.Var().Name()}: Unperformed')
time_dimension = routing.GetDimensionOrDie('Time')
total_time = 0
for vehicle_id in range(manager.GetNumberOfVehicles()):
index = routing.Start(vehicle_id)
plan_output = f'Route for vehicle {vehicle_id}:\n'
while not routing.IsEnd(index):
time_var = time_dimension.CumulVar(index)
plan_output += f'{manager.IndexToNode(index)} '
plan_output += f'Time({solution.Value(time_var)}) -> '
index = solution.Value(routing.NextVar(index))
time_var = time_dimension.CumulVar(index)
plan_output += f'{manager.IndexToNode(index)} '
plan_output += f'Time({solution.Value(time_var)})\n'
plan_output += f'Time of the route: {solution.Value(time_var)}min\n'
print(plan_output)
total_time += solution.Value(time_var)
print(f'Total time of all routes: {total_time}min')
# [END solution_printer]
def main():
"""Solve the VRP with time windows."""
# Instantiate the data problem.
# [START data]
data = create_data_model()
# [END data]
# Create the routing index manager.
# [START index_manager]
manager = pywrapcp.RoutingIndexManager(len(data['time_matrix']),
data['num_vehicles'], data['depot'])
# [END index_manager]
# Create Routing Model.
# [START routing_model]
routing = pywrapcp.RoutingModel(manager)
# [END routing_model]
# Create and register a transit callback.
# [START transit_callback]
def time_callback(from_index, to_index):
"""Returns the travel time + service time between the two nodes."""
# Convert from routing variable Index to time matrix NodeIndex.
from_node = manager.IndexToNode(from_index)
to_node = manager.IndexToNode(to_index)
return data['time_matrix'][from_node][to_node] + data['service_time'][
from_node]
transit_callback_index = routing.RegisterTransitCallback(time_callback)
# [END transit_callback]
# Define cost of each arc.
# [START arc_cost]
routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index)
# [END arc_cost]
# Add Time Windows constraint.
time = 'Time'
routing.AddDimension(
transit_callback_index,
10, # needed optional waiting time to place break
180, # maximum time per vehicle
True, # Force start cumul to zero.
time)
time_dimension = routing.GetDimensionOrDie(time)
time_dimension.SetGlobalSpanCostCoefficient(10)
# Breaks
# [START break_constraint]
# warning: Need a pre-travel array using the solver's index order.
node_visit_transit = [0] * routing.Size()
for index in range(routing.Size()):
node = manager.IndexToNode(index)
node_visit_transit[index] = data['service_time'][node]
break_intervals = {}
for v in range(manager.GetNumberOfVehicles()):
break_intervals[v] = [
routing.solver().FixedDurationIntervalVar(
50, # start min
60, # start max
10, # duration: 10 min
False, # optional: no
f'Break for vehicle {v}')
]
time_dimension.SetBreakIntervalsOfVehicle(
break_intervals[v], # breaks
v, # vehicle index
node_visit_transit)
# [END break_constraint]
# Setting first solution heuristic.
# [START parameters]
search_parameters = pywrapcp.DefaultRoutingSearchParameters()
search_parameters.first_solution_strategy = (
routing_enums_pb2.FirstSolutionStrategy.PATH_CHEAPEST_ARC)
search_parameters.local_search_metaheuristic = (
routing_enums_pb2.LocalSearchMetaheuristic.GUIDED_LOCAL_SEARCH)
# search_parameters.log_search = True
search_parameters.time_limit.FromSeconds(2)
# [END parameters]
# Solve the problem.
# [START solve]
solution = routing.SolveWithParameters(search_parameters)
# [END solve]
# Print solution on console.
# [START print_solution]
if solution:
print_solution(manager, routing, solution)
else:
print('No solution found !')
# [END print_solution]
if __name__ == '__main__':
main()
# [END program]