add vrp_breaks.py
This commit is contained in:
Mizux Seiha
192
ortools/constraint_solver/samples/vrp_breaks.py
Executable file
192
ortools/constraint_solver/samples/vrp_breaks.py
Executable file
@@ -0,0 +1,192 @@
|
||||
#!/usr/bin/env python3
|
||||
# Copyright 2010-2021 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 with Time Windows (CVRPTW).
|
||||
|
||||
This is a sample using the routing library python wrapper to solve a CVRPTW
|
||||
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],
|
||||
]
|
||||
data['service_time'] = [15] * len(data['time_matrix']) # 15 min of service time
|
||||
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('Objective: {}'.format(solution.ObjectiveValue()))
|
||||
|
||||
print('Breaks:')
|
||||
intervals = solution.IntervalVarContainer()
|
||||
for i in range(intervals.Size()):
|
||||
brk = intervals.Element(i)
|
||||
if brk.PerformedValue() == True:
|
||||
print(f'{brk.Var().Name()}: 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)} Time({solution.Value(time_var)}) -> '
|
||||
index = solution.Value(routing.NextVar(index))
|
||||
time_var = time_dimension.CumulVar(index)
|
||||
plan_output += f'{manager.IndexToNode(index)} 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(data['num_vehicles']):
|
||||
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]
|
||||
Reference in New Issue
Block a user