Mizux
commented
5 years ago Which platform ?
Closed ogunnoo closed 5 years ago
Mizux
commented
5 years ago Which platform ?
ogunnoo
commented
5 years ago I'm work with Python 3.7 on a Mac.
Mizux
commented
5 years ago Can you provide us your macOs version ? IIRC should be
sw_vers -productVersionand also the version of ortools you use:
python3.7 -m pip show ortoolsAccording to https://github.com/ContinuumIO/anaconda-issues/issues/1172#issuecomment-319320010 it may be possible that your gcc/libstdc++/libc++ lib provided by the anaconda env. is not compatible with he package generated (ed I tried to use a up-to-date brew env for this libraries...)
ogunnoo
commented
5 years ago Can you provide us your macOs version ? IIRC should be
sw_vers -productVersionand also the version of ortools you use:
python3.7 -m pip show ortools
My macOs version is 10.13.6 My OR-Tools version is 7.0.6546
docmarionum1
commented
5 years ago @ogunnoo What is your code? I got the exact same error after upgrading from version 6 to 7 and I realized it was because I didn't update the way I was defining my distance_callback.
With the old version I had;
def distance_callback(from_node, to_node):
return int(self.distance_matrix[from_node][to_node])
...I had to change it to:
def distance_callback(from_index, to_index):
from_node = manager.IndexToNode(from_index)
to_node = manager.IndexToNode(to_index)
...See: https://developers.google.com/optimization/support/release_notes#index_manager
ogunnoo
commented
5 years ago @ogunnoo What is your code? I got the exact same error after upgrading from version 6 to 7 and I realized it was because I didn't update the way I was defining my
distance_callback.With the old version I had;
def distance_callback(from_node, to_node): return int(self.distance_matrix[from_node][to_node]) ...I had to change it to:
def distance_callback(from_index, to_index): from_node = manager.IndexToNode(from_index) to_node = manager.IndexToNode(to_index) ...See: https://developers.google.com/optimization/support/release_notes#index_manager
def distance_callback(from_index, to_index):
"""Returns the distance between the two nodes."""
# Convert from routing variable Index to distance matrix NodeIndex.
from_node = manager.IndexToNode(from_index)
to_node = manager.IndexToNode(to_index)
return data['distances'][from_node][to_node]My distance call back code is the same as yours still the error persists
ogunnoo
commented
5 years ago According to ContinuumIO/anaconda-issues#1172 (comment) it may be possible that your gcc/libstdc++/libc++ lib provided by the anaconda env. is not compatible with he package generated (ed I tried to use a up-to-date brew env for this libraries...)
I updated the gcc but it didn't stop the error.
ogunnoo
commented
5 years ago I ran the code using Python 2.7 and it returns the error below. So the solver does produce a solution, but once it goes through an iteration in the print function it breaks.
RuntimeErrorTraceback (most recent call last)
<ipython-input-20-62581dcaaabd> in <module>()
232
233 if __name__ == '__main__':
--> 234 results_df = main()
<ipython-input-20-62581dcaaabd> in main()
227 # Print solution on console.
228 if assignment:
--> 229 results_df = print_solution(data, manager, routing, assignment)
230 return results_df
231
<ipython-input-20-62581dcaaabd> in print_solution(data, manager, routing, assignment)
33 node_index = manager.IndexToNode(index)
34 route_load += data['demands'][node_index]
---> 35 plan_output += ' {0} Load({1}) Time({2},{3})-> '.format(node_index, route_load, round(assignment.Min(time_var)/60,3),round(assignment.Max(time_var)/60,3))
36 previous_index = index
37 node.append(index)
RuntimeError: SWIG std::function invocation failed.recall me #1022
Mizux
commented
5 years ago @ogunnoo As you may have noticed in v7 API you need to use a manager to make perform the conversion between your data index and the solver one.
Are you sure manager is aready instantiate before defining the distance_callback ?
You can take a look at https://stackoverflow.com/questions/55862927/python-or-tools-function-does-not-work-when-called-from-within-a-python-package
ogunnoo
commented
5 years ago This is my code below
def main():
"""Solve the CVRP problem."""
# Instantiate the data problem.
data = create_data_model()
# Create the routing index manager.
manager = pywrapcp.RoutingIndexManager(
len(data['distances']), data['num_vehicles'], data['depot'])
# Create Routing Model.
routing = pywrapcp.RoutingModel(manager)
# Create and register a transit callback.
def distance_callback(from_index, to_index):
"""Returns the distance between the two nodes."""
# Convert from routing variable Index to distance matrix NodeIndex.
from_node = manager.IndexToNode(from_index)
to_node = manager.IndexToNode(to_index)
return data['distances'][from_node][to_node]
transit_callback_index = routing.RegisterTransitCallback(distance_callback)
# Define cost of each arc.
routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index)
# Add Capacity constraint.
def demand_callback(from_index):
"""Returns the demand of the node."""
# Convert from routing variable Index to demands NodeIndex.
from_node = manager.IndexToNode(from_index)
return data['demands'][from_node]
demand_callback_index = routing.RegisterUnaryTransitCallback(demand_callback)
routing.AddDimensionWithVehicleCapacity(
demand_callback_index,
0, # null capacity slack
data['vehicle_capacities'], # vehicle maximum capacities
True, # start cumul to zero
'Capacity')
def time_callback(from_index, to_index):
"""Returns the travel 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)
trav_time = (data['distances'][from_node][to_node])/data["vehicle_speed"]
serv_time = data["demands"][to_node]*data["time_per_demand_unit"]
return serv_time + trav_time
transit_callback_index = routing.RegisterTransitCallback(time_callback)
routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index)
time = 'Time'
horizon = 3000
routing.AddDimension(
transit_callback_index,
horizon, # allow waiting time
horizon, # maximum time per vehicle
False, # Don't force start cumul to zero.
time)
time_dimension = routing.GetDimensionOrDie(time)
# Add time window constraints for each location except depot.
for location_idx, time_window in enumerate(data['time_windows']):
if location_idx == 0:
continue
index = manager.NodeToIndex(location_idx)
time_dimension.CumulVar(index).SetRange(int(time_window[0]), int(time_window[1]))
# Add time window constraints for each vehicle start node.
for vehicle_id in range(data['num_vehicles']):
index = routing.Start(vehicle_id)
time_dimension.CumulVar(index).SetRange(data['time_windows'][0][0],
data['time_windows'][0][1])
for i in range(data['num_vehicles']):
routing.AddVariableMinimizedByFinalizer(time_dimension.CumulVar(routing.Start(i)))
routing.AddVariableMinimizedByFinalizer(time_dimension.CumulVar(routing.End(i)))
search_parameters = pywrapcp.DefaultRoutingSearchParameters()
search_parameters.first_solution_strategy = (routing_enums_pb2.FirstSolutionStrategy.PATH_CHEAPEST_ARC)
for vehicle_nbr in range(data["num_vehicles"]):
start_var = routing.NextVar(routing.Start(vehicle_nbr))
for node_index in range(routing.Size(), routing.Size() + routing.vehicles()):
start_var.RemoveValue(node_index)
# Solve the problem.
assignment = routing.SolveWithParameters(search_parameters)
# Print solution on console.
if assignment:
results_df = print_solution(data, manager, routing, assignment)
return results_df
if __name__ == '__main__':
results_df = main()
nttlinh
commented
5 years ago This is my code, I have same problem. I don't know how to fix it? Can you help me? The result is:
{'vehicles': 10, 'capacity': 10, 'speed': 40, 'max_dur_mult': 1.3, 'glob_span_cost_coef': None}
begin solving
RuntimeError: SWIG std::function invocation failed.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "D:/codelv/demo_3.py", line 406, in <module>
main()
File "D:/codelv/demo_3.py", line 160, in main
assignment = routing.SolveWithParameters(search_parameters)
File "D:\codelv\venv\lib\site-packages\ortools\constraint_solver\pywrapcp.py", line 3449, in SolveWithParameters
return _pywrapcp.RoutingModel_SolveWithParameters(self, search_parameters, solutions)
SystemError: <built-in function RoutingModel_SolveWithParameters> returned a result with an error set\\code
import sys, os, math
from ortools.constraint_solver import pywrapcp
from ortools.constraint_solver import routing_enums_pb2
import matplotlib.pyplot as plt
import np
from urllib3.connectionpool import xrange
def getopts(argv):
opts = {} # Empty dictionary to store key-value pairs.
while argv: # While there are arguments left to parse...
if argv[0][0] == '-': # Found a "-name value" pair.
opts[argv[0]] = argv[1] # Add key and value to the dictionary.
argv = argv[1:] # Reduce the argument list by copying it starting from index 1.
return opts
def main():
cmd_opts = getopts(sys.argv)
# configuration, problem description
depot = 0
num_vehicles = '--vehicles' in cmd_opts and int(cmd_opts['--vehicles']) or 10
vehicle_capacity = '--capacity' in cmd_opts and int(cmd_opts['--capacity']) or 10
speed = '--speed' in cmd_opts and int(cmd_opts['--speed']) or 40
search_time_limit = '--search_time_limit' in cmd_opts and int(
cmd_opts['--search_time_limit']) or 10 * 1000 # milliseconds
trip_service_duration_max = 0
max_dur_mult = '--max_dur_mult' in cmd_opts and float(cmd_opts['--max_dur_mult']) or 1.3
glob_span_cost_coef = '--glob_span_cost_coef' in cmd_opts and int(cmd_opts['--glob_span_cost_coef']) or None
plot = '--plot' in cmd_opts
print(
{
'vehicles': num_vehicles,
'capacity': vehicle_capacity,
'speed': speed,
'max_dur_mult': max_dur_mult,
'glob_span_cost_coef': glob_span_cost_coef,
})
customers = []
locations = []
demands = []
start_times = []
end_times = []
pickups = []
dropoffs = []
data = [
# customer lat lng demand start end pickup_index dropoff_index
[-1, 37.477749, -122.148499, 0, -1, -1, 0, 0],
[1, 37.467112, -122.253060, 1, 487, 2287, 0, 2],
[1, 37.477995, -122.148442, -1, 2623, 4423, 1, 0],
[2, 37.444040, -122.214423, 1, 678, 2478, 0, 4],
[2, 37.478331, -122.149008, -1, 2623, 4423, 3, 0],
[3, 37.455956, -122.285887, 1, 23, 1823, 0, 6],
[3, 37.478002, -122.148850, -1, 2623, 4423, 5, 0],
[4, 37.452259, -122.240702, 1, 537, 2337, 0, 8],
[4, 37.481572, -122.152584, -1, 2623, 4423, 7, 0],
[5, 37.447776, -122.257816, 1, 0, 1800, 0, 10],
[5, 37.485104, -122.147462, -1, 2623, 4423, 9, 0],
[6, 37.473287, -122.271279, 1, 704, 2504, 0, 12],
[6, 37.480284, -122.167614, -1, 2623, 4423, 11, 0],
[7, 37.558294, -122.263208, 1, 823, 2610, 0, 14],
[7, 37.481087, -122.166956, -1, 2640, 4423, 13, 0],
[8, 37.558294, -122.263208, 1, 0, 1800, 0, 16],
[8, 37.481087, -122.166956, -1, 2623, 4423, 15, 0],
]
for i in range(0, len(data)):
row = data[i]
customers.append(row[0])
locations.append([row[1], row[2]])
demands.append(row[3])
start_times.append(row[4])
end_times.append(row[5])
pickups.append(row[6])
dropoffs.append(row[7])
# build model
num_locations = len(locations)
#model_parameters = pywrapcp.RoutingModel.DefaultModelParameters()
model_parameters = pywrapcp.DefaultRoutingModelParameters()
# print model_parameters
manager = pywrapcp.RoutingIndexManager(num_locations,num_vehicles,depot)
routing = pywrapcp.RoutingModel(manager,model_parameters)
#routing = pywrapcp.RoutingModel(num_locations, num_vehicles, depot, model_parameters)
#search_parameters = pywrapcp.RoutingModel.DefaultSearchParameters()
search_parameters = pywrapcp.DefaultRoutingSearchParameters()
search_parameters.time_limit.seconds = search_time_limit
search_parameters.first_solution_strategy = (
routing_enums_pb2.FirstSolutionStrategy.PARALLEL_CHEAPEST_INSERTION)
# print search_parameters
#time_between_locations = CreateCustomTimeCallback(locations, speed)
time_between_locations = CreateCustomTimeCallback(locations,speed)
arc_cost_callback = time_between_locations.Duration
arc_cost_callback1 = routing.RegisterTransitCallback(arc_cost_callback)
#arc_cost_callback = routing.RegisterTransitCallback(time_between_locations.Duration)
routing.SetArcCostEvaluatorOfAllVehicles(arc_cost_callback1)
demands_at_locations = CreateDemandCallback(demands)
demands_callback = demands_at_locations.Demand
demands_callback1 = routing.RegisterUnaryTransitCallback(demands_callback)
routing.AddDimension(demands_callback1, 0, vehicle_capacity, True, "Capacity")
# time taken to load/unload at each location
service_times = CreateServiceTimeCallback(demands, trip_service_duration_max)
service_time_callback = service_times.ServiceTime
# time taken to travel between locations
travel_time_callback = time_between_locations.Duration
total_times = CreateTotalTimeCallback(service_time_callback, travel_time_callback)
total_time_callback = total_times.TotalTime
total_time_callback1 = routing.RegisterTransitCallback(total_time_callback)
horizon = max(end_times) + 7600 # buffer beyond latest dropoff
routing.AddDimension(total_time_callback1, horizon, horizon, False, "Time")
# build pickup and delivery model
time_dimension = routing.GetDimensionOrDie("Time")
if glob_span_cost_coef:
time_dimension.SetGlobalSpanCostCoefficient(glob_span_cost_coef)
solver = routing.solver()
for i in range(1, num_locations):
#index = routing.IndexToNode(i)
index = manager.NodeToIndex(i)
time_dimension.CumulVar(i).SetRange(start_times[i], end_times[i])
if demands[i] != depot and pickups[i] == 0 and dropoffs[i] != 0: # don't setup precedence for depots
#delivery_index = routing.IndexToNode(dropoffs[i])
delivery_index = manager.NodeToIndex(dropoffs[i])
if delivery_index > 0:
solver.Add(routing.VehicleVar(index) == routing.VehicleVar(delivery_index))
solver.Add(time_dimension.CumulVar(index) <= time_dimension.CumulVar(delivery_index))
min_dur = int(travel_time_callback(index, delivery_index))
max_dur = int(max_dur_mult * min_dur)
dur_expr = time_dimension.CumulVar(delivery_index) - time_dimension.CumulVar(index)
solver.Add(dur_expr <= max_dur)
routing.AddPickupAndDelivery(i, dropoffs[i])
if plot:
plt.barh(customers, np.array(end_times) - np.array(start_times), left=start_times)
plt.yticks(customers)
plt.xlabel('pickup start,end .. dropoff start,end')
plt.ylabel('customers')
plt.show()
print('begin solving')
assignment = routing.SolveWithParameters(search_parameters)
if assignment:
print('solution exists')
printer = ConsolePrinter(num_vehicles, customers, demands, start_times,
end_times, pickups, dropoffs, travel_time_callback,
max_dur_mult, routing, assignment)
printer.print_solution()
else:
print('solution not found')
class ConsolePrinter():
def __init__(self, num_vehicles, customers, demands, start_times, end_times,
pickups, dropoffs, calc_travel_time, max_dur_mult, routing, assignment):
self.num_vehicles = num_vehicles
self.customers = customers
self.demands = demands
self.start_times = start_times
self.end_times = end_times
self.pickups = pickups
self.dropoffs = dropoffs
self.calc_travel_time = calc_travel_time
self.max_dur_mult = max_dur_mult
self.routing = routing
self.assignment = assignment
def print_solution(self):
print("Total duration of all routes: " + str(self.assignment.ObjectiveValue()) + "\n")
capacity_dimension = self.routing.GetDimensionOrDie("Capacity")
time_dimension = self.routing.GetDimensionOrDie("Time")
errors = None
plan_output = ''
rides = {}
for vehicle_nbr in range(self.num_vehicles):
veh_output = ''
index = self.routing.Start(vehicle_nbr)
empty = True
while not self.routing.IsEnd(index):
node_index = self.routing.IndexToNode(index)
customer = self.customers[node_index]
demand = self.demands[node_index]
load_var = capacity_dimension.CumulVar(index)
time_var = time_dimension.CumulVar(index)
visit = Visit(vehicle_nbr, node_index, customer, demand,
self.assignment.Value(load_var),
self.assignment.Min(time_var),
self.assignment.Max(time_var),
self.assignment.Value(time_var))
ride = rides.get(customer)
if not ride:
ride = rides[customer] = Ride(customer, vehicle_nbr)
if visit.is_pickup():
ride.pickup_visit = visit
else:
ride.dropoff_visit = visit
veh_output += \
"{route_id} {node_index} {customer} {demand} {load} {tmin} {tmax} {tval}".format(
route_id=vehicle_nbr,
node_index=node_index,
customer=customer,
demand=demand,
load=self.assignment.Value(load_var),
tmin=self.assignment.Min(time_var),
tmax=self.assignment.Max(time_var),
tval=self.assignment.Value(time_var))
if self.assignment.Value(load_var) > 0:
empty = False
veh_output += "\n"
index = self.assignment.Value(self.routing.NextVar(index))
node_index = self.routing.IndexToNode(index)
customer = self.customers[node_index]
demand = self.demands[node_index]
load_var = capacity_dimension.CumulVar(index)
time_var = time_dimension.CumulVar(index)
visit = Visit(vehicle_nbr, node_index, customer, demand,
self.assignment.Value(load_var),
self.assignment.Min(time_var),
self.assignment.Max(time_var),
self.assignment.Value(time_var))
veh_output += \
"{route_id} {node_index} {customer} {demand} {load} {tmin} {tmax} {tval}".format(
route_id=vehicle_nbr,
node_index=node_index,
customer=customer,
demand=demand,
load=self.assignment.Value(load_var),
tmin=self.assignment.Min(time_var),
tmax=self.assignment.Max(time_var),
tval=self.assignment.Value(time_var))
veh_output += "\n"
if not empty:
plan_output += veh_output
print("route_id node_index customer demand load tmin tmax tval")
print(plan_output)
ride_list = rides.values()
cols = ['cust (pnode..dnode)', 'route',
'pickup_at..dropoff_at',
'cnstr_pickup', 'cnstr_dropoff',
'plan_dur',
'cnstr_dur',
'plan_pickup_range',
'plan_dropoff_range',
'plan_min_poss_dur']
row_format = "".join(map(lambda c: "{:>" + str(len(c) + 4) + "}", cols))
print(row_format.format(*cols))
for i in range(0, len(ride_list)):
ride = ride_list[i]
if not ride.pickup_visit:
continue
min_dur = self.calc_travel_time(ride.pickup_visit.node_index, ride.dropoff_visit.node_index)
vals = ["{} {}..{}".format(ride.customer, ride.pickup_visit.node_index, ride.dropoff_visit.node_index),
ride.route,
"{}..{}".format(ride.pickup_visit.tval, ride.dropoff_visit.tval),
"{}..{}".format(time_dimension.CumulVar(ride.pickup_visit.node_index).Min(),
time_dimension.CumulVar(ride.pickup_visit.node_index).Max()),
"{}..{}".format(time_dimension.CumulVar(ride.dropoff_visit.node_index).Min(),
time_dimension.CumulVar(ride.dropoff_visit.node_index).Max()),
ride.dropoff_visit.tval - ride.pickup_visit.tval,
"{}..{}".format(int(min_dur), int(self.max_dur_mult * min_dur)),
"{}..{}".format(ride.pickup_visit.tmin, ride.pickup_visit.tmax),
"{}..{}".format(ride.dropoff_visit.tmin, ride.dropoff_visit.tmax),
ride.dropoff_visit.tmin - ride.pickup_visit.tmax
]
print(row_format.format(*vals))
class Ride(object):
def __init__(self, customer, route):
self.customer = customer
self.route = route
self.pickup_visit = None
self.dropoff_visit = None
class Visit(object):
def __init__(self, route_id, node_index, customer, demand, load, tmin, tmax, tval):
self.route_id = route_id
self.node_index = node_index
self.customer = customer
self.demand = demand
self.load = load
self.tmin = tmin
self.tmax = tmax
self.tval = tval
def is_pickup(self):
return self.demand > 0
# Custom travel time callback
class CreateCustomTimeCallback(object):
def __init__(self, locations, speed):
self.locations = locations
self.speed = speed
self._durations = {}
num_locations = len(self.locations)
# precompute distance between location to have distance callback in O(1)
for from_node in xrange(num_locations):
self._durations[from_node] = {}
for to_node in xrange(num_locations):
if from_node == to_node:
self._durations[from_node][to_node] = 0
else:
loc1 = self.locations[from_node]
loc2 = self.locations[to_node]
dist = self.distance(loc1[0], loc1[1], loc2[0], loc2[1])
dur = self._durations[from_node][to_node] = (3600 * dist) / self.speed
# print "{} {} {}".format(from_node, to_node, dur)
def Duration(self, from_node, to_node):
return self._durations[from_node][to_node]
#def Duration(self, manager,from_node, to_node):
#return self._durations[manager.NodeToIndex(from_node)][manager.NodeToIndex(to_node)]
def distance(self, lat1, long1, lat2, long2):
# Note: The formula used in this function is not exact, as it assumes
# the Earth is a perfect sphere.
# Mean radius of Earth in miles
radius_earth = 3959
# Convert latitude and longitude to
# spherical coordinates in radians.
degrees_to_radians = math.pi / 180.0
phi1 = lat1 * degrees_to_radians
phi2 = lat2 * degrees_to_radians
lambda1 = long1 * degrees_to_radians
lambda2 = long2 * degrees_to_radians
dphi = phi2 - phi1
dlambda = lambda2 - lambda1
a = self.haversine(dphi) + math.cos(phi1) * math.cos(phi2) * self.haversine(dlambda)
c = 2 * math.atan2(math.sqrt(a), math.sqrt(1 - a))
d = radius_earth * c
return d
def haversine(self, angle):
h = math.sin(angle / 2) ** 2
return h
class CreateDemandCallback(object):
def __init__(self, demands):
self.matrix = demands
def Demand(self, from_node, to_node):
return self.matrix[from_node]
class CreateServiceTimeCallback(object):
def __init__(self, demands=None, max_service_time=0):
self.matrix = demands
self.max_service_time = max_service_time
def ServiceTime(self, from_node, to_node):
return self.matrix and self.matrix[from_node] or self.max_service_time
class CreateTotalTimeCallback(object):
"""Create callback to get total times between locations."""
def __init__(self, service_time_callback, travel_time_callback):
self.service_time_callback = service_time_callback
self.travel_time_callback = travel_time_callback
def TotalTime(self, from_node, to_node):
service_time = self.service_time_callback(from_node, to_node)
travel_time = self.travel_time_callback(from_node, to_node)
return service_time + travel_time
if __name__ == '__main__':
main()@nttlinh you program is ill formed you forgot to use the manager in your callback to do a conversion between solver index and your data index (call Node).
Here you code fixed but your model (ed data) seems to lend to no solution....
import sys, os, math
from ortools.constraint_solver import pywrapcp
from ortools.constraint_solver import routing_enums_pb2
import matplotlib.pyplot as plt
import numpy as np
from six.moves import xrange
#from urllib3.connectionpool import xrange
def getopts(argv):
opts = {} # Empty dictionary to store key-value pairs.
while argv: # While there are arguments left to parse...
if argv[0][0] == '-': # Found a "-name value" pair.
opts[argv[0]] = argv[1] # Add key and value to the dictionary.
argv = argv[1:] # Reduce the argument list by copying it starting from index 1.
return opts
def main():
cmd_opts = getopts(sys.argv)
# configuration, problem description
depot = 0
num_vehicles = '--vehicles' in cmd_opts and int(cmd_opts['--vehicles']) or 10
vehicle_capacity = '--capacity' in cmd_opts and int(cmd_opts['--capacity']) or 10
speed = '--speed' in cmd_opts and int(cmd_opts['--speed']) or 40
search_time_limit = '--search_time_limit' in cmd_opts and int(
cmd_opts['--search_time_limit']) or 10 * 1000 # milliseconds
trip_service_duration_max = 0
max_dur_mult = '--max_dur_mult' in cmd_opts and float(cmd_opts['--max_dur_mult']) or 1.3
glob_span_cost_coef = '--glob_span_cost_coef' in cmd_opts and int(cmd_opts['--glob_span_cost_coef']) or None
plot = '--plot' in cmd_opts
print(
{
'vehicles': num_vehicles,
'capacity': vehicle_capacity,
'speed': speed,
'max_dur_mult': max_dur_mult,
'glob_span_cost_coef': glob_span_cost_coef,
})
customers = []
locations = []
demands = []
start_times = []
end_times = []
pickups = []
dropoffs = []
data = [
# customer lat lng demand start end pickup_index dropoff_index
[-1, 37.477749, -122.148499, 0, -1, -1, 0, 0],
[1, 37.467112, -122.253060, 1, 487, 2287, 0, 2],
[1, 37.477995, -122.148442, -1, 2623, 4423, 1, 0],
[2, 37.444040, -122.214423, 1, 678, 2478, 0, 4],
[2, 37.478331, -122.149008, -1, 2623, 4423, 3, 0],
[3, 37.455956, -122.285887, 1, 23, 1823, 0, 6],
[3, 37.478002, -122.148850, -1, 2623, 4423, 5, 0],
[4, 37.452259, -122.240702, 1, 537, 2337, 0, 8],
[4, 37.481572, -122.152584, -1, 2623, 4423, 7, 0],
[5, 37.447776, -122.257816, 1, 0, 1800, 0, 10],
[5, 37.485104, -122.147462, -1, 2623, 4423, 9, 0],
[6, 37.473287, -122.271279, 1, 704, 2504, 0, 12],
[6, 37.480284, -122.167614, -1, 2623, 4423, 11, 0],
[7, 37.558294, -122.263208, 1, 823, 2610, 0, 14],
[7, 37.481087, -122.166956, -1, 2640, 4423, 13, 0],
[8, 37.558294, -122.263208, 1, 0, 1800, 0, 16],
[8, 37.481087, -122.166956, -1, 2623, 4423, 15, 0],
]
for i in range(0, len(data)):
row = data[i]
customers.append(row[0])
locations.append([row[1], row[2]])
demands.append(row[3])
start_times.append(row[4])
end_times.append(row[5])
pickups.append(row[6])
dropoffs.append(row[7])
# build model
num_locations = len(locations)
#model_parameters = pywrapcp.RoutingModel.DefaultModelParameters()
model_parameters = pywrapcp.DefaultRoutingModelParameters()
# print model_parameters
manager = pywrapcp.RoutingIndexManager(num_locations,num_vehicles,depot)
routing = pywrapcp.RoutingModel(manager,model_parameters)
#routing = pywrapcp.RoutingModel(num_locations, num_vehicles, depot, model_parameters)
#search_parameters = pywrapcp.RoutingModel.DefaultSearchParameters()
search_parameters = pywrapcp.DefaultRoutingSearchParameters()
search_parameters.time_limit.seconds = search_time_limit
search_parameters.log_search = True
search_parameters.first_solution_strategy = (
routing_enums_pb2.FirstSolutionStrategy.PARALLEL_CHEAPEST_INSERTION)
# print search_parameters
#time_between_locations = CreateCustomTimeCallback(locations, speed)
time_between_locations = CreateCustomTimeCallback(manager, locations,speed)
arc_cost_callback = time_between_locations.Duration
arc_cost_callback1 = routing.RegisterTransitCallback(arc_cost_callback)
#arc_cost_callback = routing.RegisterTransitCallback(time_between_locations.Duration)
routing.SetArcCostEvaluatorOfAllVehicles(arc_cost_callback1)
demands_at_locations = CreateDemandCallback(manager, demands)
demands_callback = demands_at_locations.Demand
demands_callback1 = routing.RegisterUnaryTransitCallback(demands_callback)
routing.AddDimension(demands_callback1, 0, vehicle_capacity, True, "Capacity")
# time taken to load/unload at each location
service_times = CreateServiceTimeCallback(manager, demands, trip_service_duration_max)
service_time_callback = service_times.ServiceTime
# time taken to travel between locations
travel_time_callback = time_between_locations.Duration
total_times = CreateTotalTimeCallback(service_time_callback, travel_time_callback)
total_time_callback = total_times.TotalTime
total_time_callback1 = routing.RegisterTransitCallback(total_time_callback)
horizon = max(end_times) + 7600 # buffer beyond latest dropoff
routing.AddDimension(total_time_callback1, horizon, horizon, False, "Time")
# build pickup and delivery model
time_dimension = routing.GetDimensionOrDie("Time")
if glob_span_cost_coef:
time_dimension.SetGlobalSpanCostCoefficient(glob_span_cost_coef)
solver = routing.solver()
for i in range(1, num_locations):
#index = routing.IndexToNode(i)
index = manager.NodeToIndex(i)
time_dimension.CumulVar(i).SetRange(start_times[i], end_times[i])
if demands[i] != depot and pickups[i] == 0 and dropoffs[i] != 0: # don't setup precedence for depots
#delivery_index = routing.IndexToNode(dropoffs[i])
delivery_index = manager.NodeToIndex(dropoffs[i])
if delivery_index > 0:
solver.Add(routing.VehicleVar(index) == routing.VehicleVar(delivery_index))
solver.Add(time_dimension.CumulVar(index) <= time_dimension.CumulVar(delivery_index))
min_dur = int(travel_time_callback(index, delivery_index))
max_dur = int(max_dur_mult * min_dur)
dur_expr = time_dimension.CumulVar(delivery_index) - time_dimension.CumulVar(index)
solver.Add(dur_expr <= max_dur)
routing.AddPickupAndDelivery(i, dropoffs[i])
if plot:
plt.barh(customers, np.array(end_times) - np.array(start_times), left=start_times)
plt.yticks(customers)
plt.xlabel('pickup start,end .. dropoff start,end')
plt.ylabel('customers')
plt.show()
print('begin solving')
assignment = routing.SolveWithParameters(search_parameters)
if assignment:
print('solution exists')
printer = ConsolePrinter(num_vehicles, customers, demands, start_times,
end_times, pickups, dropoffs, travel_time_callback,
max_dur_mult, routing, assignment)
printer.print_solution()
else:
print('solution not found')
class ConsolePrinter():
def __init__(self, num_vehicles, customers, demands, start_times, end_times,
pickups, dropoffs, calc_travel_time, max_dur_mult, routing, assignment):
self.num_vehicles = num_vehicles
self.customers = customers
self.demands = demands
self.start_times = start_times
self.end_times = end_times
self.pickups = pickups
self.dropoffs = dropoffs
self.calc_travel_time = calc_travel_time
self.max_dur_mult = max_dur_mult
self.routing = routing
self.assignment = assignment
def print_solution(self):
print("Total duration of all routes: " + str(self.assignment.ObjectiveValue()) + "\n")
capacity_dimension = self.routing.GetDimensionOrDie("Capacity")
time_dimension = self.routing.GetDimensionOrDie("Time")
errors = None
plan_output = ''
rides = {}
for vehicle_nbr in range(self.num_vehicles):
veh_output = ''
index = self.routing.Start(vehicle_nbr)
empty = True
while not self.routing.IsEnd(index):
node_index = self.manager.IndexToNode(index)
customer = self.customers[node_index]
demand = self.demands[node_index]
load_var = capacity_dimension.CumulVar(index)
time_var = time_dimension.CumulVar(index)
visit = Visit(vehicle_nbr, node_index, customer, demand,
self.assignment.Value(load_var),
self.assignment.Min(time_var),
self.assignment.Max(time_var),
self.assignment.Value(time_var))
ride = rides.get(customer)
if not ride:
ride = rides[customer] = Ride(customer, vehicle_nbr)
if visit.is_pickup():
ride.pickup_visit = visit
else:
ride.dropoff_visit = visit
veh_output += \
"{route_id} {node_index} {customer} {demand} {load} {tmin} {tmax} {tval}".format(
route_id=vehicle_nbr,
node_index=node_index,
customer=customer,
demand=demand,
load=self.assignment.Value(load_var),
tmin=self.assignment.Min(time_var),
tmax=self.assignment.Max(time_var),
tval=self.assignment.Value(time_var))
if self.assignment.Value(load_var) > 0:
empty = False
veh_output += "\n"
index = self.assignment.Value(self.routing.NextVar(index))
node_index = self.manager.IndexToNode(index)
customer = self.customers[node_index]
demand = self.demands[node_index]
load_var = capacity_dimension.CumulVar(index)
time_var = time_dimension.CumulVar(index)
visit = Visit(vehicle_nbr, node_index, customer, demand,
self.assignment.Value(load_var),
self.assignment.Min(time_var),
self.assignment.Max(time_var),
self.assignment.Value(time_var))
veh_output += \
"{route_id} {node_index} {customer} {demand} {load} {tmin} {tmax} {tval}".format(
route_id=vehicle_nbr,
node_index=node_index,
customer=customer,
demand=demand,
load=self.assignment.Value(load_var),
tmin=self.assignment.Min(time_var),
tmax=self.assignment.Max(time_var),
tval=self.assignment.Value(time_var))
veh_output += "\n"
if not empty:
plan_output += veh_output
print("route_id node_index customer demand load tmin tmax tval")
print(plan_output)
ride_list = rides.values()
cols = ['cust (pnode..dnode)', 'route',
'pickup_at..dropoff_at',
'cnstr_pickup', 'cnstr_dropoff',
'plan_dur',
'cnstr_dur',
'plan_pickup_range',
'plan_dropoff_range',
'plan_min_poss_dur']
row_format = "".join(map(lambda c: "{:>" + str(len(c) + 4) + "}", cols))
print(row_format.format(*cols))
for i in range(0, len(ride_list)):
ride = ride_list[i]
if not ride.pickup_visit:
continue
min_dur = self.calc_travel_time(ride.pickup_visit.node_index, ride.dropoff_visit.node_index)
vals = ["{} {}..{}".format(ride.customer, ride.pickup_visit.node_index, ride.dropoff_visit.node_index),
ride.route,
"{}..{}".format(ride.pickup_visit.tval, ride.dropoff_visit.tval),
"{}..{}".format(time_dimension.CumulVar(ride.pickup_visit.node_index).Min(),
time_dimension.CumulVar(ride.pickup_visit.node_index).Max()),
"{}..{}".format(time_dimension.CumulVar(ride.dropoff_visit.node_index).Min(),
time_dimension.CumulVar(ride.dropoff_visit.node_index).Max()),
ride.dropoff_visit.tval - ride.pickup_visit.tval,
"{}..{}".format(int(min_dur), int(self.max_dur_mult * min_dur)),
"{}..{}".format(ride.pickup_visit.tmin, ride.pickup_visit.tmax),
"{}..{}".format(ride.dropoff_visit.tmin, ride.dropoff_visit.tmax),
ride.dropoff_visit.tmin - ride.pickup_visit.tmax
]
print(row_format.format(*vals))
class Ride(object):
def __init__(self, customer, route):
self.customer = customer
self.route = route
self.pickup_visit = None
self.dropoff_visit = None
class Visit(object):
def __init__(self, route_id, node_index, customer, demand, load, tmin, tmax, tval):
self.route_id = route_id
self.node_index = node_index
self.customer = customer
self.demand = demand
self.load = load
self.tmin = tmin
self.tmax = tmax
self.tval = tval
def is_pickup(self):
return self.demand > 0
# Custom travel time callback
class CreateCustomTimeCallback(object):
def __init__(self, manager, locations, speed):
self.manager = manager
self.locations = locations
self.speed = speed
self._durations = {}
num_locations = len(self.locations)
# precompute distance between location to have distance callback in O(1)
for from_node in xrange(num_locations):
self._durations[from_node] = {}
for to_node in xrange(num_locations):
if from_node == to_node:
self._durations[from_node][to_node] = 0
else:
loc1 = self.locations[from_node]
loc2 = self.locations[to_node]
dist = self.distance(loc1[0], loc1[1], loc2[0], loc2[1])
dur = self._durations[from_node][to_node] = (3600 * dist) / self.speed
# print "{} {} {}".format(from_node, to_node, dur)
def Duration(self, from_index, to_index):
from_node = self.manager.IndexToNode(from_index)
to_node = self.manager.IndexToNode(to_index)
return self._durations[from_node][to_node]
#def Duration(self, manager,from_node, to_node):
#return self._durations[manager.NodeToIndex(from_node)][manager.NodeToIndex(to_node)]
def distance(self, lat1, long1, lat2, long2):
# Note: The formula used in this function is not exact, as it assumes
# the Earth is a perfect sphere.
# Mean radius of Earth in miles
radius_earth = 3959
# Convert latitude and longitude to
# spherical coordinates in radians.
degrees_to_radians = math.pi / 180.0
phi1 = lat1 * degrees_to_radians
phi2 = lat2 * degrees_to_radians
lambda1 = long1 * degrees_to_radians
lambda2 = long2 * degrees_to_radians
dphi = phi2 - phi1
dlambda = lambda2 - lambda1
a = self.haversine(dphi) + math.cos(phi1) * math.cos(phi2) * self.haversine(dlambda)
c = 2 * math.atan2(math.sqrt(a), math.sqrt(1 - a))
d = radius_earth * c
return d
def haversine(self, angle):
h = math.sin(angle / 2) ** 2
return h
class CreateDemandCallback(object):
def __init__(self, manager, demands):
self.manager = manager
self.matrix = demands
def Demand(self, from_index):
from_node = self.manager.IndexToNode(from_index)
return self.matrix[from_node]
class CreateServiceTimeCallback(object):
def __init__(self, manager, demands=None, max_service_time=0):
self.manager = manager
self.matrix = demands
self.max_service_time = max_service_time
def ServiceTime(self, from_index):
from_node = self.manager.IndexToNode(from_index)
if self.matrix is None:
return self.max_service_time
else:
return self.matrix[from_node]
class CreateTotalTimeCallback(object):
"""Create callback to get total times between locations."""
def __init__(self, service_time_callback, travel_time_callback):
self.service_time_callback = service_time_callback
self.travel_time_callback = travel_time_callback
def TotalTime(self, from_index, to_index):
service_time = self.service_time_callback(from_index)
travel_time = self.travel_time_callback(from_index, to_index)
return service_time + travel_time
if __name__ == '__main__':
main()Thanks for your help
On Wed, May 15, 2019 at 2:17 PM Mizux notifications@github.com wrote:
@nttlinh https://github.com/nttlinh you program is ill formed you forgot to use the manager in your callback to do a conversion between solver index and your data index (call Node).
Here you code fixed but your model (ed data) seems to lend to no solution....
import sys, os, mathfrom ortools.constraint_solver import pywrapcpfrom ortools.constraint_solver import routing_enums_pb2import matplotlib.pyplot as pltimport numpy as npfrom six.moves import xrange#from urllib3.connectionpool import xrange def getopts(argv): opts = {} # Empty dictionary to store key-value pairs. while argv: # While there are arguments left to parse... if argv[0][0] == '-': # Found a "-name value" pair. opts[argv[0]] = argv[1] # Add key and value to the dictionary. argv = argv[1:] # Reduce the argument list by copying it starting from index 1. return opts
def main(): cmd_opts = getopts(sys.argv)
configuration, problem description
depot = 0 num_vehicles = '--vehicles' in cmd_opts and int(cmd_opts['--vehicles']) or 10 vehicle_capacity = '--capacity' in cmd_opts and int(cmd_opts['--capacity']) or 10 speed = '--speed' in cmd_opts and int(cmd_opts['--speed']) or 40 search_time_limit = '--search_time_limit' in cmd_opts and int( cmd_opts['--search_time_limit']) or 10 * 1000 # milliseconds trip_service_duration_max = 0 max_dur_mult = '--max_dur_mult' in cmd_opts and float(cmd_opts['--max_dur_mult']) or 1.3 glob_span_cost_coef = '--glob_span_cost_coef' in cmd_opts and int(cmd_opts['--glob_span_cost_coef']) or None plot = '--plot' in cmd_opts print( { 'vehicles': num_vehicles, 'capacity': vehicle_capacity, 'speed': speed, 'max_dur_mult': max_dur_mult, 'glob_span_cost_coef': glob_span_cost_coef, }) customers = [] locations = [] demands = [] start_times = [] end_times = [] pickups = [] dropoffs = [] data = [ # customer lat lng demand start end pickup_index dropoff_index [-1, 37.477749, -122.148499, 0, -1, -1, 0, 0], [1, 37.467112, -122.253060, 1, 487, 2287, 0, 2], [1, 37.477995, -122.148442, -1, 2623, 4423, 1, 0], [2, 37.444040, -122.214423, 1, 678, 2478, 0, 4], [2, 37.478331, -122.149008, -1, 2623, 4423, 3, 0], [3, 37.455956, -122.285887, 1, 23, 1823, 0, 6], [3, 37.478002, -122.148850, -1, 2623, 4423, 5, 0], [4, 37.452259, -122.240702, 1, 537, 2337, 0, 8], [4, 37.481572, -122.152584, -1, 2623, 4423, 7, 0], [5, 37.447776, -122.257816, 1, 0, 1800, 0, 10], [5, 37.485104, -122.147462, -1, 2623, 4423, 9, 0], [6, 37.473287, -122.271279, 1, 704, 2504, 0, 12], [6, 37.480284, -122.167614, -1, 2623, 4423, 11, 0], [7, 37.558294, -122.263208, 1, 823, 2610, 0, 14], [7, 37.481087, -122.166956, -1, 2640, 4423, 13, 0], [8, 37.558294, -122.263208, 1, 0, 1800, 0, 16], [8, 37.481087, -122.166956, -1, 2623, 4423, 15, 0], ] for i in range(0, len(data)): row = data[i] customers.append(row[0]) locations.append([row[1], row[2]]) demands.append(row[3]) start_times.append(row[4]) end_times.append(row[5]) pickups.append(row[6]) dropoffs.append(row[7]) # build model num_locations = len(locations) #model_parameters = pywrapcp.RoutingModel.DefaultModelParameters() model_parameters = pywrapcp.DefaultRoutingModelParameters() # print model_parameters manager = pywrapcp.RoutingIndexManager(num_locations,num_vehicles,depot) routing = pywrapcp.RoutingModel(manager,model_parameters) #routing = pywrapcp.RoutingModel(num_locations, num_vehicles, depot, model_parameters) #search_parameters = pywrapcp.RoutingModel.DefaultSearchParameters() search_parameters = pywrapcp.DefaultRoutingSearchParameters() search_parameters.time_limit.seconds = search_time_limit search_parameters.log_search = True search_parameters.first_solution_strategy = ( routing_enums_pb2.FirstSolutionStrategy.PARALLEL_CHEAPEST_INSERTION) # print search_parameters #time_between_locations = CreateCustomTimeCallback(locations, speed) time_between_locations = CreateCustomTimeCallback(manager, locations,speed) arc_cost_callback = time_between_locations.Duration arc_cost_callback1 = routing.RegisterTransitCallback(arc_cost_callback) #arc_cost_callback = routing.RegisterTransitCallback(time_between_locations.Duration) routing.SetArcCostEvaluatorOfAllVehicles(arc_cost_callback1) demands_at_locations = CreateDemandCallback(manager, demands) demands_callback = demands_at_locations.Demand demands_callback1 = routing.RegisterUnaryTransitCallback(demands_callback) routing.AddDimension(demands_callback1, 0, vehicle_capacity, True, "Capacity") # time taken to load/unload at each location service_times = CreateServiceTimeCallback(manager, demands, trip_service_duration_max) service_time_callback = service_times.ServiceTime # time taken to travel between locations travel_time_callback = time_between_locations.Duration total_times = CreateTotalTimeCallback(service_time_callback, travel_time_callback) total_time_callback = total_times.TotalTime total_time_callback1 = routing.RegisterTransitCallback(total_time_callback) horizon = max(end_times) + 7600 # buffer beyond latest dropoff routing.AddDimension(total_time_callback1, horizon, horizon, False, "Time") # build pickup and delivery model time_dimension = routing.GetDimensionOrDie("Time") if glob_span_cost_coef: time_dimension.SetGlobalSpanCostCoefficient(glob_span_cost_coef) solver = routing.solver() for i in range(1, num_locations): #index = routing.IndexToNode(i) index = manager.NodeToIndex(i) time_dimension.CumulVar(i).SetRange(start_times[i], end_times[i]) if demands[i] != depot and pickups[i] == 0 and dropoffs[i] != 0: # don't setup precedence for depots #delivery_index = routing.IndexToNode(dropoffs[i]) delivery_index = manager.NodeToIndex(dropoffs[i]) if delivery_index > 0: solver.Add(routing.VehicleVar(index) == routing.VehicleVar(delivery_index)) solver.Add(time_dimension.CumulVar(index) <= time_dimension.CumulVar(delivery_index)) min_dur = int(travel_time_callback(index, delivery_index)) max_dur = int(max_dur_mult * min_dur) dur_expr = time_dimension.CumulVar(delivery_index) - time_dimension.CumulVar(index) solver.Add(dur_expr <= max_dur) routing.AddPickupAndDelivery(i, dropoffs[i]) if plot: plt.barh(customers, np.array(end_times) - np.array(start_times), left=start_times) plt.yticks(customers) plt.xlabel('pickup start,end .. dropoff start,end') plt.ylabel('customers') plt.show() print('begin solving') assignment = routing.SolveWithParameters(search_parameters) if assignment: print('solution exists') printer = ConsolePrinter(num_vehicles, customers, demands, start_times, end_times, pickups, dropoffs, travel_time_callback, max_dur_mult, routing, assignment) printer.print_solution() else: print('solution not found')class ConsolePrinter(): def init(self, num_vehicles, customers, demands, start_times, end_times, pickups, dropoffs, calc_travel_time, max_dur_mult, routing, assignment): self.num_vehicles = num_vehicles self.customers = customers self.demands = demands self.start_times = start_times self.end_times = end_times self.pickups = pickups self.dropoffs = dropoffs self.calc_travel_time = calc_travel_time self.max_dur_mult = max_dur_mult self.routing = routing self.assignment = assignment
def print_solution(self): print("Total duration of all routes: " + str(self.assignment.ObjectiveValue()) + "\n") capacity_dimension = self.routing.GetDimensionOrDie("Capacity") time_dimension = self.routing.GetDimensionOrDie("Time") errors = None plan_output = '' rides = {} for vehicle_nbr in range(self.num_vehicles): veh_output = '' index = self.routing.Start(vehicle_nbr) empty = True while not self.routing.IsEnd(index): node_index = self.manager.IndexToNode(index) customer = self.customers[node_index] demand = self.demands[node_index] load_var = capacity_dimension.CumulVar(index) time_var = time_dimension.CumulVar(index) visit = Visit(vehicle_nbr, node_index, customer, demand, self.assignment.Value(load_var), self.assignment.Min(time_var), self.assignment.Max(time_var), self.assignment.Value(time_var)) ride = rides.get(customer) if not ride: ride = rides[customer] = Ride(customer, vehicle_nbr) if visit.is_pickup(): ride.pickup_visit = visit else: ride.dropoff_visit = visit veh_output += \ "{route_id} {node_index} {customer} {demand} {load} {tmin} {tmax} {tval}".format( route_id=vehicle_nbr, node_index=node_index, customer=customer, demand=demand, load=self.assignment.Value(load_var), tmin=self.assignment.Min(time_var), tmax=self.assignment.Max(time_var), tval=self.assignment.Value(time_var)) if self.assignment.Value(load_var) > 0: empty = False veh_output += "\n" index = self.assignment.Value(self.routing.NextVar(index)) node_index = self.manager.IndexToNode(index) customer = self.customers[node_index] demand = self.demands[node_index] load_var = capacity_dimension.CumulVar(index) time_var = time_dimension.CumulVar(index) visit = Visit(vehicle_nbr, node_index, customer, demand, self.assignment.Value(load_var), self.assignment.Min(time_var), self.assignment.Max(time_var), self.assignment.Value(time_var)) veh_output += \ "{route_id} {node_index} {customer} {demand} {load} {tmin} {tmax} {tval}".format( route_id=vehicle_nbr, node_index=node_index, customer=customer, demand=demand, load=self.assignment.Value(load_var), tmin=self.assignment.Min(time_var), tmax=self.assignment.Max(time_var), tval=self.assignment.Value(time_var)) veh_output += "\n" if not empty: plan_output += veh_output print("route_id node_index customer demand load tmin tmax tval") print(plan_output) ride_list = rides.values() cols = ['cust (pnode..dnode)', 'route', 'pickup_at..dropoff_at', 'cnstr_pickup', 'cnstr_dropoff', 'plan_dur', 'cnstr_dur', 'plan_pickup_range', 'plan_dropoff_range', 'plan_min_poss_dur'] row_format = "".join(map(lambda c: "{:>" + str(len(c) + 4) + "}", cols)) print(row_format.format(*cols)) for i in range(0, len(ride_list)): ride = ride_list[i] if not ride.pickup_visit: continue min_dur = self.calc_travel_time(ride.pickup_visit.node_index, ride.dropoff_visit.node_index) vals = ["{} {}..{}".format(ride.customer, ride.pickup_visit.node_index, ride.dropoff_visit.node_index), ride.route, "{}..{}".format(ride.pickup_visit.tval, ride.dropoff_visit.tval), "{}..{}".format(time_dimension.CumulVar(ride.pickup_visit.node_index).Min(), time_dimension.CumulVar(ride.pickup_visit.node_index).Max()), "{}..{}".format(time_dimension.CumulVar(ride.dropoff_visit.node_index).Min(), time_dimension.CumulVar(ride.dropoff_visit.node_index).Max()), ride.dropoff_visit.tval - ride.pickup_visit.tval, "{}..{}".format(int(min_dur), int(self.max_dur_mult * min_dur)), "{}..{}".format(ride.pickup_visit.tmin, ride.pickup_visit.tmax), "{}..{}".format(ride.dropoff_visit.tmin, ride.dropoff_visit.tmax), ride.dropoff_visit.tmin - ride.pickup_visit.tmax ] print(row_format.format(*vals))class Ride(object): def init(self, customer, route): self.customer = customer self.route = route self.pickup_visit = None self.dropoff_visit = None
class Visit(object): def init(self, route_id, node_index, customer, demand, load, tmin, tmax, tval): self.route_id = route_id self.node_index = node_index self.customer = customer self.demand = demand self.load = load self.tmin = tmin self.tmax = tmax self.tval = tval
def is_pickup(self): return self.demand > 0Custom travel time callbackclass CreateCustomTimeCallback(object):
def __init__(self, manager, locations, speed): self.manager = manager self.locations = locations self.speed = speed self._durations = {} num_locations = len(self.locations) # precompute distance between location to have distance callback in O(1) for from_node in xrange(num_locations): self._durations[from_node] = {} for to_node in xrange(num_locations): if from_node == to_node: self._durations[from_node][to_node] = 0 else: loc1 = self.locations[from_node] loc2 = self.locations[to_node] dist = self.distance(loc1[0], loc1[1], loc2[0], loc2[1]) dur = self._durations[from_node][to_node] = (3600 * dist) / self.speed # print "{} {} {}".format(from_node, to_node, dur) def Duration(self, from_index, to_index): from_node = self.manager.IndexToNode(from_index) to_node = self.manager.IndexToNode(to_index) return self._durations[from_node][to_node] #def Duration(self, manager,from_node, to_node): #return self._durations[manager.NodeToIndex(from_node)][manager.NodeToIndex(to_node)] def distance(self, lat1, long1, lat2, long2): # Note: The formula used in this function is not exact, as it assumes # the Earth is a perfect sphere. # Mean radius of Earth in miles radius_earth = 3959 # Convert latitude and longitude to # spherical coordinates in radians. degrees_to_radians = math.pi / 180.0 phi1 = lat1 * degrees_to_radians phi2 = lat2 * degrees_to_radians lambda1 = long1 * degrees_to_radians lambda2 = long2 * degrees_to_radians dphi = phi2 - phi1 dlambda = lambda2 - lambda1 a = self.haversine(dphi) + math.cos(phi1) * math.cos(phi2) * self.haversine(dlambda) c = 2 * math.atan2(math.sqrt(a), math.sqrt(1 - a)) d = radius_earth * c return d def haversine(self, angle): h = math.sin(angle / 2) ** 2 return hclass CreateDemandCallback(object): def init(self, manager, demands): self.manager = manager self.matrix = demands
def Demand(self, from_index): from_node = self.manager.IndexToNode(from_index) return self.matrix[from_node]class CreateServiceTimeCallback(object): def init(self, manager, demands=None, max_service_time=0): self.manager = manager self.matrix = demands self.max_service_time = max_service_time
def ServiceTime(self, from_index): from_node = self.manager.IndexToNode(from_index) if self.matrix is None: return self.max_service_time else: return self.matrix[from_node]class CreateTotalTimeCallback(object): """Create callback to get total times between locations.""" def init(self, service_time_callback, travel_time_callback): self.service_time_callback = service_time_callback self.travel_time_callback = travel_time_callback
def TotalTime(self, from_index, to_index): service_time = self.service_time_callback(from_index) travel_time = self.travel_time_callback(from_index, to_index) return service_time + travel_timeif name == 'main': main()
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shandilya1998
commented
5 years ago I have been facing the same issue. The only difference in my case is that the start and end point of vehicles are different. I am getting a solution for same start and end point of all the vehicles, but getting this for the code below
`RuntimeError: SWIG std::function invocation failed.
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/Users/travelapp/PycharmProjects/TravelApp/venv/lib/python3.7/site-packages/ortools/constraint_solver/pywrapcp.py", line 2136, in <lambda>
__setattr__ = lambda self, name, value: _swig_setattr(self, Assignment, name, value)
File "/Users/travelapp/PycharmProjects/TravelApp/venv/lib/python3.7/site-packages/ortools/constraint_solver/pywrapcp.py", line 71, in _swig_setattr
return _swig_setattr_nondynamic(self, class_type, name, value, 0)
File "/Users/travelapp/PycharmProjects/TravelApp/venv/lib/python3.7/site-packages/ortools/constraint_solver/pywrapcp.py", line 55, in _swig_setattr_nondynamic
if type(value).__name__ == 'SwigPyObject':
SystemError: <class 'type'> returned a result with an error set
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/Users/travelapp/PycharmProjects/TravelApp/travelapp.py", line 213, in <module>
from travelapp import TripPlanner
File "/Users/travelapp/PycharmProjects/TravelApp/travelapp.py", line 215, in <module>
ob.plan_trip
File "/Users/travelapp/PycharmProjects/TravelApp/travelapp.py", line 206, in plan_trip
solution = routing.SolveWithParameters(search_parameters)
File "/Users/travelapp/PycharmProjects/TravelApp/venv/lib/python3.7/site-packages/ortools/constraint_solver/pywrapcp.py", line 3464, in SolveWithParameters
return _pywrapcp.RoutingModel_SolveWithParameters(self, search_parameters, solutions)
SystemError: <built-in function RoutingModel_SolveWithParameters> returned a result with an error set`
This is my code- ` from future import print_function from ortools.constraint_solver import routing_enums_pb2 from ortools.constraint_solver import pywrapcp class TripPlanner():
def __init(self):
self.trip = []
def create_data_model(self):
# retrieves data data for the problem
# calls distance matrix api
# currently test values have been plugged in
data = {}
data['time_matrix'] = [
[0, 6, 7, 9, 7, 3, 6, 2, 3, 2, 6, 6, 4, 4, 5, 9, 7,0],
[6, 0, 8, 3, 2, 6, 8, 4, 8, 8, 13, 7, 5, 8, 12, 12, 14, 6],
[9, 8, 0, 11, 10, 6, 3, 9, 5, 8, 14, 15, 14, 13, 9, 18, 9, 15],
[8, 3, 11, 0, 1, 7, 10, 6, 10, 10, 14, 6, 7, 9, 14, 6, 16, 14],
[7, 2, 10, 3, 0, 6, 9, 4, 10, 19, 13, 4, 6, 18, 12, 8, 14, 9],
[3, 6, 6, 7, 6, 0, 2, 8, 2, 2, 7, 9, 7, 7, 6, 12, 8, 3],
[6, 8, 3, 10, 9, 2, 0, 6, 2, 5, 4, 12, 10, 10, 6, 15, 5, 10],
[2, 4, 9, 6, 4, 3, 6, 0, 4, 4, 18, 5, 4, 23, 7, 8, 10, 12],
[3, 8, 5, 10, 8, 2, 2, 4, 0, 3, 4, 9, 8, 7, 3, 13, 6, 5],
[2, 8, 8, 10, 9, 2, 5, 4, 3, 0, 4, 6, 5, 4, 3, 9, 5, 8],
[6, 13, 4, 14, 13, 7, 4, 8, 4, 4, 0, 10, 9, 8, 4, 13, 4, 9],
[6, 7, 15, 6, 24, 9, 12, 5, 9, 6, 10, 0, 1, 3, 7, 13, 10, 11],
[4, 5, 14, 8, 6, 7, 10, 4, 8, 5, 9, 1, 0, 2, 26, 4, 8, 1],
[4, 8, 13, 9, 8, 7, 10, 13, 7, 4, 8, 3, 2, 0, 4, 5, 6, 2],
[5, 12, 9, 14, 12, 2, 6, 7, 13, 13, 4, 7, 6, 4, 0, 9, 12, 4],
[9, 10, 18, 6, 8, 12, 20, 8, 3, 9, 13, 3, 4, 5, 9, 0, 9,10],
[7, 14, 9, 16, 14, 8, 5, 10, 6, 5, 4, 10, 8, 6, 2, 9, 0,13],
[0, 4, 4, 6, 9, 2, 5, 8, 4, 2, 5, 15, 7, 1, 5, 13, 1, 0]
]
data['time_windows'] = [
(0, 22), # depot
(7, 12), # 1
(10, 15), # 2
(16, 18), # 3
(10, 13), # 4
(0, 5), # 5
(5, 10), # 6
(0, 4), # 7
(5, 10), # 8
(0, 3), # 9
(10, 16), # 10
(10, 15), # 11
(0, 5), # 12
(5, 10), # 13
(7, 8), # 14
(10, 15), # 15
(11, 15), # 16
(18,22) #17
]
data['num_days'] = 4
data['start'] = [0,0,0,0]#,17,0,17]
data['end'] = [17,17,17,17]
return data
def print_solutions(self,
data,
manager,
routing,
assignment):
# prints the final routing solution on the console
time_dimension = routing.GetDimensionOrDie('Time')
total_time = 0
for vehicle_id in range(data['num_days']):
index = routing.Start(vehicle_id)
plan_output = 'Route for vehicle {}:\n'.format(vehicle_id)
while not routing.IsEnd(index):
time_var = time_dimension.CumulVar(index)
plan_output += '{0} Time({1},{2}) -> '.format(
manager.IndexToNode(index), assignment.Min(time_var),
assignment.Max(time_var))
index = assignment.Value(routing.NextVar(index))
time_var = time_dimension.CumulVar(index)
plan_output += '{0} Time({1},{2})\n'.format(
manager.IndexToNode(index), assignment.Min(time_var),
assignment.Max(time_var))
plan_output += 'Time of the route: {}min\n'.format(
assignment.Min(time_var))
print(plan_output)
total_time += assignment.Min(time_var)
print('Total time of all routes: {}min'.format(total_time))
@property
def plan_trip(self):
"""Entry point of the program."""
# Instantiate the data problem.
data = self.create_data_model()
# Create the routing index manager.
manager = pywrapcp.RoutingIndexManager(
len(data['time_matrix']), data['num_days'], data['start'], data['end'])
# Create Routing Model.
routing = pywrapcp.RoutingModel(manager)
# Create and register a transit callback.
def time_callback(from_index, to_index):
"""Returns the distance between the two nodes."""
# Convert from routing variable Index to distance matrix NodeIndex.
from_node = manager.IndexToNode(from_index)
to_node = manager.IndexToNode(to_index)
return data['time_matrix'][from_node][to_node]
transit_callback_index = routing.RegisterTransitCallback(time_callback)
# Define cost of each arc.
routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index)
# Add Distance constraint.
dimension_name = 'Time'
routing.AddDimension(
transit_callback_index,
30, # maximum waiting time for a vehicle
30, # vehicle maximum travel time
False, # start cumul to zero
dimension_name)
time_dimension = routing.GetDimensionOrDie(dimension_name)
# Add time window constraints for each location except depot.
for location_idx, time_window in enumerate(data['time_windows']):
if location_idx == 0:
continue
index = manager.NodeToIndex(location_idx)
print(location_idx)
print(index)
print(time_dimension.CumulVar(index))
time_dimension.CumulVar(index).SetRange(time_window[0], time_window[1])
# Add time window constraints for each vehicle start node.
for vehicle_id in range(data['num_days']):
index = routing.Start(vehicle_id)
time_dimension.CumulVar(index).SetRange(data['time_windows'][0][0],
data['time_windows'][0][1])
for i in range(data['num_days']):
routing.AddVariableMinimizedByFinalizer(
time_dimension.CumulVar(routing.Start(i)))
routing.AddVariableMinimizedByFinalizer(
time_dimension.CumulVar(routing.End(i)))
time_dimension.SetSpanCostCoefficientForAllVehicles(30)
# Setting first solution heuristic.
search_parameters = pywrapcp.DefaultRoutingSearchParameters()
search_parameters.first_solution_strategy = (
routing_enums_pb2.FirstSolutionStrategy.PATH_CHEAPEST_ARC)
# Solve the problem.
solution = routing.SolveWithParameters(search_parameters)
# Print solution on console.
if solution:
self.print_solutions(data, manager, routing, solution)from travelapp import TripPlanner ob = TripPlanner() ob.plan_trip
` Could someone tell what am i doing wrong. This is my first time using ORtools
lperron
commented
5 years ago Most likely a python exception thrown in the distance callback. Can you add a try catch around your code ? Laurent Perron | Operations Research | lperron@google.com | (33) 1 42 68 53 00
Le sam. 20 juil. 2019 à 09:49, shandilya1998 notifications@github.com a écrit :
I have been facing the same issue. The only difference in my case is that the start and end point of vehicles are different. I am getting a solution for same start and end point of all the vehicles, but getting this for the code below `RuntimeError: SWIG std::function invocation failed.
The above exception was the direct cause of the following exception:
Traceback (most recent call last): File "/Users/travelapp/PycharmProjects/TravelApp/venv/lib/python3.7/site-packages/ortools/constraint_solver/pywrapcp.py", line 2136, in setattr = lambda self, name, value: _swig_setattr(self, Assignment, name, value) File "/Users/travelapp/PycharmProjects/TravelApp/venv/lib/python3.7/site-packages/ortools/constraint_solver/pywrapcp.py", line 71, in _swig_setattr return _swig_setattr_nondynamic(self, class_type, name, value, 0) File "/Users/travelapp/PycharmProjects/TravelApp/venv/lib/python3.7/site-packages/ortools/constraint_solver/pywrapcp.py", line 55, in _swig_setattr_nondynamic if type(value).name == 'SwigPyObject': SystemError: <class 'type'> returned a result with an error set
The above exception was the direct cause of the following exception:
Traceback (most recent call last): File "/Users/travelapp/PycharmProjects/TravelApp/travelapp.py", line 213, in from travelapp import TripPlanner File "/Users/travelapp/PycharmProjects/TravelApp/travelapp.py", line 215, in ob.plan_trip File "/Users/travelapp/PycharmProjects/TravelApp/travelapp.py", line 206, in plan_trip solution = routing.SolveWithParameters(search_parameters) File "/Users/travelapp/PycharmProjects/TravelApp/venv/lib/python3.7/site-packages/ortools/constraint_solver/pywrapcp.py", line 3464, in SolveWithParameters return _pywrapcp.RoutingModel_SolveWithParameters(self, search_parameters, solutions) SystemError: returned a result with an error set`
This is my code- `from future import print_function from typing import List, Any from app import app, db from app.models import placeDescriptionTag, places from app.APICalls import call_places_details_api, call_places_photos_api, call_places_text_api from ortools.constraint_solver import routing_enums_pb2 from ortools.constraint_solver import pywrapcp
class PopulatePlaces():
def init(self, city): self.tag_lst = [] self.city = city
def add_city(self): for tag in self.tag_lst:
create_query() creates a query to Places Text api to get a list of places for tag
query = self.create_query(self.city, tag) # call_places_api() calls Places Text API and Places Details API, # and stores the responses in the database self.call_places_api(query, tag)def call_places_api(self, query, tag):
call_place_text_api() calls places text search API with query
# and returns data with place_id as key to retrieve all data for each place data = call_places_text_api(query) # place_id is the place ID used by google to uniquely identify each place in their database for place_id in data: tag_place = placeDescriptionTag(idplaces = place_id, tag = tag) exists = places.in_places(place_id) if exists: db.session.add(tag_place) db.session.commit() else: # Complete the initialization of the places object # Make changes in places table to that data can be added sequentially # as it is being queried from places API place = places() # call_places_details_api() queries for place details from places details API place_details = call_places_details_api(place_id) # call_places_photos_api() queries place photos from places photos API place_photo = call_places_photos_api(place_id) # replace the next two statement based on the response # received from places details API and places photos API place.details = place_details place.photo = place_photo db.session.add(tag_place) db.session.add(place) db.session.commit()def create_query(self, city, tag):
Check how this function can be used for every call to API function
return 'query'class TripPlanner():
def __init(self): self.trip = []
def create_data_model(self):
retrieves data data for the problem
# calls distance matrix api # currently test values have been plugged in data = {} data['time_matrix'] = [ [0, 6, 7, 9, 7, 3, 6, 2, 3, 2, 6, 6, 4, 4, 5, 9, 7,0], [6, 0, 8, 3, 2, 6, 8, 4, 8, 8, 13, 7, 5, 8, 12, 12, 14, 6], [9, 8, 0, 11, 10, 6, 3, 9, 5, 8, 14, 15, 14, 13, 9, 18, 9, 15], [8, 3, 11, 0, 1, 7, 10, 6, 10, 10, 14, 6, 7, 9, 14, 6, 16, 14], [7, 2, 10, 3, 0, 6, 9, 4, 10, 19, 13, 4, 6, 18, 12, 8, 14, 9], [3, 6, 6, 7, 6, 0, 2, 8, 2, 2, 7, 9, 7, 7, 6, 12, 8, 3], [6, 8, 3, 10, 9, 2, 0, 6, 2, 5, 4, 12, 10, 10, 6, 15, 5, 10], [2, 4, 9, 6, 4, 3, 6, 0, 4, 4, 18, 5, 4, 23, 7, 8, 10, 12], [3, 8, 5, 10, 8, 2, 2, 4, 0, 3, 4, 9, 8, 7, 3, 13, 6, 5], [2, 8, 8, 10, 9, 2, 5, 4, 3, 0, 4, 6, 5, 4, 3, 9, 5, 8], [6, 13, 4, 14, 13, 7, 4, 8, 4, 4, 0, 10, 9, 8, 4, 13, 4, 9], [6, 7, 15, 6, 24, 9, 12, 5, 9, 6, 10, 0, 1, 3, 7, 13, 10, 11], [4, 5, 14, 8, 6, 7, 10, 4, 8, 5, 9, 1, 0, 2, 26, 4, 8, 1], [4, 8, 13, 9, 8, 7, 10, 13, 7, 4, 8, 3, 2, 0, 4, 5, 6, 2], [5, 12, 9, 14, 12, 2, 6, 7, 13, 13, 4, 7, 6, 4, 0, 9, 12, 4], [9, 10, 18, 6, 8, 12, 20, 8, 3, 9, 13, 3, 4, 5, 9, 0, 9,10], [7, 14, 9, 16, 14, 8, 5, 10, 6, 5, 4, 10, 8, 6, 2, 9, 0,13], [0, 4, 4, 6, 9, 2, 5, 8, 4, 2, 5, 15, 7, 1, 5, 13, 1, 0] ] data['time_windows'] = [ (0, 22), # depot (7, 12), # 1 (10, 15), # 2 (16, 18), # 3 (10, 13), # 4 (0, 5), # 5 (5, 10), # 6 (0, 4), # 7 (5, 10), # 8 (0, 3), # 9 (10, 16), # 10 (10, 15), # 11 (0, 5), # 12 (5, 10), # 13 (7, 8), # 14 (10, 15), # 15 (11, 15), # 16 (18,22) #17 ] data['num_days'] = 4 data['start'] = [0,0,0,0]#,17,0,17] data['end'] = [17,17,17,17] return datadef print_solutions(self, data, manager, routing, assignment):
prints the final routing solution on the console
time_dimension = routing.GetDimensionOrDie('Time') total_time = 0 for vehicle_id in range(data['num_days']): index = routing.Start(vehicle_id) plan_output = 'Route for vehicle {}:\n'.format(vehicle_id) while not routing.IsEnd(index): time_var = time_dimension.CumulVar(index) plan_output += '{0} Time({1},{2}) -> '.format( manager.IndexToNode(index), assignment.Min(time_var), assignment.Max(time_var)) index = assignment.Value(routing.NextVar(index)) time_var = time_dimension.CumulVar(index) plan_output += '{0} Time({1},{2})\n'.format( manager.IndexToNode(index), assignment.Min(time_var), assignment.Max(time_var)) plan_output += 'Time of the route: {}min\n'.format( assignment.Min(time_var)) print(plan_output) total_time += assignment.Min(time_var) print('Total time of all routes: {}min'.format(total_time))@property def plan_trip(self): """Entry point of the program."""
Instantiate the data problem.
data = self.create_data_model() # Create the routing index manager. manager = pywrapcp.RoutingIndexManager( len(data['time_matrix']), data['num_days'], data['start'], data['end']) # Create Routing Model. routing = pywrapcp.RoutingModel(manager) # Create and register a transit callback. def time_callback(from_index, to_index): """Returns the distance between the two nodes.""" # Convert from routing variable Index to distance matrix NodeIndex. from_node = manager.IndexToNode(from_index) to_node = manager.IndexToNode(to_index) return data['time_matrix'][from_node][to_node] transit_callback_index = routing.RegisterTransitCallback(time_callback) # Define cost of each arc. routing.SetArcCostEvaluatorOfAllVehicles(transit_callback_index) # Add Distance constraint. dimension_name = 'Time' routing.AddDimension( transit_callback_index, 30, # maximum waiting time for a vehicle 30, # vehicle maximum travel time False, # start cumul to zero dimension_name) time_dimension = routing.GetDimensionOrDie(dimension_name) # Add time window constraints for each location except depot. for location_idx, time_window in enumerate(data['time_windows']): if location_idx == 0: continue index = manager.NodeToIndex(location_idx) print(location_idx) print(index) print(time_dimension.CumulVar(index)) time_dimension.CumulVar(index).SetRange(time_window[0], time_window[1]) # Add time window constraints for each vehicle start node. for vehicle_id in range(data['num_days']): index = routing.Start(vehicle_id) time_dimension.CumulVar(index).SetRange(data['time_windows'][0][0], data['time_windows'][0][1]) for i in range(data['num_days']): routing.AddVariableMinimizedByFinalizer( time_dimension.CumulVar(routing.Start(i))) routing.AddVariableMinimizedByFinalizer( time_dimension.CumulVar(routing.End(i))) time_dimension.SetSpanCostCoefficientForAllVehicles(30) # Setting first solution heuristic. search_parameters = pywrapcp.DefaultRoutingSearchParameters() search_parameters.first_solution_strategy = ( routing_enums_pb2.FirstSolutionStrategy.PATH_CHEAPEST_ARC) # Solve the problem. solution = routing.SolveWithParameters(search_parameters) # Print solution on console. if solution: self.print_solutions(data, manager, routing, solution)from travelapp import TripPlanner ob = TripPlanner() ob.plan_trip
` Could someone tell what am i doing wrong. This is my first time using ORtools
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shandilya1998
commented
5 years ago Getting this now-
Traceback (most recent call last): File "/Users/travelapp/PycharmProjects/TravelApp/travelapp.py", line 216, in <module> from travelapp import TripPlanner File "/Users/travelapp/PycharmProjects/TravelApp/travelapp.py", line 218, in <module> ob.plan_trip File "/Users/travelapp/PycharmProjects/TravelApp/travelapp.py", line 189, in plan_trip time_dimension.CumulVar(index).SetRange(time_window[0], time_window[1]) AttributeError: 'NoneType' object has no attribute 'SetRange'
lperron
commented
5 years ago Can you add a time windows on the start ? Not sure. Laurent Perron | Operations Research | lperron@google.com | (33) 1 42 68 53 00
Le sam. 20 juil. 2019 à 10:18, shandilya1998 notifications@github.com a écrit :
abduakhatov
Data-Science-Link
fabian-rudolf
Hello,
Whenever I run my code on a certain dataset I get this error:
Please could someone help identify why this is happening