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Mizux/cvrptw_pd.py

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CVRPTW_PD
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cvrptw_pd.py
#!/usr/bin/env python3
"""Development In Progress
CVRPTW.
or-tools == 9.9.3963
python == 3.11.7
Number of Regular Nodes = 16,
Depot Nodes = 1
Number of Nodes Duplicated = 16(Same as Number of Regular Nodes)
Total Nodes = 16+16+1 = 33
Demnds = 0 for Depot, 1 for Regular Nodes and -1 for Duplicate Nodes.
Time Windwos = Applied Business Logic for Regular Nodes and Whole Day for Duplicate Nodes.
pickup_dropoff = Regular Node Index, len(data)+Regular Node Index
"""
import numpy as np
from ortools.routing import enums_pb2
from ortools.routing import pywraprouting
FirstSolutionStrategy = enums_pb2.FirstSolutionStrategy
LocalSearchMetaheuristic = enums_pb2.LocalSearchMetaheuristic
RoutingSearchStatus = enums_pb2.RoutingSearchStatus
def create_data_model():
data = {}
num_depots = 1
patient_len = 16
vehicle_capacity = 3
data["num_Locations"] = 2 * patient_len + num_depots
# fmt:off
# data['demands'] = [0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3, -3]
# for the Demands Tried adding Vehicle_Capacity(-3) instead of -1, Vehicle Didnt Visit Any Nodes. But adding -1 yielded result
data['demands']=[0, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1, -1]
data['time_windows']=[(0, 86400), (23400, 25200), (23400, 25200), (23400, 25200), (23400, 25200), (23400, 25200), (28800, 28800), (28800, 28800), (32400, 32400), (32400, 32400), (36000, 36000), (36000, 36000), (36000, 36000), (39600, 39600), (39600, 39600), (43200, 43200), (43200, 43200), (0, 86400), (0, 86400), (0, 86400), (0, 86400), (0, 86400), (0, 86400), (0, 86400), (0, 86400), (0, 86400), (0, 86400), (0, 86400), (0, 86400), (0, 86400), (0, 86400), (0, 86400), (0, 86400)]
data['num_vehicles']= 40
data['vehicle_capacity'] = [vehicle_capacity for _ in range(data['num_vehicles'])]
data['depot']=0
data['pickup_dropoff']=[(1, 17), (2, 18), (3, 19), (4, 20), (5, 21), (6, 22), (7, 23), (8, 24), (9, 25), (10, 26), (11, 27), (12, 28), (13, 29), (14, 30), (15, 31), (16, 32)]
data['duplicate_nodes']=patient_len+1 # INdex of Start of Duplicate Node
data['distance_matrix'] = [
[ 0 ,18432 , 8219 , 7741 ,21036 ,11099 ,28697 ,21912 ,31279 ,39777 ,35803 , 8667 ,71688 ,12592 ,11929 ,21985 ,18432 ],
[17866 , 0 ,10701 ,16151 ,21228 ,29756 ,25445 ,22105 ,31472 ,36525 ,48423 ,10499 ,68436 ,14823 ,14225 ,12439 , 0 ],
[ 8084 ,10986 , 0 , 6369 ,13032 ,19974 ,21474 ,13909 ,23623 ,32555 ,38641 , 1221 ,64465 , 4799 , 4140 ,14762 ,10986 ],
[ 7268 ,16304 , 6090 , 0 ,18907 ,19158 ,26568 ,19783 ,31148 ,37649 ,32296 , 6538 ,69559 ,10463 , 9800 ,19856 ,16304 ],
[19622 ,21970 ,12496 ,17908 , 0 ,31512 ,13404 , 4291 ,13905 ,26053 ,37574 ,11758 ,56084 , 8945 , 9289 ,18362 ,21970 ],
[11208 ,30040 ,19827 ,19349 ,32644 , 0 ,40305 ,33520 ,42887 ,51385 ,47721 ,20275 ,83296 ,24200 ,23536 ,33593 ,30040 ],
[28383 ,26104 ,21364 ,26669 ,15291 ,40273 , 0 ,13247 ,15930 ,14162 ,46324 ,20465 ,46072 ,21785 ,22129 ,15111 ,26104 ],
[20790 ,23138 ,13664 ,19075 , 4208 ,32680 ,11417 , 0 ,10501 ,24831 ,37917 ,12926 ,54862 ,10113 ,10457 ,20970 ,23138 ],
[31108 ,33154 ,23981 ,29142 ,14263 ,42997 ,17630 ,11016 , 0 ,24328 ,31712 ,23243 ,50310 ,19040 ,19699 ,28100 ,33154 ],
[39053 ,36774 ,32034 ,37339 ,26278 ,50943 ,12623 ,24234 ,25334 , 0 ,69610 ,31135 ,32389 ,36012 ,35353 ,25781 ,36774 ],
[37147 ,49357 ,39144 ,31154 ,39309 ,45936 ,47054 ,38162 ,32604 ,57812 , 0 ,39592 ,87181 ,43516 ,42853 ,52910 ,49357 ],
[ 8344 ,10812 , 1179 , 6629 ,12035 ,20234 ,20257 ,12911 ,22229 ,31337 ,38901 , 0 ,63248 , 5003 , 4344 ,13545 ,10812 ],
[70605 ,68325 ,63585 ,68890 ,54839 ,82495 ,43646 ,52795 ,49929 ,26387 ,80816 ,62687 , 0 ,61333 ,61677 ,57333 ,68325 ],
[12370 ,14944 , 4734 ,10655 , 8988 ,24259 ,24531 , 9864 ,18076 ,35611 ,42926 , 4653 ,62123 , 0 , 658 ,17819 ,14944 ],
[11711 ,14285 , 4075 , 9996 , 9332 ,23600 ,23872 ,10208 ,18734 ,34952 ,42267 , 3994 ,62467 , 658 , 0 ,17160 ,14285 ],
[21792 ,12856 ,14773 ,20077 ,19004 ,33682 ,15385 ,19880 ,26223 ,26465 ,52349 ,13874 ,58376 ,18750 ,18091 , 0 ,12856 ],
[17866 , 0 ,10701 ,16151 ,21228 ,29756 ,25445 ,22105 ,31472 ,36525 ,48423 ,10499 ,68436 ,14823 ,14225 ,12439 , 0 ],
]
data['duration_matrix']=[
[ 0 , 1468 , 564 , 528 , 1535 , 864 , 1797 , 1630 , 2442 , 2552 , 1737 , 614 , 3806 , 916 , 870 , 1501 , 1468 ],
[1391 , 0 , 939 , 1229 , 1685 , 2157 , 1949 , 1781 , 2592 , 2704 , 2610 , 921 , 3958 , 1194 , 1167 , 1167 , 0 ],
[ 612 , 1026 , 0 , 450 , 1165 , 1378 , 1475 , 1260 , 2017 , 2230 , 1832 , 173 , 3485 , 445 , 388 , 1180 , 1026 ],
[ 515 , 1306 , 402 , 0 , 1373 , 1282 , 1635 , 1468 , 2238 , 2390 , 1506 , 452 , 3644 , 755 , 708 , 1339 , 1306 ],
[1488 , 1699 , 1077 , 1327 , 0 , 2255 , 1216 , 450 , 1297 , 1998 , 2616 , 968 , 2941 , 895 , 929 , 1470 , 1699 ],
[ 801 , 2204 , 1301 , 1265 , 2272 , 0 , 2533 , 2367 , 3178 , 3288 , 2511 , 1351 , 4542 , 1653 , 1607 , 2238 , 2204 ],
[1805 , 1968 , 1438 , 1644 , 1069 , 2572 , 0 , 958 , 1318 , 1113 , 2858 , 1318 , 2368 , 1572 , 1607 , 1051 , 1968 ],
[1620 , 1831 , 1208 , 1458 , 445 , 2386 , 1062 , 0 , 1060 , 1879 , 2512 , 1100 , 2821 , 1026 , 1061 , 1557 , 1831 ],
[2427 , 2680 , 2015 , 2189 , 1345 , 3194 , 1433 , 1097 , 0 , 2052 , 2065 , 1907 , 2937 , 1802 , 1860 , 2218 , 2680 ],
[2549 , 2712 , 2182 , 2387 , 1980 , 3315 , 1130 , 1869 , 1986 , 0 , 3769 , 2062 , 1751 , 2421 , 2363 , 1794 , 2712 ],
[1906 , 2784 , 1880 , 1494 , 2655 , 2516 , 3025 , 2534 , 2047 , 3862 , 0 , 1930 , 4808 , 2233 , 2186 , 2817 , 2784 ],
[ 617 , 989 , 165 , 456 , 1059 , 1384 , 1308 , 1154 , 1937 , 2063 , 1837 , 0 , 3317 , 451 , 393 , 1012 , 989 ],
[3862 , 4024 , 3495 , 3700 , 2895 , 4628 , 2432 , 2784 , 2858 , 1643 , 4725 , 3375 , 0 , 3397 , 3432 , 3107 , 4024 ],
[ 913 , 1297 , 428 , 751 , 922 , 1679 , 1684 , 1017 , 1752 , 2439 , 2132 , 431 , 3435 , 0 , 57 , 1388 , 1297 ],
[ 855 , 1240 , 371 , 693 , 957 , 1622 , 1626 , 1052 , 1810 , 2381 , 2075 , 374 , 3470 , 57 , 0 , 1331 , 1240 ],
[1488 , 1267 , 1120 , 1326 , 1529 , 2254 , 1121 , 1624 , 2266 , 1876 , 2707 , 1000 , 3130 , 1360 , 1302 , 0 , 1267 ],
[1391 , 0 , 939 , 1229 , 1685 , 2157 , 1949 , 1781 , 2592 , 2704 , 2610 , 921 , 3958 , 1194 , 1167 , 1167 , 0 ],
]
# fmt:off
assert data['num_Locations']==len(data['time_windows'])
assert len(data['distance_matrix'])*2-1 == data['num_Locations']
assert len(data['duration_matrix'])*2-1 == data['num_Locations']
assert data['num_Locations']==len(data['demands'])
return data
def print_solution(manager, routing, solution):
"""Prints solution on console."""
status = routing.status()
print(f"Status: {RoutingSearchStatus.Value.Name(status)}")
if (
status != RoutingSearchStatus.ROUTING_OPTIMAL
and status != RoutingSearchStatus.ROUTING_SUCCESS
):
print("No solution found!")
return
print(f"Objective: {solution.ObjectiveValue()}")
# Display dropped nodes.
dropped_nodes = "Dropped nodes:"
for node in range(routing.Size()):
if routing.IsStart(node) or routing.IsEnd(node):
continue
if solution.Value(routing.NextVar(node)) == node:
dropped_nodes += f" {manager.IndexToNode(node)}"
print(dropped_nodes)
# Display routes.
time_dimension = routing.GetDimensionOrDie("Time")
capacity_dimension = routing.GetDimensionOrDie("Capacity")
total_distance = 0
total_time = 0
total_load = 0
for vehicle_id in range(manager.GetNumberOfVehicles()):
nodes_visited = [] # To Keep Track of Node Visited by Vehicle
index = routing.Start(vehicle_id)
plan_output = f"Route for vehicle {vehicle_id}:\n"
route_distance = 0
nodes_visited.append(manager.IndexToNode(index))
while not routing.IsEnd(index):
time_var = time_dimension.CumulVar(index)
capacity_var = capacity_dimension.CumulVar(index)
plan_output += (
f"Node_{manager.IndexToNode(index)}"
f" {route_distance}m"
f" TW:[{time_var.Min()},{time_var.Max()}]"
f" Time({solution.Min(time_var)},{solution.Max(time_var)})"
f" Load({solution.Value(capacity_var)}/{capacity_var.Max()})"
" -> "
)
previous_index = index
index = solution.Value(routing.NextVar(index))
nodes_visited.append(manager.IndexToNode(index))
route_distance += routing.GetArcCostForVehicle(
previous_index, index, vehicle_id
)
if len(nodes_visited) > 2: # Condition does not prints vehicels that are not assigned
time_var = time_dimension.CumulVar(index)
capacity_var = capacity_dimension.CumulVar(index)
plan_output += (
f"Node_{manager.IndexToNode(index)}"
f" {route_distance}m"
f" Time({solution.Min(time_var)},{solution.Max(time_var)})"
f" Load({solution.Value(capacity_var)}/{capacity_var.Max()})"
"\n"
)
plan_output += f"Distance of the route: {route_distance}m\n"
plan_output += f"Time of the route: {solution.Min(time_var)}min\n"
plan_output += f"Load of the route: {solution.Value(capacity_var)}\n"
print(plan_output)
total_distance += route_distance
total_time += solution.Min(time_var)
total_load += solution.Value(capacity_var)
print(nodes_visited)
print(f"Total distance of all routes: {total_distance}m")
print(f"Total time of all routes: {total_time}min")
print(f"Total load of all routes: {total_load}")
# print(f"Total Distance of all routes: {total_distance}m")
def main():
data = create_data_model()
manager = pywraprouting.RoutingIndexManager(
data["num_Locations"], data["num_vehicles"], data["depot"]
)
routing = pywraprouting.RoutingModel(manager)
def distance_callback(from_index, to_index):
from_node = manager.IndexToNode(from_index)
to_node = manager.IndexToNode(to_index)
if from_node in range(data["duplicate_nodes"], data["num_Locations"]):
from_node = 0
if to_node in range(data["duplicate_nodes"], data["num_Locations"]):
to_node = 0
return data["distance_matrix"][from_node][to_node]
data_callback_index = routing.RegisterTransitCallback(distance_callback)
routing.SetArcCostEvaluatorOfAllVehicles(data_callback_index)
def demand_callback(from_index):
from_node = manager.IndexToNode(from_index)
return data["demands"][from_node]
demand_callback_index = routing.RegisterUnaryTransitCallback(demand_callback)
capacity = "Capacity"
routing.AddDimensionWithVehicleCapacity(
demand_callback_index, 0, data["vehicle_capacity"], True, capacity
)
capacity_dimension = routing.GetDimensionOrDie(capacity)
def time_callback(from_index, to_index):
from_node = manager.IndexToNode(from_index)
to_node = manager.IndexToNode(to_index)
if from_node in range(data["duplicate_nodes"], data["num_Locations"]):
from_node = 0
if to_node in range(data["duplicate_nodes"], data["num_Locations"]):
to_node = 0
return data["duration_matrix"][from_node][to_node]
time_callback_index = routing.RegisterTransitCallback(time_callback)
time_dim = "Time"
routing.AddDimension(
time_callback_index,
300_000,
100_000_000_000, # Some Big Number so that Model should not limit itself.
False,
time_dim,
)
time_dimension = routing.GetDimensionOrDie(time_dim)
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(time_window[0], time_window[1])
routing.AddToAssignment(time_dimension.SlackVar(index))
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]
)
routing.AddToAssignment(time_dimension.SlackVar(index))
for i in range(data["num_vehicles"]):
routing.AddVariableMinimizedByFinalizer(
time_dimension.CumulVar(routing.Start(i))
)
routing.AddVariableMinimizedByFinalizer(time_dimension.CumulVar(routing.End(i)))
for request in data["pickup_dropoff"]:
pickup_index = manager.NodeToIndex(request[0])
delivery_index = manager.NodeToIndex(request[1])
routing.solver().Add(
routing.VehicleVar(pickup_index) == routing.VehicleVar(delivery_index)
)
routing.solver().Add(
time_dimension.CumulVar(pickup_index)
<= time_dimension.CumulVar(delivery_index)
)
# Not Sure about whether this is right or wrong. Added Here Baesd Upon the issue #685
min_dur = time_callback(pickup_index, delivery_index)
max_dur = int(1.3 * min_dur)
dur_expr = time_dimension.CumulVar(delivery_index) - time_dimension.CumulVar(
index
)
routing.solver().Add(dur_expr <= max_dur)
# Consraint End-----------
routing.AddPickupAndDelivery(pickup_index, delivery_index)
routing.AddDisjunction([pickup_index, delivery_index], 20_000, 2)
search_parameters = pywraprouting.DefaultRoutingSearchParameters()
search_parameters.first_solution_strategy = (
FirstSolutionStrategy.PARALLEL_CHEAPEST_INSERTION
)
search_parameters.local_search_metaheuristic = (
LocalSearchMetaheuristic.GUIDED_LOCAL_SEARCH
)
search_parameters.time_limit.FromSeconds(3)
# search_parameters.log_search = True
solution = routing.SolveWithParameters(search_parameters)
print_solution(manager, routing, solution)
if __name__ == "__main__":
main()
Raw
diff.md 
%diff -u --color main.py cvrptw_pd.py
--- main.py	2024-07-04 16:11:07.524848863 +0200
+++ cvrptw_pd.py	2024-07-04 16:10:16.518365568 +0200
@@ -17,8 +17,12 @@
 """
 
 import numpy as np
-from ortools.constraint_solver import routing_enums_pb2
-from ortools.constraint_solver import pywrapcp
+from ortools.routing import enums_pb2
+from ortools.routing import pywraprouting
+
+FirstSolutionStrategy = enums_pb2.FirstSolutionStrategy
+LocalSearchMetaheuristic = enums_pb2.LocalSearchMetaheuristic
+RoutingSearchStatus = enums_pb2.RoutingSearchStatus
 
 
 def create_data_model():
@@ -86,47 +90,89 @@
     return data
 
 
-def print_solution(data, manager, routing, solution):
+def print_solution(manager, routing, solution):
     """Prints solution on console."""
+    status = routing.status()
+    print(f"Status: {RoutingSearchStatus.Value.Name(status)}")
+    if (
+        status != RoutingSearchStatus.ROUTING_OPTIMAL
+        and status != RoutingSearchStatus.ROUTING_SUCCESS
+    ):
+        print("No solution found!")
+        return
     print(f"Objective: {solution.ObjectiveValue()}")
+    # Display dropped nodes.
+    dropped_nodes = "Dropped nodes:"
+    for node in range(routing.Size()):
+        if routing.IsStart(node) or routing.IsEnd(node):
+            continue
+        if solution.Value(routing.NextVar(node)) == node:
+            dropped_nodes += f" {manager.IndexToNode(node)}"
+    print(dropped_nodes)
+    # Display routes.
+    time_dimension = routing.GetDimensionOrDie("Time")
+    capacity_dimension = routing.GetDimensionOrDie("Capacity")
     total_distance = 0
-    for vehicle_id in range(data["num_vehicles"]):
-        nodes_visited = []  # To Keep Track of Vehicles Visited by Vehicle
+    total_time = 0
+    total_load = 0
+    for vehicle_id in range(manager.GetNumberOfVehicles()):
+        nodes_visited = []  # To Keep Track of Node Visited by Vehicle
         index = routing.Start(vehicle_id)
         plan_output = f"Route for vehicle {vehicle_id}:\n"
         route_distance = 0
         nodes_visited.append(manager.IndexToNode(index))
         while not routing.IsEnd(index):
-            node = manager.IndexToNode(index)
-            plan_output += f" {node} -> "
+            time_var = time_dimension.CumulVar(index)
+            capacity_var = capacity_dimension.CumulVar(index)
+            plan_output += (
+                f"Node_{manager.IndexToNode(index)}"
+                f" {route_distance}m"
+                f" TW:[{time_var.Min()},{time_var.Max()}]"
+                f" Time({solution.Min(time_var)},{solution.Max(time_var)})"
+                f" Load({solution.Value(capacity_var)}/{capacity_var.Max()})"
+                " -> "
+            )
             previous_index = index
             index = solution.Value(routing.NextVar(index))
             nodes_visited.append(manager.IndexToNode(index))
             route_distance += routing.GetArcCostForVehicle(
                 previous_index, index, vehicle_id
             )
-        if (
-            len(nodes_visited) > 2
-        ):  # Condition does not prints vehicels that are not assigned
-            plan_output += f"{manager.IndexToNode(index)}\n"
+        if len(nodes_visited) > 2:  # Condition does not prints vehicels that are not assigned
+            time_var = time_dimension.CumulVar(index)
+            capacity_var = capacity_dimension.CumulVar(index)
+            plan_output += (
+                f"Node_{manager.IndexToNode(index)}"
+                f" {route_distance}m"
+                f" Time({solution.Min(time_var)},{solution.Max(time_var)})"
+                f" Load({solution.Value(capacity_var)}/{capacity_var.Max()})"
+                "\n"
+            )
             plan_output += f"Distance of the route: {route_distance}m\n"
+            plan_output += f"Time of the route: {solution.Min(time_var)}min\n"
+            plan_output += f"Load of the route: {solution.Value(capacity_var)}\n"
             print(plan_output)
             total_distance += route_distance
+            total_time += solution.Min(time_var)
+            total_load += solution.Value(capacity_var)
             print(nodes_visited)
+    print(f"Total distance of all routes: {total_distance}m")
+    print(f"Total time of all routes: {total_time}min")
+    print(f"Total load of all routes: {total_load}")
     # print(f"Total Distance of all routes: {total_distance}m")
 
 
 def main():
     data = create_data_model()
-    manager = pywrapcp.RoutingIndexManager(
+    manager = pywraprouting.RoutingIndexManager(
         data["num_Locations"], data["num_vehicles"], data["depot"]
     )
 
-    routing = pywrapcp.RoutingModel(manager)
+    routing = pywraprouting.RoutingModel(manager)
 
     def distance_callback(from_index, to_index):
         from_node = manager.IndexToNode(from_index)
-        to_node = manager.IndexToNode(to_node)
+        to_node = manager.IndexToNode(to_index)
         if from_node in range(data["duplicate_nodes"], data["num_Locations"]):
             from_node = 0
         if to_node in range(data["duplicate_nodes"], data["num_Locations"]):
@@ -148,9 +194,6 @@
     )
     capacity_dimension = routing.GetDimensionOrDie(capacity)
 
-    for node in range(data["num_Locations"]):
-        routing.AddDisjunction([manager.NodeToIndex(node)], 100)
-
     def time_callback(from_index, to_index):
         from_node = manager.IndexToNode(from_index)
         to_node = manager.IndexToNode(to_index)
@@ -165,8 +208,8 @@
     time_dim = "Time"
     routing.AddDimension(
         time_callback_index,
-        300,
-        100000000000,  # Some Big Number so that Model should not limit itself.
+        300_000,
+        100_000_000_000,  # Some Big Number so that Model should not limit itself.
         False,
         time_dim,
     )
@@ -214,24 +257,20 @@
         # Consraint End-----------
 
         routing.AddPickupAndDelivery(pickup_index, delivery_index)
-        search_parameters = pywrapcp.DefaultRoutingSearchParameters()
+        routing.AddDisjunction([pickup_index, delivery_index], 20_000, 2)
+
+    search_parameters = pywraprouting.DefaultRoutingSearchParameters()
     search_parameters.first_solution_strategy = (
-        routing_enums_pb2.FirstSolutionStrategy.PARALLEL_CHEAPEST_INSERTION
+        FirstSolutionStrategy.PARALLEL_CHEAPEST_INSERTION
     )
     search_parameters.local_search_metaheuristic = (
-        routing_enums_pb2.LocalSearchMetaheuristic.GUIDED_LOCAL_SEARCH
+        LocalSearchMetaheuristic.GUIDED_LOCAL_SEARCH
     )
-    search_parameters.time_limit.seconds = 30
+    search_parameters.time_limit.FromSeconds(3)
     # search_parameters.log_search = True
 
     solution = routing.SolveWithParameters(search_parameters)
-
-    if solution:
-        print("Solution Found")
-        print_solution(data, manager, routing, solution)
-
-    else:
-        print("NO SOLUTION")
+    print_solution(manager, routing, solution)
 
 
 if __name__ == "__main__":
Raw
output.md 
python /tmp/cvrptw_pd.py
Status: ROUTING_SUCCESS
Objective: 268314
Dropped nodes: 1 5 6 8 9 10 12 15 16 17 21 22 24 25 26 28 31 32
Route for vehicle 0:
Node_0 0m TW:[0,86400] Time(0,0) Load(0/0) -> Node_3 7741m TW:[23400,25200] Time(23400,24121) Load(0/3) -> Node_19 15009m TW:[0,86400] Time(23915,24636) Load(1/3) -> Node_2 23228m TW:[23400,25200] Time(24479,25200) Load(0/3) -> Node_11 24449m TW:[36000,36000] Time(36000,36000) Load(1/3) -> Node_14 28793m TW:[39600,39600] Time(39600,39600) Load(2/3) -> Node_18 40504m TW:[0,86400] Time(40455,40455) Load(3/3) -> Node_27 40504m TW:[0,86400] Time(40455,40455) Load(2/3) -> Node_30 40504m TW:[0,86400] Time(40455,40455) Load(1/3) -> Node_0 40504m Time(40455,40455) Load(0/3)
Distance of the route: 40504m
Time of the route: 40455min
Load of the route: 0

[0, 3, 19, 2, 11, 14, 18, 27, 30, 0]
Route for vehicle 3:
Node_0 0m TW:[0,86400] Time(0,0) Load(0/0) -> Node_4 21036m TW:[23400,25200] Time(23400,25200) Load(0/3) -> Node_7 25327m TW:[28800,28800] Time(28800,28800) Load(1/3) -> Node_13 35440m TW:[39600,39600] Time(39600,39600) Load(2/3) -> Node_23 47810m TW:[0,86400] Time(40513,40513) Load(3/3) -> Node_20 47810m TW:[0,86400] Time(40513,40513) Load(2/3) -> Node_29 47810m TW:[0,86400] Time(40513,40513) Load(1/3) -> Node_0 47810m Time(40513,40513) Load(0/3)
Distance of the route: 47810m
Time of the route: 40513min
Load of the route: 0

[0, 4, 7, 13, 23, 20, 29, 0]
Total distance of all routes: 88314m
Total time of all routes: 80968min
Total load of all routes: 0
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