Мобильная версияПодробности:
У меня в экземпляре 30 клиентов, но кажется, что один из них индексы выходят за пределы допустимого диапазона.
Обратная трассировка указывает на то, что ошибка возникает при попытке доступа к маршрутам после минимизации транспортных средств.
Вот фрагмент моей функции _get_start_solution для контекста :
Код: Выделить всё
def _get_start_solution(self, problem):
"""
Generate an initial solution for the problem by assigning requests to vehicles
based on vehicle capacity and customer demands.
Parameters
----------
problem : `Problem`
The optimization problem containing vehicles and requests.
Returns
-------
solution : `Solution`
The initial solution object with routes for all vehicles.
"""
# Initialize the solution object
solution = Solution(problem)
num_customers = len(problem.P) # Number of customers (pickup points)
print(f"Number of customers: {num_customers}")
# Default vehicle capacity, adjust if capacity is stored elsewhere in problem
vehicle_capacity = getattr(problem.vehicles[0], 'capacity', 100) # Get vehicle capacity from the first vehicle
print(f"Vehicle capacity: {vehicle_capacity}")
# Initialize routes and remaining capacities for each vehicle
routes = []
capacities = []
vehicle_id = 0 # Start vehicle IDs from 0
# Create a list of customers (excluding depot which is assumed to be customer 0)
customers = list(range(1, num_customers + 1)) # Only customers, not the depot
print(f"Shuffling customers: {customers}")
random.shuffle(customers)
# Create a new route whenever the vehicle is full
current_route = []
current_capacity = vehicle_capacity
# Iterate over the shuffled customers and assign them to vehicles
for customer_id in customers:
if customer_id not in problem.P:
print(f"Customer {customer_id} not found in problem.P")
continue # Skip this customer if they do not exist
# Get the demand of the customer (assuming demand is stored in 'load')
demand = problem.P[customer_id].load # Adjust if demand attribute is different
print(f"Customer {customer_id} demand: {demand}")
# Check if the current vehicle can accommodate the customer's demand
if current_capacity >= demand:
current_route.append(customer_id)
current_capacity -= demand
# Remove the customer from the request bank as it is now assigned
if customer_id in solution.request_bank:
solution.request_bank.remove(customer_id)
else:
# If the current vehicle is full, finalize the current route and start a new one
if current_route: # Only append if current_route is not empty
route = Route(problem, vehicle_id)
route.route = current_route # Assign the customers to the route
routes.append(route) # Add the completed route to the routes list
# Start a new route with a new vehicle
current_route = [customer_id]
current_capacity = vehicle_capacity - demand
# Remove the customer from the request bank as it is now assigned
if customer_id in solution.request_bank:
solution.request_bank.remove(customer_id)
# Increment vehicle ID for the next route
vehicle_id += 1
# Add the final route (if there are still customers left)
if current_route:
route = Route(problem, vehicle_id)
route.route = current_route # Assign the customers to the route
routes.append(route) # Add the last route to the routes list
# Check if all requests have been assigned to a route
if 0 in solution.request_bank: # Check if depot is in the request bank (shouldn't be)
solution.request_bank.remove(0) # Remove depot if present
if len(solution.request_bank) > 0:
print(f"Remaining in request bank: {solution.request_bank}")
raise IndexError("There are not enough vehicles to assign all requests")
# Filter the routes to include only those that were used
solution.routes = routes # Use the routes list created earlier
print(
f"Final solution: {solution.routes}, "
f"Number of routes: {len(solution.routes)}, "
f"Number of vehicles used: {solution._number_of_used_vehicles()}"
)
# Rebuild insert matrices to reflect the current state of the solution
solution._rebuild_insert_matrices()
return solution
def _rebuild_insert_matrices(self):
"""
(Re)build the insert matrices.
This method (re)builds _delta_f and _best_insert_position.
Matrices needed by the insert heuristics.
"""
# Creating and initializing matrices
self._delta_f = [[float('inf')]*len(self.routes) for x in range(self.problem.n)]
self._best_insert_position = [[-1]*len(self.routes) for x in range(self.problem.n)]
# For each route
for route_id in self.available_vehicles:
self._update_best_insert_route(route_id)
Код: Выделить всё
B-n31-k5
runtime: 831.782910
VEHICLE
NUMBER CAPACITY
100000 100
CUSTOMER
CUST NO. XCOORD. YCOORD. DEMAND
0 17 76 0
1 24 6 25
2 96 29 3
3 14 19 13
4 14 32 17
5 0 34 16
6 16 22 9
7 20 26 22
8 22 28 10
9 17 23 16
10 98 30 8
11 30 8 3
12 23 27 16
13 19 23 16
14 34 7 10
15 31 7 24
16 0 37 16
17 19 23 15
18 0 36 14
19 26 7 5
20 98 32 12
21 5 40 2
22 17 26 18
23 21 26 20
24 28 8 15
25 1 35 8
26 27 28 22
27 99 30 15
28 26 28 10
29 17 29 13
30 20 26 19
Подробнее здесь: https://stackoverflow.com/questions/791 ... -in-vehicl
