我正在研究车辆路径问题的实现，在执行 _get_start_solution 函数时遇到 IndexError。错误发生在解决方案的最终打印语句期间。
详情：
'Traceback (most recent call last):
File "C:\Users\hajar\Desktop\lns_v_test_epsilon\lns\test_alpha_gamma.py", line 128, in <module>
main()
File "C:\Users\hajar\Desktop\lns_v_test_epsilon\lns\test_alpha_gamma.py", line 124, in main
test(epsilon, gamma, alpha)
File "C:\Users\hajar\Desktop\lns_v_test_epsilon\lns\test_alpha_gamma.py", line 96, in test
solution = alg.solve(problem, start_time,type="eps_greedy", method="TS",eps=epsilon, ensemble=[])
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\hajar\Desktop\lns_v_test_epsilon\lns\algorithm.py", line 704, in solve
start_solution = self._get_start_solution(problem)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "C:\Users\hajar\Desktop\lns_v_test_epsilon\lns\algorithm.py", line 802, in _get_start_solution
f"Final solution: {solution.routes}, "
File "C:\Users\hajar\Desktop\lns_v_test_epsilon\lns\solution.py", line 391, in __repr__
self.earliest[i],
~~~~~~~~~~~~~^^^
IndexError: list index out of range'
我的实例中有 30 个客户，但其中一个指数似乎超出了范围。 回溯表明，在最小化车辆后尝试访问路线时出现错误。
这是我的 _get_start_solution 函数的上下文片段：
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)
我有这个数据：
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
任何人都可以帮助我确定为什么会发生此 IndexError 以及如何确保所有客户端都正确包含在解决方案中？任何有关有效管理路线的指导将不胜感激！
repr的代码：
def __repr__(self):
result = "* Total current cost: %s \n" % self.cost
result += "* (node: [start, departure_load]):\n"
for i in range(len(self.route)):
result += "(%s: [%s, %s]) --> " % (self.route[i],
self.earliest[i],
self.loads[i])
return result
此代码解决了我的问题，无需更改 repr，只需更改 get_start_solution
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}")
vehicle_capacity = getattr(problem.vehicles[0], 'capacity', 100) # Get vehicle capacity from the first vehicle
print(f"Vehicle capacity: {vehicle_capacity}")
routes = []
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)
current_route = []
current_capacity = vehicle_capacity
current_loads = [] # To keep track of the loads in the current route
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
demand = problem.P[customer_id].load # Assuming demand is stored in 'load'
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
current_loads.append(demand) # Track the load for this route
# 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 current_route: # Only append if current_route is not empty
route = Route(problem, vehicle_id)
route.route = current_route
routes.append(route)
# Synchronize earliest, latest, and loads with the route length
route.earliest = [0] * len(current_route) # Assuming default values for earliest
route.latest = [0] * len(current_route) # Assuming default values for latest
route.loads = current_loads # Assign the loads
# Start a new route with a new vehicle
current_route = [customer_id]
current_capacity = vehicle_capacity - demand
current_loads = [demand] # Reset the load for the new route
# 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
routes.append(route)
# Synchronize earliest, latest, and loads with the route length
route.earliest = [0] * len(current_route)
route.latest = [0] * len(current_route)
route.loads = current_loads # Assign the final loads
# 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)
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")
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