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```def calculate_interference(routers):
interference = 0.0

for i in range(len(routers)):
for j in range(i + 1, len(routers)):
router1 = routers[i]
router2 = routers[j]

# Calculate the squared Euclidean distance between routers
distance_squared = (router1.x - router2.x)**2 + (router1.y - router2.y)**2

# Calculate the inverse of squared distance as a measure of interference
# Higher values of distance_squared result in lower interference
# Use a constant factor to scale the value as needed
inverse_distance_squared = 1.0 / distance_squared

# Add the interference caused by this router pair to the total
interference += inverse_distance_squared

return interference

def calculate_coverage(routers, clients):
covered_clients = 0
for client in clients:
for router in routers:
distance = ((client.x - router.x)**2 + (client.y - router.y)**2)**0.5
covered_clients += 1
break  # This client is covered, move to the next client
coverage = covered_clients / len(clients)
return coverage

# Calculate the number of clients connected to each router
clients_per_router =  * len(routers)
for client in clients:
min_distance = float('inf')
closest_router_index = -1
for i, router in enumerate(routers):
distance = ((client.x - router.x)**2 + (client.y - router.y)**2)**0.5
if distance <= router.radius and distance < min_distance:
min_distance = distance
closest_router_index = i
if closest_router_index != -1:
clients_per_router[closest_router_index] += 1

# Calculate the standard deviation of clients per router
mean_clients = sum(clients_per_router) / len(clients_per_router)
load_balancing = (sum((x - mean_clients)**2 for x in clients_per_router) / len(clients_per_router))**0.5

def calculate_fitness(routers, clients, weight_interference, weight_coverage, weight_load_balancing):
# Calculate interference based on router locations
interference = calculate_interference(routers)

# Calculate coverage and load balancing (you can implement these)
coverage = calculate_coverage(routers, clients)  