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import numpy as np
import time
import threading
# Rastrigin function
def rastrigin_function(x):
A = 10
return A * len(x) + np.sum(x**2 - A * np.cos(2 * np.pi * x))
# Initialize control parameters
SN = 10000 # Number of food sources
MCN = 100000 # Maximum number of cycles
limit = 50 # Maximum number of exploitations for a solution
dimensionality = 2 # Dimensionality of the search space
# Shared variables among threads
food_sources_lock = threading.Lock()
trial_lock = threading.Lock()
cyc_lock = threading.Lock()
start_time_lock = threading.Lock()
food_sources = np.random.uniform(-5.12, 5.12, size=(SN, dimensionality)) # Initial random positions
trial = np.zeros(SN) # Initialize trial counters
cyc = 1 # Initial cycle
start_time = None # Start time
# Function for Employed Bees' Phase
def employed_bees_phase():
global food_sources, trial
for i in range(SN):
# Generate a neighbor solution
x_hat = food_sources[i] + np.random.uniform(-0.5, 0.5, size=(dimensionality,))
# Update solution if it is better
if rastrigin_function(x_hat) < rastrigin_function(food_sources[i]):
with food_sources_lock:
food_sources[i] = x_hat
trial[i] = 0
else:
with trial_lock:
trial[i] += 1
# Function for Onlooker Bees' Phase
def onlooker_bees_phase():
global food_sources, trial
probabilities = 1 / (1 + np.exp(-trial)) # Use trial as a measure of fitness
onlooker_indices = np.random.choice(SN, size=SN, p=probabilities / probabilities.sum())
for i in onlooker_indices:
# Generate a neighbor solution
x_hat = food_sources[i] + np.random.uniform(-0.5, 0.5, size=(dimensionality,))
# Update solution if it is better
if rastrigin_function(x_hat) < rastrigin_function(food_sources[i]):
with food_sources_lock:
food_sources[i] = x_hat
trial[i] = 0
else:
with trial_lock:
trial[i] += 1
# Function for Scout Bee Phase
def scout_bee_phase():
global food_sources, trial
max_trial_index = np.argmax(trial)
if trial[max_trial_index] > limit:
with food_sources_lock:
food_sources[max_trial_index] = np.random.uniform(-5.12, 5.12, size=(dimensionality,))
trial[max_trial_index] = 0
# Record start time
with start_time_lock:
start_time = time.time()
# Thread for Employed Bees' Phase
employed_thread = threading.Thread(target=employed_bees_phase)
# Thread for Onlooker Bees' Phase
onlooker_thread = threading.Thread(target=onlooker_bees_phase)
# Thread for Scout Bee Phase
scout_thread = threading.Thread(target=scout_bee_phase)
# Start all threads
employed_thread.start()
onlooker_thread.start()
scout_thread.start()
# Wait for all threads to finish
employed_thread.join()
onlooker_thread.join()
scout_thread.join()
# Record end time
end_time = time.time()
# Find the best solution
best_solution = food_sources[np.argmin([rastrigin_function(x) for x in food_sources])]
print("Best solution:", best_solution)
print("Objective function value at best solution:", rastrigin_function(best_solution))
print("Time taken:", end_time - start_time, "seconds")
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