def simulated_annealing(hyper_params : HyperParams, clusters : clt.Clusters) -> (float, float):
current_temp : float = hyper_params.init_temp
init_time : float = time.time()
elapsed_time : float = time.time()
clusters.initialize_state()
smallest : float = clusters.sse
while current_temp > hyper_params.final_temp:
iterations : int = 0
while iterations < hyper_params.num_iter:
# Disturbing the state:
clusters.disturb()
# Comparing the costs of the current state and the disturbed state:
delta : float = clusters.disturbed_sse - clusters.sse
if delta < 0 or random.random() < math.exp(-delta / current_temp):
if clusters.disturbed_sse < smallest:
smallest = clusters.disturbed_sse
clusters.accept_disturbed()
iterations += 1
elapsed_time = time.time()
if elapsed_time - init_time >= 1:
break
# Updating the temperature:
current_temp *= hyper_params.alpha
elapsed_time = time.time()
if elapsed_time - init_time >= 1:
break
return (smallest, elapsed_time - init_time)
def local_search(clusters : clt.Clusters, current_value : float) -> float:
clusters.disturb()
if (clusters.disturbed_sse <= current_value):
return local_search(clusters, clusters.disturbed_sse)
else:
return current_value