def choose_sequence(self):
selected_sequence = TabuSequence()
sequence_decision = []
for i, generated_sequence in enumerate(self.generated_neighbour_list):
if not generated_sequence.values['decision'] == 'tabu':
print('neighbour error', generated_sequence.error)
if generated_sequence.error <= self.best_sequence.error:
self.best_sequence = copy.deepcopy(generated_sequence)
selected_sequence = copy.deepcopy(self.best_sequence)
sequence_decision.append('best sequence')
elif generated_sequence.error < selected_sequence.error:
selected_sequence = copy.deepcopy(generated_sequence)
selected_sequence.values['decision'] = 'selected sequence'
sequence_decision.append('selected sequence')
else:
sequence_decision.append('not_chosen')
else:
sequence_decision.append('tabu')
self.prev_sequence_list.append(selected_sequence)
self.prev_sequence = selected_sequence
self.generated_neighbour_list = []
print('decision', sequence_decision)
return sequence_decision
def next_iteration(self, iteration_number):
print('next iteration')
new_sequence = TabuSequence()
new_sequence.values['iteration number'] = iteration_number
new_sequence.coming_sequence = self.generate_random(self.prev_sequence.coming_sequence)
new_sequence.going_sequence = self.generate_random(self.prev_sequence.going_sequence)
if self.same_generated(new_sequence):
print('same')
self.next_iteration(iteration_number)
else:
print('diff')
self.generated_neighbour_list.append(new_sequence)
return new_sequence