def run(n):
current_node = Individual(n)
while current_node.fitness() > 0:
neighbours = current_node.get_neighbours()
neighbours.sort(key=lambda b: b.fitness())
best_neighbour = neighbours[0]
if best_neighbour.fitness() < current_node.fitness():
current_node = copy.deepcopy(best_neighbour)
else:
return current_node, current_node.fitness()
return current_node, current_node.fitness()
def run(self):
current_node = Individual(self.__n)
while current_node.fitness() > 0:
neighbours = current_node.get_neighbours()
neighbours.sort(key=lambda b: b.fitness())
best_neighbour = neighbours[0]
if best_neighbour.fitness() < current_node.fitness():
current_node = copy.deepcopy(best_neighbour)
else:
self.signal.emit(
[current_node,
current_node.fitness(), 'done'])
return
self.signal.emit([current_node, current_node.fitness(), 'done'])