def notify(self, algorithm):
if algorithm.n_gen % 10 == 0:
fig, ax = plt.subplots()
x = algorithm.opt[0].get("X")
visualize(problem, x, fig=fig, ax=ax, show=False)
ax.set_title(f"Generation: {algorithm.n_gen}")
self.video.record(fig=fig)
def notify(self, algorithm):
if algorithm.n_gen % 10 == 0:
x = algorithm.opt[0].get("X")
visualize(problem, x, show=False)
plt.title(f"Generation: {algorithm.n_gen}")
self.vid.record()
sampling=RandomPermutationSampling(),
mutation=InversionMutation(),
# crossover=EdgeRecombinationCrossover(),
crossover=OrderCrossover(),
repair=StartFromZeroRepair(),
eliminate_duplicates=True)
# if the algorithm did not improve the last 200 generations then it will terminate (and disable the max generations)
termination = SingleObjectiveDefaultTermination(n_last=200, n_max_gen=np.inf)
res = minimize(problem, algorithm, termination, seed=1, verbose=False)
print(res.F)
print(res.algorithm.evaluator.n_eval)
visualize(problem, res.X)
class PathVisualization(Callback):
def __init__(self):
super().__init__()
self.vid = Video(File("tsp.mp4"))
def notify(self, algorithm):
if algorithm.n_gen % 10 == 0:
x = algorithm.opt[0].get("X")
visualize(problem, x, show=False)
plt.title(f"Generation: {algorithm.n_gen}")
self.vid.record()