def ga_p(city_list):
cfg = GACfg(gene_len=25,
gene_size=25,
pop_size=1000,
elite_size=50,
tournament_num=50,
tournament_size=100,
mutation_rate=0.03,
repeatable=False)
ga = GA(fitness_func, cfg)
ga.prepare_kwargs(city_list=city_list)
ga.init_population()
progress = []
progress.append(1 / ga.cal_fitness()[0][1])
for _ in range(100):
early_stop = ga.evolve()
progress.append(1 / ga.cal_fitness()[0][1])
if early_stop:
break
print("Final distance: " + str(1 / ga.cal_fitness()[0][1]))
plt.plot(progress)
plt.ylabel('Distance')
plt.xlabel('Generation')
plt.show()
