Attempting to run the Genetic Algorithm from mlrose on the Four Peaks problem, but it converges very fast and not sure if this is normal. I've used 7 different seeds and a population size of 600, and 30 iterations for each.

fitness_fn = mlrose.FourPeaks(t_pct=.1) problem = mlrose.DiscreteOpt(length=600, fitness_fn=fitness_fn, maximize=True, max_val=2) mlrose.genetic_alg(problem, pop_size=int(600), mutation_prob=0.4, max_iters=int(max_iter), random_state=seed) 

 1 9.0 10.0 13.0 11.0 13.0 10.0 9.0 2 11.0 12.0 115.0 11.0 13.0 16.0 9.0 3 11.0 16.0 115.0 13.0 17.0 112.0 9.0 4 13.0 16.0 119.0 13.0 17.0 112.0 9.0 5 22.0 24.0 120.0 14.0 17.0 114.0 12.0 6 22.0 24.0 120.0 20.0 17.0 116.0 12.0 7 122.0 24.0 120.0 113.0 17.0 116.0 12.0 8 122.0 24.0 120.0 114.0 17.0 117.0 12.0 9 122.0 24.0 120.0 120.0 19.0 117.0 112.0 10 122.0 112.0 120.0 123.0 19.0 117.0 112.0 11 124.0 116.0 120.0 123.0 20.0 117.0 114.0 12 124.0 121.0 120.0 123.0 20.0 117.0 114.0 13 124.0 121.0 120.0 123.0 20.0 117.0 114.0 14 125.0 121.0 120.0 123.0 20.0 117.0 115.0 15 126.0 121.0 120.0 123.0 20.0 119.0 115.0 16 127.0 121.0 120.0 123.0 21.0 119.0 115.0 17 127.0 121.0 120.0 123.0 21.0 119.0 115.0 18 127.0 121.0 120.0 123.0 21.0 119.0 117.0 19 127.0 121.0 120.0 123.0 21.0 119.0 117.0 20 127.0 121.0 120.0 123.0 114.0 119.0 122.0 21 127.0 121.0 120.0 123.0 117.0 119.0 122.0 22 127.0 121.0 120.0 123.0 119.0 119.0 122.0 23 127.0 121.0 120.0 123.0 120.0 120.0 122.0 24 127.0 121.0 120.0 123.0 121.0 123.0 122.0 25 127.0 121.0 120.0 123.0 121.0 123.0 122.0 26 127.0 121.0 120.0 123.0 121.0 123.0 122.0 27 127.0 121.0 120.0 123.0 121.0 123.0 122.0 28 127.0 121.0 120.0 123.0 122.0 123.0 122.0 29 127.0 121.0 120.0 123.0 123.0 123.0 122.0 30 127.0 121.0 120.0 123.0 123.0 123.0 122.0 

The question is, why is it converging so fast and what can I do to improve?