That's because genetic algorithms and simulated annealing algorithms are really similar. You could imagine a GA as being a multiple simulated annealing algorit

That's because genetic algorithms and simulated annealing algorithms are really similar. You could imagine a GA as being a multiple simulated annealing algorithm in which you occasionally cross pollinated your solutions. Technically, in GA you keep the top solutions and SA you will move to a less optimal solution with some probability. But the mechanics of them are quite similar.