There are lots of metaheuristic optimization methods; simulated annealing is the easiest one to explain and implement, but consequently it’s also the dumbest of them.
I’m personally a fan of tabu search, which prevents cycling and getting stuck in local optima by remembering features of previously seen solutions, and not visiting any solution with those features for some set length of time. “Best” depends on the particular problem, though; there are situations when the easy implementation of simulated annealing makes it a superior solution to a cleverer but longer implementation of something else.
There are lots of metaheuristic optimization methods; simulated annealing is the easiest one to explain and implement, but consequently it’s also the dumbest of them.
What are the best ones?
I’m personally a fan of tabu search, which prevents cycling and getting stuck in local optima by remembering features of previously seen solutions, and not visiting any solution with those features for some set length of time. “Best” depends on the particular problem, though; there are situations when the easy implementation of simulated annealing makes it a superior solution to a cleverer but longer implementation of something else.