3 ms·
Simulated Annealing with restarting is a simpler, less finicky and robust one to use in place of GAs. But since the No Free Lunch theorem for optimization says
by Dn_Ab 16y ago
Simulated Annealing with restarting is a simpler, less finicky and robust one to use in place of GAs. But since the No Free Lunch theorem for optimization says that the general applicability of any optimization algorithm is as bad as every other and no better than random search the answer is like anything else. Understand your problem and pick the right tools. You can get an overview of the numerous techniques here. http://en.wikipedia.org/wiki/Category:Optimization_algorithms http://en.wikipedia.org/wiki/Category:Optimization_algorithm...
* Actually its not quite any since it holds not exactly but to a very very good approximation and there are a few, like Coevolutionary approaches which provide a loophole out of that. So that might be something you want to look at.
- yters 16y agoWhat is the loophole that coevolution provides? I didn't realize there was a loophole to NFLT.
- Dn_Ab 16y agoWell the loophole is not really a loophole more like an escape hatch in that NFLT was shown to not be applicable for certain types of coevolutionary algorithms like say pareto coevolution. The way I understand it is that in essence the no free lunch theorem only applies when candidate solutions are not re-evaluated in terms of relative performance. In coevolution we continually pit a population of candidate solutions 'to play' against each other in order to evolve a champion. Since fitness in this case is relative and not absolute - making performance tricky to measure - NFTL can be wiggled out of. as long as you can evaluate/term your problem within game like heuristics. - http://www.no-free-lunch.org/ http://www.no-free-lunch.org/ - http://cs.calstatela.edu/wiki/images/1/15/Wolpert-Coevolution.pdf http://cs.calstatela.edu/wiki/images/1/15/Wolpert-Coevolutio...