# Should you use Genetic algorithm for an extremly large unstructured search space?

My search space is discrete and in the order of $10^{1360}$, with a probably very complex fitness surface. Is it hopeless to attempt to use GA for such a problem? One fitness evaluation could take 1-3 minutes per candidate solution.

• Thanks for the comment. One fitness evaluation is for one solution, not a whole generation. I edited to make it clear. Aug 17 '16 at 17:58
• This question does not contain nearly enough information to be answerable.
– Raphael
Aug 17 '16 at 19:44
• You are saying that computing the fitness function for a single element in a single generation run takes 1-3 minutes? I.e. a single generation takes a few hours? Aug 17 '16 at 20:25
• Not an answer to your question, but I hope still useful. There is a branch of search algorithms based on Bayesian methods. Some of these algorithms are targeted at search problems with long computation time and even may take the time necessary to evaluate a function into account when considering which parts of the space to explore to get best improvements quickly. See e.g. cs.ubc.ca/~hutter/nips2011workshop/papers_and_posters/… Aug 18 '16 at 0:22
• If the search space is truly unstructured then no algorithm will work besides brute force. Aug 18 '16 at 0:36