Multiple parameter optimization with lots of local minima

Question

I\'m looking for algorithms to find a \"best\" set of parameter values. The function in question has a lot of local minima and changes very quickly. To make matters even worse,

Answer 1

There is no generalized way to answer your question. There are lots of books/papers on the subject matter, but you'll have to choose your path according to your needs, which are not clearly spoken here.

Some things to know, however - 1min/test is way too much for any algorithm to handle. I guess that in your case, you must really do one of the following:

• get 100 computers to cut your parameter testing time to some reasonable time
• really try to work out your parameters by hand and mind. There must be some redundancy and at least some sanity check so you can test your case in <1min
• for possible result sets, try to figure out some 'operations' that modify it slightly instead of just randomizing it. For example, in TSP some basic operator is lambda, that swaps two nodes and thus creates new route. Your can be shifting some number up/down for some value.
• then, find yourself some nice algorithm, your starting point can be somewhere here. The book is invaluable resource for anyone who starts with problem-solving.