Assume that I want to find the global minimum of a non-linear, non-convex, multidimensional function subject to several restrictions.
Could you recommend me any deterministic strategy which can generally find an acceptable solution in a reasonable time-frame (say less than 1 hour)? Or should I go with the heuristic / stochastic route?
Ok, I will slightly rephrase the question:
If you had to find the global optimum of a multidimensional non-convex function, are there any type of problem/structure where deterministic strategies will be preferred to other stochastic/heuristic methods like simulated annealing or a genetic algorithm.