Cp. Stephens et W. Baritompa, GLOBAL OPTIMIZATION REQUIRES GLOBAL INFORMATION, Journal of optimization theory and applications, 96(3), 1998, pp. 575-588
Citations number
20
Categorie Soggetti
Operatione Research & Management Science",Mathematics,"Operatione Research & Management Science
There are many global optimization algorithms which do not use global
information. We broaden previous results, showing limitations on such
algorithms, even if allowed to run forever. We show that deterministic
algorithms must sample a dense set to find the global optimum value a
nd can never be guaranteed to converge only to global optimizers. Furt
her, analogous results show that introducing a stochastic element does
not overcome these limitations. An example is simulated annealing in
practice. Our results show that there are functions for which the prob
ability of success is arbitrarily small.