Branch and probability bound methods for global optimization
Anatoly A. Zhigljavsky · 1990
The maximization problem for an objective func tion f given on a feasible region X is considered, where X is a compact subset of Rn and f belongs t.o a set. of cont.inuous mul tiextremal functions on X can be evaluated at any point x in X without error, and its maximum M = maxf(;r) together with a rEX maximizer .r*(a point x* in X such that AI = f(;r*)) are to be approximated. We consider a class of the global random search methods, underlying an apparatus of the mathematical statistics and generalizing the so-called branch a,nd bound methods.