Branch and probability bound methods for global optimization
Volume 1, Issue 1 (1990), pp. 125–140
Pub. online: 1 January 1990
Type: Research Article
Published
1 January 1990
1 January 1990
Abstract
The maximization problem for an objective function f given on a feasible region X is considered, where X is a compact subset of Rn and f belongs to a set of continuous multiextremal functions on X can be evaluated at any point x in X without error, and its maximum M=max x∈Xf(x) together with a maximizer x*(a point x* in X such that M=f(x*)) 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 and bound methods.