relation: https://pure.iiasa.ac.at/id/eprint/4962/ title: A Branch and Bound Method for Stochastic Global Optimization creator: Norkin, V.I. creator: Pflug, G.C. creator: Ruszczynski, A. description: A stochastic version of the branch and bound method is proposed for solving stochastic global optimization problems. The method, instead of deterministic bounds, uses stochastic upper and lower estimates of the optimal value of subproblems, to guide the partitioning process. Almost sure convergence of the method is proved and random accuracy estimates derived. Methods for constructing random bounds for stochastic global optimization problems are discussed. The theoretical considerations are illustrated with an example of a facility location problem. publisher: WP-96-065 date: 1996-06 type: Monograph type: NonPeerReviewed format: text language: en identifier: https://pure.iiasa.ac.at/id/eprint/4962/1/WP-96-065.pdf identifier: Norkin, V.I. , Pflug, G.C. ORCID: https://orcid.org/0000-0001-8215-3550 , & Ruszczynski, A. (1996). A Branch and Bound Method for Stochastic Global Optimization. IIASA Working Paper. IIASA, Laxenburg, Austria: WP-96-065