170 eng Norkin, Vladimir I. A branch and bound method for stochastic global optimization A stochastic branch and bound method for solving stochastic global optimization problems is proposed. As in the deterministic case, the feasible set is partitioned into compact subsets. To guide the partitioning process the method uses stochastic upper and lower estimates of the optimal value of the objective function in each subset. Convergence of the method is proved and random accuracy estimates derived. Methods for constructing stochastic upper and lower bounds are discussed. The theoretical considerations are illustrated with an example of a facility location problem.. Article de fons. Stochastic programming Global optimization Branch and bound method Facility location Article Pflug, Georg Ch. Ruszczynski, Andrzej Elsevier vol. 83 n. 3 (1998) p. 425-450 83:3<425 Mathematical Programming 0025-5610 00255610v83n3p425 425 450 11 3 83 00255610v83n3 1998 ARTPUB info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://ddd.uab.cat/uab/matpro/00255610v83n3p425.pdf 26 892680