eng
A branch and bound method for stochastic global optimization
Norkin, Vladimir I.
Pflug, Georg Ch.
Ruszczynski, Andrzej
Article
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
1998
Stochastic programming
Global optimization
Branch and bound method
Facility location
Mathematical Programming ; vol. 83 n. 3 (1998) p. 425-450
http://ddd.uab.cat/record/170
oai:ddd.uab.cat:170
00255610v83n3p425
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..
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