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A Branch and Bound Method for Stochastic Global Optimization

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Author Info
V.I. Norkin
G.C. Pflug
A. Ruszczynski

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Abstract

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.

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Paper provided by International Institute for Applied Systems Analysis in its series Working Papers with number wp96065.

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Date of creation: Jun 1996
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Handle: RePEc:wop:iasawp:wp96065

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Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
  1. labbe, M. & Peeters, D. & Thisse, J.F., 1992. "Location on Networks," Papers 9216, Universite Libre de Bruxelles - C.E.M.E..
    Other versions:
    • LABBE, Martine & PEETERS, Dominique & THISSE, Jacques-Franois, 1993. "Location on Networks," CORE Discussion Papers 1993040, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    • Labbe, M. & Peeters, D. & Thisse, J.F., 1992. "Location on Networks," Papers 9255-a, Erasmus University of Rotterdam - Econometric Institute.
  2. V.I. Norkin & Y.M. Ermoliev & A. Ruszczynski, 1994. "On Optimal Allocation of Indivisibles Under Uncertainty," Working Papers wp94021, International Institute for Applied Systems Analysis. [Downloadable!]
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  1. Y.M. Ermoliev & V.I. Norkin, 1998. "Monte Carlo Optimization and Path Dependent Nonstationary Laws of Large Numbers," Working Papers ir98009, International Institute for Applied Systems Analysis. [Downloadable!]
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