4.2 Article

On the convergence of stochastic dual dynamic programming and related methods

期刊

OPERATIONS RESEARCH LETTERS
卷 36, 期 4, 页码 450-455

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ELSEVIER SCIENCE BV
DOI: 10.1016/j.orl.2008.01.013

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multistage stochastic programming; Monte-Carlo sampling; Benders decomposition

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We discuss the almost-sure convergence of a broad class of sampling algorithms for multistage stochastic linear programs. We provide a convergence proof based on the finiteness of the set of distinct cut coefficients. This differs from existing published proofs in that it does not require a restrictive assumption. (C) 2008 Elsevier B.V. All rights reserved.

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