On the convergence of stochastic dual dynamic programming and related methods

Authors:
A. B. Philpott;Z. Guan
Affiliations:
Department of Engineering Science, The University of Auckland, Private Bag 92019, Auckland, New Zealand;Department of Engineering Science, The University of Auckland, Private Bag 92019, Auckland, New Zealand
Venue:
Operations Research Letters
Year:
2008

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Abstract

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.