|edoc-Server der Humboldt-Universität zu Berlin|
A. B. Philpott, University of Auckland|
Z. Guan, University of Auckland
|Title:||On the convergence of stochastic dual dynamic programming and related methods|
|Date of Acceptance:||06.03.2008|
Stochastic Programming E-Print Series |
|Editors:||Julie L. Higle; Werner Römisch; Surrajeet Sen|
|Complete Preprint:||pdf (urn:nbn:de:kobv:11-10086956)|
|Keywords (eng):||Benders decomposition, multi-stage stochastic programming, Monte-Carlo sampling|
|To appear in:||OR-Letters|
|Metadata export: To export the complete metadata set as Endote or Bibtex format please click to the appropriate link.||Endnote Bibtex|
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|We discuss the almost-sure convergence of a broad class of sampling algorithms for multi-stage 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.|
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