On the Convergence of Sampling-Based Decomposition Algorithms for Multistage Stochastic Programs
Journal
Journal of Optimization Theory and Applications
ISSN
0022-3239
ISSN-Digital
1573-2878
Type
journal article
Date Issued
2005-05-01
Author(s)
Linowsky, Karsten
;
Philpott, Andrew B.
Abstract
The paper presents a convergence proof for a broad class of sampling algorithms for multistage stochastic linear programs in which the uncertain parameters occur only in the constraint right-hand sides. This class includes SDDP, AND, ReSa, and CUPPS. We show that, under some independence assumptions on the sampling procedure, the algorithms converge with probability 1.
Language
English
HSG Classification
contribution to scientific community
Refereed
Yes
Publisher
Springer Science + Business Media
Publisher place
Dordrecht
Volume
125
Number
2
Start page
349
End page
366
Pages
18
Subject(s)
Division(s)
Eprints ID
44948