On the Convergence of Sampling-Based Decomposition Algorithms for Multistage Stochastic Programs

K. Linowsky and A. B. Philpott
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K. Linowsky: University of St. Gallen
A. B. Philpott: University of Auckland

Journal of Optimization Theory and Applications, 2005, vol. 125, issue 2, No 6, 349-366

Abstract: 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.

Keywords: Multistage stochastic programming; sampling; almost sure convergence (search for similar items in EconPapers)
Date: 2005
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Citations: View citations in EconPapers (11)

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DOI: 10.1007/s10957-004-1842-z

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