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Article Dans Une Revue Mathematics of Operations Research Année : 2015

On the Convergence of Decomposition Methods for Multistage Stochastic Convex Programs

Résumé

We prove the almost-sure convergence of a class of sampling-based nested decomposition algorithms for multistage stochastic convex programs in which the stage costs are general convex functions of the decisions , and uncertainty is modelled by a scenario tree. As special cases, our results imply the almost-sure convergence of SDDP, CUPPS and DOASA when applied to problems with general convex cost functions.
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Dates et versions

hal-01208295 , version 1 (02-10-2015)

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Pierre Girardeau, Vincent Leclere, A. B. Philpott. On the Convergence of Decomposition Methods for Multistage Stochastic Convex Programs. Mathematics of Operations Research, 2015, 40 (1), ⟨10.1287/moor.2014.0664⟩. ⟨hal-01208295⟩
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