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

Linowsky, K. ; Philpott, A.

In: Journal of Optimization Theory and Applications, 2005, vol. 125, no. 2, p. 349-366

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    Titel
    • On the Convergence of Sampling-Based Decomposition Algorithms for Multistage Stochastic Programs
    Autor
    • Linowsky, K.. PhD Student, University of St. Gallen, St. Gallen, Switzerland
    • Philpott, A.. Professor, University of Auckland, Auckland, New Zealand
    Dokumententyp
    • Postprint
    Sprache
    • Englisch
    Veröffentlicht in
    • Journal of Optimization Theory and Applications, 2005, vol. 125, no. 2, p. 349-366. Kluwer Academic Publishers-Plenum Publishers
    Andere elektronische Ausgabe
    OAI-PMH-ID
    • oai:doc.rero.ch:311029
    Summary
    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