The Expected loss in the discretization of multistage stochastic programming problems—estimation and convergence rate

Martin Šmíd ()

Annals of Operations Research, 2009, vol. 165, issue 1, 29-45

Abstract: In the present paper, the approximate computation of a multistage stochastic programming problem (MSSPP) is studied. First, the MSSPP and its discretization are defined. Second, the expected loss caused by the usage of the “approximate” solution instead of the “exact” one is studied. Third, new results concerning approximate computation of expectations are presented. Finally, the main results of the paper—an upper bound of the expected loss and an estimate of the convergence rate of the expected loss—are stated. Copyright Springer Science+Business Media, LLC 2009

Keywords: Multistage stochastic programming problems; Approximation; Discretization; Monte Carlo (search for similar items in EconPapers)
Date: 2009
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DOI: 10.1007/s10479-008-0355-9

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