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A note on sample complexity of multistage stochastic programs

Marcus de Mendes C. R. Reaiche (mmcr***at***impa.br)

Abstract: We derive a \emph{lower bound} for the \emph{sample complexity} of the Sample Average Approximation method for a certain class of multistage stochastic optimization problems. In previous works, \emph{upper bounds} for such problems were derived. We show that the dependence of the \emph{lower bound} with respect to the complexity parameters and the problem's data are comparable to the upper bound's estimates. Like previous results, our \emph{lower bound} presents an additional multiplicative factor showing that it is unavoidable for certain stochastic problems.

Keywords: Stochastic programming, Monte Carlo sampling, Sample average method, Complexity

Category 1: Stochastic Programming

Citation:

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Entry Submitted: 11/20/2014
Entry Accepted: 11/20/2014
Entry Last Modified: 03/17/2016

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