On Complexity of Multistage Stochastic Programs
Alexander Shapiro (ashapiroisye.gatech.edu)
Abstract: In this paper we derive estimates of the sample sizes required to solve a multistage stochastic programming problem with a given accuracy by the (conditional sampling) sample average approximation method. The presented analysis is self contained and is based on a, relatively elementary, one dimensional Cramer's Large Deviations Theorem.
Keywords: stochastic programming, Monte Carlo sampling, sample average method, large deviations exponential bounds, complexity.
Category 1: Stochastic Programming
Citation: Working paper, Georgia Institute of Technology, Atlanta, GA
Entry Submitted: 01/06/2005
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