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The empirical behavior of sampling methods for stochastic programming

Jeff Linderoth (), Alexander Shapiro () and Stephen Wright ()

Annals of Operations Research, 2006, vol. 142, issue 1, 215-241

Abstract: We investigate the quality of solutions obtained from sample-average approximations to two-stage stochastic linear programs with recourse. We use a recently developed software tool executing on a computational grid to solve many large instances of these problems, allowing us to obtain high-quality solutions and to verify optimality and near-optimality of the computed solutions in various ways. Copyright Springer Science + Business Media, Inc. 2006

Keywords: Stochastic linear programming; Recourse; Sample average approximations; Computational grid; Monte Carlo sampling; Optimality gap; Statistical KKT test (search for similar items in EconPapers)
Date: 2006
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DOI: 10.1007/s10479-006-6169-8

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Handle: RePEc:spr:annopr:v:142:y:2006:i:1:p:215-241:10.1007/s10479-006-6169-8