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
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)
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Persistent link: https://EconPapers.repec.org/RePEc:spr:annopr:v:142:y:2006:i:1:p:215-241:10.1007/s10479-006-6169-8
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