Please use this identifier to cite or link to this item: https://doi.org/10.1007/s10589-010-9328-4
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dc.titleA smoothing sample average approximation method for stochastic optimization problems with CVaR risk measure
dc.contributor.authorMeng, F.
dc.contributor.authorSun, J.
dc.contributor.authorGoh, M.
dc.date.accessioned2014-05-20T02:28:43Z
dc.date.available2014-05-20T02:28:43Z
dc.date.issued2011-10
dc.identifier.citationMeng, F., Sun, J., Goh, M. (2011-10). A smoothing sample average approximation method for stochastic optimization problems with CVaR risk measure. Computational Optimization and Applications 50 (2) : 379-401. ScholarBank@NUS Repository. https://doi.org/10.1007/s10589-010-9328-4
dc.identifier.issn09266003
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/53387
dc.description.abstractThis paper is concerned with solving single CVaR and mixed CVaR minimization problems. A CHKS-type smoothing sample average approximation (SAA) method is proposed for solving these two problems, which retains the convexity and smoothness of the original problem and is easy to implement. For any fixed smoothing constant ε, this method produces a sequence whose cluster points are weak stationary points of the CVaR optimization problems with probability one. This framework of combining smoothing technique and SAA scheme can be extended to other smoothing functions as well. Practical numerical examples arising from logistics management are presented to show the usefulness of this method. © 2010 Springer Science+Business Media, LLC.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1007/s10589-010-9328-4
dc.sourceScopus
dc.subjectConditional value-at-risk
dc.subjectSample average approximation
dc.subjectSmoothing method
dc.subjectStochastic optimization
dc.typeArticle
dc.contributor.departmentCENTRE FOR MARITIME STUDIES
dc.contributor.departmentDECISION SCIENCES
dc.description.doi10.1007/s10589-010-9328-4
dc.description.sourcetitleComputational Optimization and Applications
dc.description.volume50
dc.description.issue2
dc.description.page379-401
dc.description.codenCPPPE
dc.identifier.isiut000295574600009
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