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Conference Paper: Sequential sampling for Bayesian robust ranking and selection

TitleSequential sampling for Bayesian robust ranking and selection
Authors
Zhang, XiaoweiDing, Liang
Issue Date2017
PublisherIEEE.
Citation
2016 Winter Simulation Conference (WSC 2016), Washington, DC, 11-14 December 2016. In Proceedings - Winter Simulation Conference, 2017, p. 758-769 How to Cite?
DOI: http://dx.doi.org/10.1109/WSC.2016.7822139
Abstract© 2016 IEEE. We consider a Bayesian ranking and selection problem in the presence of input distribution uncertainty. The distribution uncertainty is treated from a robust perspective. A naive extension of the knowledge gradient (KG) policy fails to converge in the new robust setting. We propose several stationary policies that extend KG in various aspects. Numerical experiments show that the proposed policies have excellent performance in terms of both probability of correction selection and normalized opportunity cost.
Persistent Identifierhttp://hdl.handle.net/10722/271489
ISSN
0891-7736
2023 SCImago Journal Rankings: 0.272

 

DC FieldValueLanguage
dc.contributor.authorZhang, Xiaowei-
dc.contributor.authorDing, Liang-
dc.date.accessioned2019-07-02T07:16:13Z-
dc.date.available2019-07-02T07:16:13Z-
dc.date.issued2017-
dc.identifier.citation2016 Winter Simulation Conference (WSC 2016), Washington, DC, 11-14 December 2016. In Proceedings - Winter Simulation Conference, 2017, p. 758-769-
dc.identifier.issn0891-7736-
dc.identifier.urihttp://hdl.handle.net/10722/271489-
dc.description.abstract© 2016 IEEE. We consider a Bayesian ranking and selection problem in the presence of input distribution uncertainty. The distribution uncertainty is treated from a robust perspective. A naive extension of the knowledge gradient (KG) policy fails to converge in the new robust setting. We propose several stationary policies that extend KG in various aspects. Numerical experiments show that the proposed policies have excellent performance in terms of both probability of correction selection and normalized opportunity cost.-
dc.languageeng-
dc.publisherIEEE.-
dc.relation.ispartofProceedings - Winter Simulation Conference-
dc.titleSequential sampling for Bayesian robust ranking and selection-
dc.typeConference_Paper-
dc.description.naturelink_to_subscribed_fulltext-
dc.identifier.doi10.1109/WSC.2016.7822139-
dc.identifier.scopuseid_2-s2.0-85014262615-
dc.identifier.spage758-
dc.identifier.epage769-
dc.identifier.issnl0891-7736-

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