Please use this identifier to cite or link to this item: https://doi.org/10.1109/WSC.2007.4419642
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dc.titleFinding the pareto set for multi-objective simulation models by minimization of expected opportunity cost
dc.contributor.authorLee, L.H.
dc.contributor.authorChew, E.P.
dc.contributor.authorTeng, S.
dc.date.accessioned2014-10-07T10:26:49Z
dc.date.available2014-10-07T10:26:49Z
dc.date.issued2007
dc.identifier.citationLee, L.H.,Chew, E.P.,Teng, S. (2007). Finding the pareto set for multi-objective simulation models by minimization of expected opportunity cost. Proceedings - Winter Simulation Conference : 513-521. ScholarBank@NUS Repository. <a href="https://doi.org/10.1109/WSC.2007.4419642" target="_blank">https://doi.org/10.1109/WSC.2007.4419642</a>
dc.identifier.isbn1424413060
dc.identifier.issn08917736
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/87323
dc.description.abstractIn this study, we mainly explore how to optimally allocate the computing budget for a multi-objective ranking and selection (MORS) problem when the measure of selection quality is the expected opportunity cost (OC). We define OC incurred to both the observed Pareto and non-Pareto set, and present a sequential procedure to allocate the replications among the designs according to some asymptotic allocation rules. Numerical analysis shows that the proposed solution framework works well when compared with other algorithms in terms of its capability of identifying the true Pareto set. © 2007 IEEE.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1109/WSC.2007.4419642
dc.sourceScopus
dc.typeConference Paper
dc.contributor.departmentINDUSTRIAL & SYSTEMS ENGINEERING
dc.description.doi10.1109/WSC.2007.4419642
dc.description.sourcetitleProceedings - Winter Simulation Conference
dc.description.page513-521
dc.description.codenWSCPD
dc.identifier.isiutNOT_IN_WOS
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