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dc.contributor.authorSabuncuoglu, I.en_US
dc.contributor.authorFadiloglu, M. M.en_US
dc.contributor.authorÇelik, S.en_US
dc.date.accessioned2016-02-08T10:09:22Z
dc.date.available2016-02-08T10:09:22Z
dc.date.issued2008en_US
dc.identifier.issn0740-817X
dc.identifier.urihttp://hdl.handle.net/11693/23132
dc.description.abstractWe provide a thorough analysis of the effectiveness of different Variance Reduction Techniques (VRTs). We consider both stand-alone and combined applications of two input techniques, Antithetic Variates (AV) and Latin Hypercube Sampling (LHS), and two output techniques, Control Variates (CV) and Poststratified Sampling (PS). Previous research in the area mainly focuses on asymptotic variance reduction. In this experimental study, we measure the performance of VRTs under finite simulation run lengths and analyze their effects. Our findings show that the asymptotic variance reduction results do not readily apply to finite-length simulations. We consider three different types of systems (M/M/1, serial production line and (s, S) inventory control systems) and compare the VRTs under various experimental conditions. We observe that a variance reduction cannot be guaranteed for every instance a VRT is applied. Our results also indicate that the output VRTs (CV, PS) are better than input VRTs (AV, LHS) on the average for the single systems considered in this study. More interestingly, the less-sophisticated techniques (AV, CV) often perform better than the relatively more-complex techniques (LHS, PS). A comprehensive bibliography is also provided.en_US
dc.language.isoEnglishen_US
dc.source.titleIIE Transactions (Institute of Industrial Engineers)en_US
dc.relation.isversionofhttp://dx.doi.org/10.1080/07408170701761938en_US
dc.subjectSimulation,en_US
dc.subjectVariance reduction techniquesen_US
dc.subjectAntithetic variatesen_US
dc.subjectLatin hypercube samplingen_US
dc.subjectControl variatesen_US
dc.subjectPoststratified samplingen_US
dc.titleVariance reduction techniques: experimental comparison and analysis for single systemsen_US
dc.typeArticleen_US
dc.departmentDepartment of Industrial Engineering
dc.citation.spage538en_US
dc.citation.epage551en_US
dc.citation.volumeNumber40en_US
dc.citation.issueNumber5en_US
dc.identifier.doi10.1080/07408170701761938en_US
dc.publisherTaylor & Francisen_US
dc.identifier.eissn1545-8830


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