Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/30508
Full metadata record
DC FieldValueLanguage
dc.contributor.authorBranke, Juergen-
dc.contributor.authorVAN NIEUWENHUYSE, Inneke-
dc.contributor.authorRojas-Gonzalez, Sebastian-
dc.date.accessioned2020-02-12T15:03:26Z-
dc.date.available2020-02-12T15:03:26Z-
dc.date.issued2019-
dc.date.submitted2020-02-05T19:37:18Z-
dc.identifier.citationMustafee, N.; Bae, K.-H.G.; Lazarova-Molnar, S.; Rabe, M.; Szabo, C.; Haas, P.; Son, Y.-J. (Ed.). Proceedings - Winter Simulation Conference,p. 3392-3403-
dc.identifier.isbn978-1-7281-3283-9-
dc.identifier.issn0891-7736-
dc.identifier.urihttp://hdl.handle.net/1942/30508-
dc.description.abstractWe consider multi-objective ranking and selection problems with heteroscedastic noise and correlation between the mean values of alternatives. From a Bayesian perspective, we propose a sequential sampling technique that uses a combination of screening, stochastic kriging metamodels, and hypervolume estimates to decide how to allocate samples. Empirical results show that the proposed method only requires a small fraction of samples compared to the standard EQUAL allocation method, with the exploitation of the correlation structure being the dominant contributor to the improvement.-
dc.language.isoen-
dc.publisherIEEE-
dc.relation.ispartofseriesWinter Simulation Conference Proceedings-
dc.rightsWinter Simulation Conference 2019 2020.-
dc.titleMULTIOBJECTIVE RANKING AND SELECTION WITH CORRELATION AND HETEROSCEDASTIC NOISE-
dc.typeProceedings Paper-
local.bibliographicCitation.authorsMustafee , N.-
local.bibliographicCitation.authorsBae, K.-H.G.-
local.bibliographicCitation.authorsLazarova-Molnar, S.-
local.bibliographicCitation.authorsRabe, M.-
local.bibliographicCitation.authorsSzabo, C.-
local.bibliographicCitation.authorsHaas, P.-
local.bibliographicCitation.authorsSon, Y.-J.-
local.bibliographicCitation.conferencedateDecember 8-11-
local.bibliographicCitation.conferencenameWinter Simulation Conference (WSC)-
local.bibliographicCitation.conferenceplaceMaryland-
dc.identifier.epage3403-
dc.identifier.spage3392-
local.bibliographicCitation.jcatC1-
local.publisher.place345 E 47TH ST, NEW YORK, NY 10017 USA-
local.type.refereedRefereed-
local.type.specifiedProceedings Paper-
dc.source.typeMeeting-
dc.identifier.isi000529791403022-
dc.identifier.eissn-
local.provider.typePdf-
local.bibliographicCitation.btitleProceedings - Winter Simulation Conference-
local.uhasselt.uhpubyes-
local.uhasselt.internationalyes-
item.contributorBranke, Juergen-
item.contributorVAN NIEUWENHUYSE, Inneke-
item.contributorRojas-Gonzalez, Sebastian-
item.fullcitationBranke, Juergen; VAN NIEUWENHUYSE, Inneke & Rojas-Gonzalez, Sebastian (2019) MULTIOBJECTIVE RANKING AND SELECTION WITH CORRELATION AND HETEROSCEDASTIC NOISE. In: Mustafee, N.; Bae, K.-H.G.; Lazarova-Molnar, S.; Rabe, M.; Szabo, C.; Haas, P.; Son, Y.-J. (Ed.). Proceedings - Winter Simulation Conference,p. 3392-3403.-
item.accessRightsRestricted Access-
item.fulltextWith Fulltext-
item.validationecoom 2021-
crisitem.journal.issn0891-7736-
Appears in Collections:Research publications
Files in This Item:
File Description SizeFormat 
paperSebastian_finalproceedings.pdf
  Restricted Access		Published version5.57 MBAdobe PDFView/Open    Request a copy
Show simple item record

WEB OF SCIENCETM
Citations

2
checked on May 2, 2024

Page view(s)

86
checked on Sep 7, 2022

Download(s)

4
checked on Sep 7, 2022

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.