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dc.contributor.authorAzadi, Majid
dc.contributor.authorFarzipoor Saen, Reza
dc.contributor.authorTavana, Madjid
dc.date.accessioned2017-05-03T13:51:57Z
dc.date.available2017-05-03T13:51:57Z
dc.date.issued2012
dc.date.modified2013-08-20T00:06:14Z
dc.identifier.issn17485037
dc.identifier.doi10.1504/IJISE.2012.045179
dc.identifier.urihttp://hdl.handle.net/10072/52149
dc.description.abstractThe changing economic conditions have challenged many organisations to search for more efficient and effective ways to manage their supply chain. During recent years supplier selection decisions have received considerable attention in the supply chain management literature. There are four major decisions that are related to the supplier selection process: what product or services to order, from which suppliers, in what quantities and in which time periods? Data envelopment analysis (DEA) has been successfully used to select the most efficient supplier(s) in a supply chain. In this study, we introduce a novel supplier selection model using chance-constrained DEA with non-discretionary factors and stochastic data. We propose a deterministic equivalent of the stochastic non-discretionary model and convert this deterministic problem into a quadratic programming problem. This quadratic programming problem is then solved using algorithms available for this class of problems. We perform sensitivity analysis on the proposed non-discretionary model and present a case study to demonstrate the applicability of the proposed approach and to exhibit the efficacy of the procedures and algorithms.
dc.description.peerreviewedYes
dc.description.publicationstatusYes
dc.format.extent814105 bytes
dc.format.mimetypeapplication/pdf
dc.languageEnglish
dc.language.isoeng
dc.publisherInderscience Publishers
dc.publisher.placeUnited Kingdom
dc.relation.ispartofstudentpublicationN
dc.relation.ispartofpagefrom167
dc.relation.ispartofpageto196
dc.relation.ispartofissue2
dc.relation.ispartofjournalInternational Journal of Industrial and Systems Engineering
dc.relation.ispartofvolume10
dc.rights.retentionY
dc.subject.fieldofresearchCommerce, Management, Tourism and Services not elsewhere classified
dc.subject.fieldofresearchMechanical Engineering
dc.subject.fieldofresearchcode159999
dc.subject.fieldofresearchcode0913
dc.titleSupplier selection using chance-constrained data envelopment analysis with non-discretionary factors and stochastic data
dc.typeJournal article
dc.type.descriptionC1 - Articles
dc.type.codeC - Journal Articles
gro.rights.copyright© 2012 Inderscience Publishers. This is the author-manuscript version of this paper. Reproduced in accordance with the copyright policy of the publisher. Please refer to the journal website for access to the definitive, published version.
gro.date.issued2012
gro.hasfulltextFull Text
gro.griffith.authorFarzipoor Saen, Reza


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