Dual-role factors for imprecise data envelopment analysis

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dc.cclicenceCC-BY-NCen
dc.contributor.authorHatami-Marbini, A.en
dc.date.accessioned2017-09-20T10:17:45Z
dc.date.available2017-09-20T10:17:45Z
dc.date.issued2017-07
dc.description.abstractIn conventional data envelopment analysis (DEA), the observed inputs, outputs and dual-factors are assumed to be precise. However, we often observe imprecise and ambiguous data in practice. In this paper, we present an imprecise DEA model in the presence of dual-role factors to deal with the imprecise data. The resulting models are the mixed binary integer programming models that supply the best possible relative efficiencies from the optimistic and pessimistic viewpoints. After some theoretical discussions, the proposed models are illustrated with a numerical example.en
dc.funderN/Aen
dc.identifier.citationHatami-Marbini, A. (2017) Dual-role factors for imprecise data envelopment analysis. 21st International Federation of Operational Research Societies (IFORS), July 17-21,2017, Quebec City, Canada.en
dc.identifier.urihttp://hdl.handle.net/2086/14516
dc.language.isoenen
dc.peerreviewedYesen
dc.projectidN/Aen
dc.publisherInternational Federation of Operational Research Societies (IFORS)en
dc.researchinstituteCentre for Enterprise and Innovation (CEI)en
dc.subjectdata envelopment analysisen
dc.titleDual-role factors for imprecise data envelopment analysisen
dc.typeConferenceen

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