Multi-choice conic goal programming model-based network data envelopment analysis

dc.authorid0000-0003-2676-1628
dc.authorid0000-0001-9226-211X
dc.authorid0000-0002-3762-6256
dc.authorid0000-0001-5831-932X
dc.contributor.authorDeliktaş, Derya
dc.contributor.authorÜstün, Özden
dc.contributor.authorAktar Demirtaş, Ezgi
dc.contributor.authorArapoğlu, Rıfat Aykut
dc.date.accessioned2024-09-23T07:43:37Z
dc.date.available2024-09-23T07:43:37Z
dc.date.issued2024
dc.departmentMühendislik Fakültesi
dc.description.abstractIn multi-stage processes, classical Data Envelopment Analysis (DEA) acts like a black box and measures the efficiency of decision-making units (DMUs) without considering the internal structure of the system. Unlike classical DEA, recent studies have shown that the overall system efficiency scores are more meaningful if researched using the Network DEA (NDEA) methodology. NDEA performs simultaneous efficiency evaluations of sub-processes and the entire system. Recently, the composition method integrated with multi-objective programming (MOP) has been preferred by many authors to alleviate the drawbacks of earlier methods such as decomposition, slack-based measure (SBM) and the system-centric approach. This study proposes a novel approach incorporating Multi-Choice Conic Goal Programming into the NDEA (MCCGP-NDEA). It provides a more accurate representation of the Pareto front by revealing potential Pareto optimal solutions which are overlooked by the composition methods. Due to its ability to modify stage weights based on the decision makers' (DMs) preferences, it is likely to gather more samples from the Pareto surface. Computational results on available benchmark problems confirm that the proposed MCCGP-NDEA is a viable alternative to existing methods.
dc.identifier.doi10.1051/ro/2024117
dc.identifier.endpage3416en_US
dc.identifier.issn0399-0559
dc.identifier.issn2804-7303
dc.identifier.issue4en_US
dc.identifier.scopusqualityQ2
dc.identifier.startpage3391en_US
dc.identifier.urihttps:/dx.doi.org/10.1051/ro/2024117
dc.identifier.urihttps://hdl.handle.net/20.500.12451/12441
dc.identifier.volume58en_US
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherEDP Sciences
dc.relation.ispartofRAIRO - Operations Research
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/embargoedAccess
dc.subjectData Envelopment Analysis
dc.subjectNetwork DEA
dc.subjectMulti-choice Conic Goal Programming
dc.subjectMulti-objective Programming
dc.titleMulti-choice conic goal programming model-based network data envelopment analysis
dc.typeArticle

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