Weight Determination Methods in Fuzzy Environment

dc.contributor.authorHosseinzadeh Lotfi, F.
dc.contributor.authorAllahviranloo, T.
dc.contributor.authorPedrycz, W.
dc.contributor.authorShahriari, M.
dc.contributor.authorSharafi, H.
dc.contributor.authorRazipour, GhalehJough, S.
dc.date.accessioned2024-05-19T14:34:24Z
dc.date.available2024-05-19T14:34:24Z
dc.date.issued2023
dc.departmentİstinye Üniversitesien_US
dc.description.abstractThis chapter focuses on the determination of fuzzy weights in multi-criteria decision making (MCDM). Various methods for fuzzy weight determination are explored, with a particular emphasis on the fuzzy least square error method and the fuzzy BWM (Best Worst Method). The chapter presents theoretical explanations of these methods and provides practical examples to illustrate their application. Through the examination of these methods and their solutions, readers gain insights into the process of assigning weights to criteria in MCDM problems, considering the inherent uncertainty and imprecision in decision-making situations. The chapter aims to enhance readers’ understanding of fuzzy weight determination methods and their potential applicability in real-world decision-making scenarios. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2023.en_US
dc.identifier.doi10.1007/978-3-031-44742-6_3
dc.identifier.endpage100en_US
dc.identifier.issn1860-949X
dc.identifier.scopus2-s2.0-85184709303en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.startpage83en_US
dc.identifier.urihttps://doi.org/10.1007/978-3-031-44742-6_3
dc.identifier.urihttps://hdl.handle.net/20.500.12713/4479
dc.identifier.volume1121en_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer Science and Business Media Deutschland GmbHen_US
dc.relation.ispartofStudies in Computational Intelligenceen_US
dc.relation.publicationcategoryKitap Bölümü - Uluslararasıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.snmz20240519_kaen_US
dc.titleWeight Determination Methods in Fuzzy Environmenten_US
dc.typeBook Chapteren_US

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