Alpha-cut based fuzzy cognitive maps with applications in decision-making

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dc.authorscopusid7004171955
dc.authorscopusid56515313300
dc.contributor.authorBaykasoğlu, Adil
dc.contributor.authorGölcük, İlker
dc.date.accessioned2022-02-15T16:57:24Z
dc.date.available2022-02-15T16:57:24Z
dc.date.issued2021
dc.departmentBakırçay Üniversitesien_US
dc.description.abstractFuzzy cognitive maps (FCMs) are widely used fuzzy modeling tools for handling causal interdependencies in complex systems. In FCMs, system variables (concepts) and degree of interrelationships are quantified by means of fuzzy sets. However, these fuzzy sets are defuzzified and fuzzy singletons are processed in the inference algorithm. Defuzzification of fuzzy numbers before the FCM inference implies information loss which is an undesired situation. Moreover, the resultant concept values are fuzzy singletons that these crisp numbers do not provide any information about the range of possible outcomes. There is a research gap in the literature regarding fuzzy number representation in FCMs that the both of the inputs and outputs of FCMs being fuzzy sets. This study proposes alpha-cut based computational procedures for simulating FCMs in which concepts and degree of relationships are represented via fuzzy numbers. The proposed model is tested on well-known problems adopted from the literature by using type-1 fuzzy numbers and the results are compared with the extension principle-based approach. Moreover, the proposed model is extended to interval type-2 (IT2) fuzzy sets and computational details regarding IT2 FCMs are given. Because relative importance of criteria is usually modeled via fuzzy sets in multiple-attribute decision making problems, a new FCM-based objective weighting method is proposed in order to demonstrate the usefulness of fuzzy number representation in FCMs. The proposed model is implemented in the real-life third-party logistics service provider selection problem.en_US
dc.description.sponsorshipScientific Research Projects Governing Unit (BAPYB) of Dokuz Eylul UniversityDokuz Eylul University [KB.FEN.025]en_US
dc.description.sponsorshipThis work was supported by a Scientific Research Projects Governing Unit (BAPYB) of Dokuz Eylul University, project No: 2016.KB.FEN.025.en_US
dc.identifier.doi10.1016/j.cie.2020.107007
dc.identifier.issn0360-8352
dc.identifier.issn1879-0550
dc.identifier.scopus2-s2.0-85098123337en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.urihttps://doi.org/10.1016/j.cie.2020.107007
dc.identifier.urihttps://hdl.handle.net/20.500.14034/141
dc.identifier.volume152en_US
dc.identifier.wosWOS:000614112600019en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.journalComputers & Industrial Engineeringen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectAlpha-cuten_US
dc.subjectCriteria weightingen_US
dc.subjectDecomposition theoremen_US
dc.subjectFuzzy cognitive mapsen_US
dc.subjectInterval type-2 fuzzy setsen_US
dc.subjectDecision analysesen_US
dc.titleAlpha-cut based fuzzy cognitive maps with applications in decision-makingen_US
dc.typeArticleen_US

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