An Interactive data-driven (dynamic) multiple attribute decision making model via interval type-2 fuzzy functions

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dc.authoridBaykasoglu, Adil / 0000-0002-4952-7239
dc.authoridGolcuk, Ilker / 0000-0002-8430-7952
dc.authorscopusid7004171955
dc.authorscopusid56515313300
dc.authorwosidBaykasoglu, Adil/G-4311-2010
dc.authorwosidGolcuk, Ilker/B-2116-2015
dc.contributor.authorBaykasoğlu, Adil
dc.contributor.authorGölcük, İlker
dc.date.accessioned2022-02-15T16:57:24Z
dc.date.available2022-02-15T16:57:24Z
dc.date.issued2019
dc.departmentBakırçay Üniversitesien_US
dc.description.abstractA new multiple attribute decision making (MADM) model was proposed in this paper in order to cope with the temporal performance of alternatives during different time periods. Although dynamic MADM problems are enjoying a more visible position in the literature, majority of the applications deal with combining past and present data by means of aggregation operators. There is a research gap in developing data-driven methodologies to capture the patterns and trends in the historical data. In parallel with the fact that style of decision making evolving from intuition-based to data-driven, the present study proposes a new interval type-2 fuzzy (IT2F) functions model in order to predict current performance of alternatives based on the historical decision matrices. As the availability of accurate historical data with desired quality cannot always be obtained and the data usually involves imprecision and uncertainty, predictions regarding the performance of alternatives are modeled as IT2F sets. These estimated outputs are transformed into interpretable forms by utilizing the vocabulary matching procedures. Then the interactive procedures are employed to allow decision makers to modify the predicted decision matrix based on their perceptions and subjective judgments. Finally, ranking of alternatives are performed based on past and current performance scores.en_US
dc.identifier.doi10.3390/math7070584
dc.identifier.issn2227-7390
dc.identifier.issue7en_US
dc.identifier.scopus2-s2.0-85068854643en_US
dc.identifier.scopusqualityQ2en_US
dc.identifier.urihttps://doi.org/10.3390/math7070584
dc.identifier.urihttps://hdl.handle.net/20.500.14034/140
dc.identifier.volume7en_US
dc.identifier.wosWOS:000478765700023en_US
dc.identifier.wosqualityQ1en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherMDPIen_US
dc.relation.journalMathematicsen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectdynamic multiple attribute decision makingen_US
dc.subjectfuzzy regressionen_US
dc.subjectinterval type-2 fuzzy setsen_US
dc.subjectAggregation Operatorsen_US
dc.subjectFrameworken_US
dc.subjectSelectionen_US
dc.subjectSystemsen_US
dc.subjectVikoren_US
dc.titleAn Interactive data-driven (dynamic) multiple attribute decision making model via interval type-2 fuzzy functionsen_US
dc.typeArticleen_US

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