Circular Intuitionistic Fuzzy Decision Making and Its Application

Circular intuitionistic fuzzy set (C-IFS) is introduced by Atanassov in 2020 as an extension of intuitionistic fuzzy sets. It is represented by a circle with a radius (r) of each element consist of degrees of membership and non-membership. Several MCDM methods based on distance measures of C-IFS are...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Expert systems with applications 2023-09, Vol.225, p.120076, Article 120076
Hauptverfasser: Çakır, Esra, Taş, Mehmet Ali
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Circular intuitionistic fuzzy set (C-IFS) is introduced by Atanassov in 2020 as an extension of intuitionistic fuzzy sets. It is represented by a circle with a radius (r) of each element consist of degrees of membership and non-membership. Several MCDM methods based on distance measures of C-IFS are already proposed in the literature. The primary objective of this study is the development, with the use of the C-IFS, of a new formulation of functions to form a novel C-IFS multi-criteria decision making (MCDM) method. In addition to the existing literature, this study contributes to circular intuitionistic fuzzy sets by proposing some formulations on radius calculation and a new defuzzification function for C-IFS. The optimistic and pessimistic points are also defined on the set to identify a novel score function and an accuracy function with decision-makers attitude (λ). When the perspective of the decision-maker (λ) approaches 1, it means that C-IFS is defuzzified close to its optimistic point, and when the perspective (λ) approaches 0, it is defuzzified close to the pessimistic point of C-IFS. With the use of these functions, a novel C-IFS MCDM method is presented based on criteria weighting and alternative ranking algorithms. This technique is applied to a supplier selection problem for a seamless supply chain network. A sensitivity analysis is also performed to test the effect of parameter changes on the final results. The findings of the study are compared with the results of a classical IFS-MCDM model. Since C-IFS is an extension of IFS, in addition to similar rankings, more precise results are obtained by considering the optimistic and pessimistic points by including the decision-maker attitude in the functions proposed for C-IFS. The study is a pioneer in the C-IFS literature by presenting C-IFS defuzzification function and a new C-IFS MCDM procedure.
ISSN:0957-4174
1873-6793
DOI:10.1016/j.eswa.2023.120076