Circular Intuitionistic Fuzzy Decision Making and Its Application

被引:29
|
作者
Cakir, Esra [1 ]
Tas, Mehmet Ali [2 ]
机构
[1] Galatasaray Univ, Dept Ind Engn, TR-34349 Istanbul, Turkiye
[2] Turkish German Univ, Dept Ind Engn, TR-34820 Istanbul, Turkiye
关键词
Circular intuitionistic fuzzy sets; Circular intuitionistic fuzzy MCDM; Fuzzy set extensions; C-IFS score function; Supply chain network; Supplier selection; SEAMLESS SUPPLY CHAIN; MCDM APPROACH; SELECTION; ENVIRONMENT; METHODOLOGY; EXTENSION; MODEL;
D O I
10.1016/j.eswa.2023.120076
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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 nonmembership. 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 (lambda). When the perspective of the decision-maker (lambda) approaches 1, it means that C-IFS is defuzzified close to its optimistic point, and when the perspective (lambda) 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.
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页数:13
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