Circular Intuitionistic Fuzzy Decision Making and Its Application

多准则决策分析 排名(信息检索) 加权 数学 数学优化 计算机科学 集合(抽象数据类型) 模糊集 点(几何) 功能(生物学) 模糊数 模糊逻辑 数据挖掘 算法 人工智能 程序设计语言 放射科 生物 进化生物学 医学 几何学
作者
Esra Çakır,Mehmet Ali Taş
出处
期刊:Expert Systems With Applications [Elsevier]
卷期号:225: 120076-120076 被引量:30
标识
DOI:10.1016/j.eswa.2023.120076
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 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.

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