Artificial Intelligence


Intuitionistic Fuzzy Decision-Making in the Framework of Dempster-Shafer Structures

Authors: Liguo Fei

The main emphasis of this paper is placed on the problem of multi-criteria decision making (MCDM) in intuitionistic fuzzy environments. Some limitations in the existing literature that explains Atanassov’ intuitionistic fuzzy sets (A-IFS) from the perspective of Dempster-Shafer theory (DST) of evidence have been analyzed. To address the issues of using Dempster’s rule to aggregate intuitionistic fuzzy values (IFVs), a novel aggregation operator named OWA-based MOS is proposed based on ordered weighted averaging (OWA) aggregation operator, which allows the expression of decision makers’ subjectivity by introducing the attitudinal character. The effectiveness of the developed OWAbased MOS approach in aggregating IFVs is demonstrated by the known example of MCDM problem. To compare different IFVs obtained from the OWA-based MOS approach, the golden rule representative value for IFVs comparison is introduced, which can get over the shortcomings of score functions. The hierarchical structure of the proposed decision approach is presented based on the above researches, which allow us to solve MCDM problem without intermediate defuzzification when not only criteria, but their weights are represented by IFVs. The proposed OWA-based MOS approach is illustrated as a more flexible decision-making method, which can better solve the problem of intuitionistic fuzzy multi-criteria decision making in the framework of DST.

Comments: 15 Pages.

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Submission history

[v1] 2019-07-12 09:06:31

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