An improved HK model-driven consensus reaching for group decision making under interval-valued fuzzy preference relations with self-confidence. (September 2022)

• Record Type: Journal Article
• Authors: Li, Ling; Qiu, Lei; Liu, Xia; Xu, Yejun; Herrera-Viedma, Enrique
• Is Part Of: Computers & industrial engineering. Volume 171(2022)
• Publication Date: 2022-09
• Subjects: Interval-valued fuzzy preference relations -- Bounded confidence -- IHK model -- Self-confidence levels; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2022.108438
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: This paper proposed interval-valued fuzzy preference relation with self-confidence. Some operation laws regarding the IFPR-SC are presented. A novel feedback adjustment mechanism called IHK model is devised. Abstract: Self-confidence actually affects group decision making (GDM) because it can somehow reflect decision maker (DM)'s expertise and cognitive level. This paper proposes a new form of preference relation named interval-valued fuzzy preference relation with self-confidence (IFPR-SC). IFPR-SC requires DMs to express self-confidence levels when offering interval-valued preferences. Some operation laws regarding IFPR-SC are presented. Moreover, this paper uses an induced-ordered weighted aggregation operator to aggregate individual IFPRs-SC, then presents a novel feedback adjustment mechanism called improved Hegselmann-Kraus (IHK) model to update DMs' IFPRs-SC. Finally, this paper offers an illustrative example and several comparisons to verify the feasibility and efficiency of IHK model.