Revisiting the consistency improvement and consensus reaching processes of intuitionistic multiplicative preference relations. (April 2023)

• Record Type: Journal Article
• Authors: Wang, Rui; Chen, Zhen-Song; Shuai, Bin; Martínez, Luis; Kong, Wen-Tao; Pedrycz, Witold
• Is Part Of: Engineering applications of artificial intelligence. Volume 120(2023)
• Publication Date: 2023-04
• Subjects: Group decision-making -- Intuitionistic multiplicative preference relation -- Consistency improvement process -- Consensus reaching process; Engineering -- Data processing -- Periodicals; Artificial intelligence -- Periodicals; Expert systems (Computer science) -- Periodicals; Ingénierie -- Informatique -- Périodiques; Intelligence artificielle -- Périodiques; Systèmes experts (Informatique) -- Périodiques; Artificial intelligence; Engineering -- Data processing; Expert systems (Computer science); Periodicals; 620.00285
• DOI: 10.1016/j.engappai.2023.105931
• Languages: English
• ISSNs: 0952-1976

Abstract

Abstract: Intuitionistic multiplicative preference relation (IMPR) has been successfully and widely used to model the decision makers' preferences elicited by pairwise comparisons. As the critical links of group decision-making (GDM) procedure, the consistency improvement process (CIP) and consensus reaching process (CRP) have been investigated intensively; nevertheless, the extant methods explored the CIP and CRP of IMPRs without considering the situations of whether decision makers participate in the reassessment task. To overcome the limitation, this paper proposes two novel IMPR-based GDM approaches with CIP and CRP under different situations. First, when decision makers only express their original preferences, the novel consistency index and group consensus measure of IMPRs are defined to construct the CIP and CRP without feedback mechanism, in which the original preferences can be updated automatically. Second, when decision makers are required to modify their opinions, a series of consistency, consensus, and proximity degrees are put forwards to generate the identification and direction rules for improving the inconsistent and conflict preferences. Subsequently, the induced intuitionistic multiplicative ordered geometric averaging operator is constructed to fuse the individual preferences for determining the GDM results, in which the collective IMPR can maintain the acceptable consistency. Finally, a numerical example is applied to illustrate the feasibility and advantages of the proposed methods, which can improve the consistency and consensus levels of IMPRs according to the degrees of decision makers' involvement in the re-evaluation process.