Deriving priorities based on representable uninorms from fuzzy preference relations

Abstract

Deriving priorities of objects from preference relations is an important research topic for decision making with preference information. In this paper, this issue is solved for fuzzy preference relations using representable uninorms, with which several alternative definitions of representable uninorm-based consistency (⊗-consistency) are provided for complete and incomplete fuzzy preference relations. In particular, a procedure to evaluate incomplete fuzzy preference relations with arbitrary n−1 independent preference values is provided. Furthermore, a novel acceptable ⊗-consistency is defined by the proposed local priority vectors, and then a method to check and reach the ⊗-consistency of fuzzy preference relations by reducing the distances between the optimal priority vector and local ones is proposed. Specific examples are illustrated to show how the models work, and comparisons with the existing methods are also offered to show the advantages of the proposed method.