Abstract
Deriving priority vectors for preference relations in group decision-making (GDM) is an interesting research topic. In this paper, this issue is examined for GDM with fuzzy preference relations (FPRs). It is proven that both the parameterized Tanino's normality and the usual k-normality are crucial to characterize additively consistent FPRs, based on which some existing results to derive priority vectors for additively consistent FPRs are improved by adding a suitable normality. Then, visible methods to check and modify the acceptably additive consistency and the consensus of FPRs in GDM are proposed without a preset threshold. Some examples are given to demonstrate how the proposed methods work, and comparisons to existing methods are also offered to indicate the advantages of the proposed methods.
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