Mining Weight Information from a Triangular Fuzzy Number Preference

A new method is presented to mine weight information from a triangular fuzzy number preference relation. Firstly, some new concepts about additive consistency are defined. Secondly, the triangular fuzzy number preference relation is transformed to some interval fuzzy preference relations by different reg-level sets. Four models are established to acquire different weight vectors. Thirdly, the final ranking weight vector is derived by the arithmetic mean of weight vectors. Finally, a numerical example is provided to illustrate the validity and practicality of our developed approach. In this paper, more potential weight information is mined. The decision makerpsilas preference is considered sufficiently.