Abstract:

The aim of this paper is to deal with the aggregating problem of group evaluation under fuzzy preference. A new similarity measuring function that is situated between two trapezoidal fuzzy numbers is computed by using distance functions, which makes its applied scope expand. The unanimity between individual and group is measured by utilizing entropy, a group entropy model is established and the uncertainty of the group is reduced. With the aid of the model, the expert’s original weight is modified to a revised weight by an iterative procedure, and then the expert’s integrative weight is linear synthesized by original weight and revised weight. Finally， an example is applied to demonstrate the practicability and validity of this approach.