Ranking model based on fuzzy variables

Abstract

Purpose: ranking technique based on fuzzy expert estimation developing. Discussion: the set of linguistic variables is commonly understood as a set of values that provides expert minimum degree of difficulty in estimation process. The fuzzy scale solves two problems. The fuzzy variables present generalized expert estimation on selected criteria and allow checking the degree of consensus of experts. Results: in this paper we proposed a solution of mentioned problems in the case when estimation is performed in a continuous fuzzy scale with linguistic variables, presented by trapezoidal numbers. This technique allows fuzzy and non-fuzzy general object estimations, ranking objects according to the degree of preference, as well as calculating the degree of agreement of expert estimates.