Fuzzy rule based approach with z-numbers for selection of alternatives using TOPSIS

Abstract

The lack of ability to handle vagueness in the decision making practice has been main drawback of the conventional TOPSIS. Thus, type 1, type 2 and Z fuzzy sets have been applied with conventional TOPSIS to allow experts to incorporate imperfect information in analysis. However the existing methods do not take into account the influence degree of decision makers. Hence, a novel modification of TOPSIS method to handle vagueness and imperfect information in decision making practice is presented. The concept of Z- numbers is used to present decision maker's reliability. Furthermore, a hybrid analysis of decision making process that requires the use of human sensitivity to reflect influence degree of decision maker can be often expressed by a fuzzy rule base. The ranking based on proposed method is validated comparatively using Spearmen rho correlation coefficient. The result shows proposed method outperforms the existing non rule based version of TOPSIS in terms of ranking performance.