Dynamic multi-attribute decision making model based on triangular intuitionistic fuzzy numbers

Abstract

Triangular Intuitionistic Fuzzy Numbers (TIFNs) express more abundant and flexible information than Triangular Fuzzy Numbers (TFNs). The main purpose of this paper is to propose a Dynamic Multi-Attribute Decision Making (DMADM) model on the basis of TIFNs, to solve the DMADM problem, where all the decision information takes the form of TIFNs. A new distance measure between two TIFNs is developed to aid in determining attribute weights, using the entropy method. An aggregation operator, the weighted arithmetic averaging operator on TIFNs (TIFN-WAA), is presented to aggregate the decision information with TIFNs. Finally, the effectiveness and applicability of the proposed DMADM model, as well as analysis of comparison with another model, are illustrated with an investment example.