Does “Fuzzifying” AHP Improve the Quality of Multi-Attribute Decision Making?

The Analytic Hierarchy Process (AHP) model was designed by Thomas L.Saaty (Saaty, 1980) in 1970s as a decision making aid. It is especially suitable for complex decisions which involve the comparison of decision elements which are difficult to quantify. It is based on the assumption that when faced with a complex decision the natural human reaction is to cluster the decision elements according to their common characteristics. Along the way of its development, people found that the uncertainty in assigning priorities for the selected decision elements is not being addressed. This naturally led to the incorporation of the traditional AHP with fuzzy logic to suggest the relative strength of factors in the corresponding criteria, thereby enabling the construction of a fuzzy judgment matrix to facilitate decision making. Fuzzy Analytic Hierarchy Process (FAHP) model became the solution to the problem. No doubt, FAHP has a better performance in dealing with vague input data, but the trade-off is a more complicated calculation it adds to the traditional AHP model. This paper aims to analyse the worthiness of using FAHP instead of traditional AHP to improve the quality of multi-attribute decision making in consideration of its complexity based on outranking method/ELECTRE 1.