A comparative analysis of the rank reversal phenomenon in the EDAS and TOPSIS methods

Abstract

The rank reversal (RR) phenomenon could occur when new information about alternatives or criteria is added to the decision space of a discrete multi-criteria decision-making (MCDM) problem. If this addition leads to a change in the original rank of alternatives, the RR phenomenon occurs. In this study, we analyze the RR phenomenon in a new MCDM method called EDAS (Evaluation based on Distance from Average Solution). For this purpose, three RR indices are defined, and the efficiency of the EDAS method is compared with the TOPSIS method through a simulation-based analysis. The results show that the EDAS method is more efficient than the TOPSIS method with respect to the defined RR measures.