The Impacts of Aggregation Rules, Measurement Scale and Normalization Methods on Ranking of Alternatives in AHP

In this paper we analyze the impacts of various aggregation rules (additive and multiplicative), normalization methods (Saaty, vector, weitendorf’s linear, juttler-Korth, nonlinear and logarithmic), and measurement scales (linear, power, geometric, logarithmic, ischolar_main square, inverse linear and balanced), on the results of the well-known and widely used methods of MADM:Analytic Hierarchy Process (AHP). A problem with a known answer is used to test different conditions. In general, this studies an experimentally reveals that the 'Conventional AHP' method is more or equal effective to others in solving the Multiple Attribute Decision making problems. Therefore, we more recommended using the 'Conventional AHP' in various areas of human activities.