IMPACT OF THE OBJECTIVE ATTRIBUTE WEIGHTING ON FIVE POPULAR MULTI-CRITERIA DECISION-MAKING METHODS: AN EMPIRICAL STUDY

Abstract

In a Multi Criteria Decision Making (MCDM) problem, it is rarely possible to optimize all objectives simultaneously, since they can be contradictory, ambiguous or may involve other types of inconsistencies or uncertainties. Therefore, when trying to choose from a number of available alternatives, a decision maker is expected to assign weights to attributes whose values are utilized to evaluate the alternative under consideration for ranking. Attributes can be qualitative or quantitative, and their weights can be assigned by the decision maker in a somewhat subjective manner or algorithmically. In this paper, the impact of attribute weighting approaches on the ranking results across a number of widely used MCDM methods are discussed. That is, it examines how different weighting methods affect the results on the same multi-criteria decision-making methods when making a rating. In doing so, consider five MCDM methods, namely, Evamix, Aras, Topsis, Vikor, Waspas, under three different objective attribute weight assignment procedures, namely, Critic, Entropy, and Standart Deviation (SD). Results indicate that, in some cases, the employed attribute weight-assignment mechanism influences the rating results more heavily than the MCDM method itself. In other words, different MCDM methods tend to yield similar results under the same weight assignment method whereas, the same method produces more distinguishable results under different weighting schemes.