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Çok Kriterli Karar Verme Problemlerinde Fayda Fonksiyonu Ağırlıklarının Tahmin Edilmesi için Matematiksel Model Temelli bir Yöntem

Yet, Barbaros
A basic issue in Multiple Criteria Decision Making (MCDM) problems is to include the preferences of the decision maker (DM) in the problem solution process. Many MCDM methods assume that DM preferences can be modeled in the form of utility functions. The parameters of these functions represent varying priorities of different DMs about the problem. Several approaches in the literature assume that these parameters are already known or the DM can express them directly and correctly. The approaches developed to derive preferential parameters may require the DM to make many assessments and comparisons, and involve complex procedures. The mathematical programming-based method developed in this study estimates criteria weights in weighted sum utility functions by few preference assessments without imposing cognitive difficulty on the DM. The DM is not asked to directly evaluate criteria but to rank a limited number of alternatives in preference order. The developed approach is applied to a financial portfolio selection problem with three criteria and a university ranking problem with five criteria. For comparison, the Swing method is also applied to the same problems. The proposed method is observed to be more convenient, impose less cognitive burden and provide superior results.