Abstract:

In this study, an interactive approach with the decision maker is proposed for sorting alternatives evaluated by multiple criteria. The preferences of the decision maker are assumed to be consistent with an additive utility function which is commonly used in literature. In the proposed approach, alternatives are assigned to categories by the decision maker through iterations. Based on the information obtained from the decision maker, mathematical models are solved in order to determine the worst and best possible categories of the alternatives. Accordingly, the probabilities of assigning alternatives to categories are calculated. Relative entropy, which is a measure of information theory, is used to measure the assignment ambiguity of the alternatives and select the alternative to be asked the decision maker. Alternatives with a certain level of assignment probability are probabilistically assigned to categories without consulting the decision maker. Assignment information from the decision maker is gathered iteratively until there are no alternative left. Our approach is compared against another approach from literature on a data set in the energy sector. The results show that the proposed approach is successful in reducing the cognitive burden of the decision maker.

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