Multi-Criteria Decision-Making with Linguistic Labels
Alicja Mieszkowicz-Rolka, Leszek Rolka
Citation: Proceedings of the 17th Conference on Computer Science and Intelligence Systems, M. Ganzha, L. Maciaszek, M. Paprzycki, D. Ślęzak (eds). ACSIS, Vol. 30, pages 263–267 (2022)
Abstract. This paper proposes an approach that is suitable for solving multi-criteria decision-making problems that are characterized by fuzzy (subjective) criteria.A finite set (universe) of alternatives will be expressed as a decision table that represents a fuzzy information system, in which every fuzzy criterion is connected with a set of its linguistic values. We apply subjective preference degrees for linguistic values that should be provided by a decision-maker. To simplify the process of decision-making in big data environments, an additional stage will be introduced that can produce a smaller set of alternatives represented by fuzzy linguistic labels of similarity classes. We select a small set of similarity classes for a final ranking. A measure of compatibility will be defined that should express the accordance of a selected alternative with preferences given for the linguistic values of a particular fuzzy criterion.
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