Multi-criteria decision-making with linguistic labels

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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1. Short article

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2. Track 5: 4th International Symposium on Rough Sets: Theory and Applications

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3. Opracowanie rekordu ze środków MEiN, umowa nr SONP/SP/546092/2022 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2022-2023).