Use of rough sets and fuzzy sets in MCDC represents the 14-th chapter of the book “Multicriteria decision making”: Advances in MCDC models, algorithms, theory and applications”. In the subsection 14.1 the authors present the rough sets theory, introduced by Z. Pawlak, and also the connection between rough sets and fuzzy sets. The original rough sets theory is used in the analysis of multiattribute classification problems in subsection 14.3.1. In subsections 14.3.2 and 14.3.3, in order to deal with problems of MCDC, like sorting, choice or ranking, two important methodological changes to the original rough sets theory are introduced: approximation by dominance relations, which allows to deal with order properties of criteria, and pairwise comparison table, which allows to handle preference relations for choice and ranking problems. Finally, some other recently obtained results are given: rough approximations by means of similarity relations (crisp or fuzzy) and the equivalence of a decision rule preference model with a conjoint measurement model which is neither additive nor transitive.
For the entire collection see [Zbl 0928.00019].