Consistency improvement with a feedback recommendation in personalized linguistic group decision making
Consistency is an important issue in linguistic decision making with various consistency measures and consistency improving methods available in the literature. However, existing linguistic consistency studies omit the fact that words mean different things for different people, that is, decision makers' personalized individual semantics (PISs) over their expressed linguistic preferences are ignored. Therefore, the aim of this article is to propose a novel consistency improving approach based on PISs in linguistic group decision making. The proposed approach combines the characteristics of personalized representation and integrates the PIS-based model in measuring and improving the consistency of linguistic preference relations. A detailed numerical and comparative analysis to support the feasibility of the proposed approach is provided.
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.
Citation : Li, C-C., Liang, H., Dong, Y., Chiclana, F., Herrera-Viedma, E. (2021) Consistency improvement with a feedback recommendation in personalized linguistic group decision making. IEEE Transactions on Cybernetics.
ISSN : 2168-2267
Research Institute : Institute of Artificial Intelligence (IAI)
Peer Reviewed : Yes