Methodological study introduces a parameter-free compact fuzzy set for group decision making, indicating robust conflict modeling without data distortion.
Key Points
To introduce the compact fuzzy set (CFS) as a parameter-free, unifying framework that reliably models expert conflict without mathematical distortion or synthetic indeterminacy.
Formulated mathematical foundations for Compact Fuzzy Sets (CFS) to allow independent assignment of membership and non-membership degrees without normalization.
Assessed theoretical validity through asymptotic limit stability analysis and evaluated consistency with intuitionistic fuzzy sets.
Implemented a CFS-TOPSIS multi-criteria decision-making framework to evaluate reputation management strategies under high expert disagreement.
CFS eliminated synthetic indeterminacy and data loss by capturing high-inconsistency expert inputs without requiring arbitrary parameter tuning or data transformation.
Theoretical validation confirmed stability at asymptotic limits where other fuzzy extensions suffer from mathematical paradoxes.
Application of CFS-TOPSIS generated robust, stable strategy rankings despite severe disagreement among expert evaluators.