Three-way decision theory based on interval type-2 fuzzy linguistic term sets

• Published in: Journal of intelligent & fuzzy systems 2022-01, Vol.43 (4), p.3911-3932
• Main Authors: Peng, Jiangang, Cai, Ya, Xia, Guang, Hao, Ming
• Format: Article
• Language: English
• Subjects: Algorithms; Computation; Data analysis; Data integration; Decision analysis; Decision making; Decision theory; Fuzzy logic; Fuzzy sets; Information management; Linguistics; Multiple criterion; Theoretical linguistics
• ISSN: 1064-1246; 1875-8967
• DOI: 10.3233/JIFS-213236

This study examines decision theory based on interval type-2 fuzzy sets with linguistic information for the three-way decision approach by addressing the challenge of uncertainty for information analysis and fusion in subjective decision-making processes. First, the interval type-2 fuzzy linguistic term sets (IT2 FLTSs) are defined to represent and normalize the uncertain preference information in linguistic decision-making. Subsequently, perception computing based on computing with words paradigm is introduced to implement information fusion among different decision-makers in the linguistic information-based fuzzy logic reasoning process. Then, a three-way decision (3WD) theory based on IT2 FLTSs with fuzzy neighborhood covering is proposed, and the corresponded tri-partitioning strategies that satisfy Jaccard similarity of membership distributions are given. Finally, 3WD theory is applied to multi-criteria group decision-making with linguistic terms, and the algorithm steps are illustrated by a promising application under the background of coronavirus disease 2019 to reveal the feasibility and practicability of the proposed approach.