Linguistic Interval-Valued Intuitionistic Fuzzy Frank Operators
LIU Limei1, GONG Yinli1, YANG Yi1, WU Shaozhi2
1. Key Laboratory of Hunan Province for New Retail Virtual Reality Technology, Hunan University of Technology and Business, Changsha 410205; 2. School of Computer Science and Engineering, University of Elec-tronic Science and Technology of China, Chengdu 611731
Abstract Aiming at the aggregation problem of linguistic interval-valued intuitionistic fuzzy information, Frank aggregation operator is proposed. A group decision-making method is constructed to solve the problem of supplier selection. Firstly, linguistic interval-valued intuitionistic fuzzy Frank operational laws are defined by introducing the extended Frank t-norms and s-norms, and linguistic interval-valued intuitionistic fuzzy Frank weighted averaging (LIVIFFWA) operator and geometric (LIVIFFWG) operator are proposed. Secondly, some properties of these operators are proved, such as idempotency, closeness and monotonicity, and the degeneracy of these operators with respect to parameters is analyzed. Then, based on the proposed LIVIFFWA operators and LIVIFFWG operators, a linguistic interval-valued intuitionistic fuzzy multi-attribute group decision-making method is constructed to solve the supplier decision-making problem. Finally, the feasibility and flexibility of the decision-making method are demonstrated through the case analysis of the selection of suppliers with shared bicycle recycling. The influence of parameter variation on decision-making results is discussed, and the ability of parameters to represent and feed back the attitudes of decision makers is verified.
Fund:Supported by National Social Science Foundation of China(No.18BGL181)
About author:: (LIU Limei, Ph.D., professor. Her research interests include logistics management and artificial intelligence.);(GONG Yinli, master student. Her research interests include intelligent logistics and emergency decision-making.);(YANG Yi(Corresponding author), Ph.D., lecturer. His research interests include intelligent decision-making and computing with words.);(WU Shaozhi, Ph.D., associate professor. His research interests include data mining and its application.)
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2020, Vol. 33 
