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Article type: Research Article
Authors: Tan, Chunqiao1; 2; * | Jia, Yuan2 | Chen, Xiaohong2
Affiliations: [1] School of Government Audit, Nanjing Audit University, Nanjing 211815, China | [2] School of Business, Central South University, Changsha 410083, China, E-mails: [email protected], [email protected]
Correspondence: [*] Corresponding author.
Abstract: In this paper, a new class of uncertain linguistic variables called 2-tuple linguistic hesitant fuzzy sets (2-TLHFSs) is defined, which can express complex multi-attribute decision-making problems as well as reflect decision makers’ hesitancy, uncertainty and inconsistency. Besides, it can avoid information and precision losing in aggregation process. Firstly, several new closed operational laws based on Einstein t-norm and t-conorm are defined over 2-TLHFSs, which can overcome granularity and logical problems of existing operational laws. Based on the new operational laws, 2-tuple linguistic hesitant fuzzy Einstein weighted averaging (2-TLHFEWA) operator and 2-tuple linguistic hesitant fuzzy Einstein weighted geometric (2-TLHFEWG) operator are proposed, and some of their properties are investigated. Then, a new model method based on similarity to ideal solution is proposed to determine weights of attribute, which takes both subjective and objective factors into consideration. Finally, a linguistic hesitant fuzzy multi-attribute decision making procedure is developed by means of 2-TLHFEWA and 2-TLHFEWG operators. An example is given to illustrate the practicality and efficiency of the proposed approach.
Keywords: multi-attribute decision making, aggregation operator, 2-tuple linguistic hesitant fuzzy sets, 2-tuple linguistic hesitant fuzzy Einstein weighted averaging operators, 2-tuple linguistic hesitant fuzzy Einstein weighted geometric operator
Journal: Informatica, vol. 28, no. 2, pp. 329-358, 2017
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