Multiple attribute group decision making based on 2-dimension linguistic intuitionistic fuzzy aggregation operators

被引:0
|
作者
Rajkumar Verma
José M. Merigó
机构
[1] University of Chile,Department of Management Control and Information Systems
[2] University of Technology Sydney,School of Information, Systems and Modelling, Faculty of Engineering and Information Technology
来源
Soft Computing | 2020年 / 24卷
关键词
Multiple attribute decision making; Linguistic intuitionistic fuzzy numbers; Linguistic variables; 2-dimension linguistic variables; 2-dimension linguistic intuitionistic fuzzy variables;
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学科分类号
摘要
The 2-dimension linguistic variables (2-DLVs) add a subjective evaluation on the reliability of the evaluation results provided by decision makers, so 2-DLVs are very useful tools for describing uncertain or fuzzy information. This work extends the idea of 2-DLVs by introducing 2-dimension linguistic intuitionistic fuzzy variables (2-DLIFVs) in which 1 class and 2 class information describe in the form of linguistic intuitionistic fuzzy numbers. The paper defines some operational laws, score, and accuracy functions for 2-DLIFVs. Further, we develop some arithmetic and geometric aggregation operators for aggregating 2-DLIF information and prove a number of valuable properties associated with them. Using the proposed aggregation operators, an approach for multiple attribute group decision making with 2-DLIF information is formulated. Finally, an illustrated example is given to verify and prove the validity of the developed method. The computed results are also compared with the existing results.
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页码:17377 / 17400
页数:23
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