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

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Abstract

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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Acknowledgements

This work was financially supported by the Chilean Government (Conicyt) through the Fondecyt Postdoctoral program (Project Number-3170556).

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Correspondence to Rajkumar Verma.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Communicated by V. Loia.

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Verma, R., Merigó, J.M. Multiple attribute group decision making based on 2-dimension linguistic intuitionistic fuzzy aggregation operators. Soft Comput 24, 17377–17400 (2020). https://doi.org/10.1007/s00500-020-05026-z

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  • DOI: https://doi.org/10.1007/s00500-020-05026-z

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