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Linguistic intuitionistic fuzzy Hamacher aggregation operators and their application to group decision making

  • Jie Tang
  • Fanyong Meng
Original Paper

Abstract

Linguistic intuitionistic fuzzy variables (LIFVs) can efficiently denote the qualitative preferred and non-preferred cognitions of decision makers. This paper researches group decision making with linguistic intuitionistic fuzzy information. To do this, several Hamacher operational laws on LIFVs are defined. To derive the comprehensive evaluating values of alternatives, several linguistic intuitionistic fuzzy Hamacher aggregation operators are proposed, including the linguistic intuitionistic fuzzy Hamacher weighted average operator, the linguistic intuitionistic fuzzy Hamacher weighted geometric mean operator, the linguistic intuitionistic fuzzy Hamacher ordered weighted average operator, the linguistic intuitionistic fuzzy Hamacher ordered weighted geometric mean operator, the linguistic intuitionistic fuzzy Hamacher hybrid weighted average operator, and the linguistic intuitionistic fuzzy Hamacher hybrid weighted geometric mean operator. Then, several of their desirable properties are researched to guarantee the rationality. Methods for determining the weights of criteria, decision makers as well as the ordered positions are offered, respectively. After that, a procedure for group decision making with linguistic intuitionistic fuzzy information is provided. Finally, a group decision-making problem is offered to illustrate the application of the new results.

Keywords

Group decision making Linguistic intuitionistic fuzzy variable Hamacher t-norm and t-conorm Aggregation operator 

Notes

Acknowledgements

This work was supported by the National Natural Science Foundation of China (nos. 71571192, and 71671188), the National Social Science Foundation of China (no. 16BJY119), the Innovation-Driven Project of Central South University (no. 2018CX039), the Major Project for National Natural Science Foundation of China (no. 71790615), the State Key Program of National Natural Science of China (no. 71431006), the Projects of Major International Cooperation NSFC (no. 71210003), and the Hunan Province Foundation for Distinguished Young Scholars of China (no. 2016JJ1024).

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  1. 1.School of BusinessCentral South UniversityChangshaChina

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