An extended MABAC method for multiple-attribute group decision making under probabilistic T-spherical hesitant fuzzy environment
ISSN: 0368-492X
Article publication date: 28 April 2022
Issue publication date: 1 November 2023
Abstract
Purpose
The purpose of this article is to present the idea of a T-spherical hesitant fuzzy set associated with probability and to develop an extended multi-attributive border approximation area comparison (MABAC) method under probabilistic T-spherical hesitant fuzzy (Pt-SHF) settings.
Design/methodology/approach
The authors define some basic operational laws for Pt-SHF sets (Pt-SHFSs) and a comparison method of two probabilistic T-spherical hesitant fuzzy numbers (Pt-SHFNs) is proposed. Moreover, some Pt-SHF aggregation operators and the multi-attributive border approximation area comparison (MABAC) method are established under Pt-SHF scenario to solve group decision making problems.
Findings
The developed Pt-SHF MABAC method for multi-attribute group decision making (MAGDM) can overcome the drawbacks of conventional MABAC method and limitations for decision makers, which they face while providing their assessment concerning any object.
Research limitations/implications
Clearly, this paper is devoted to MABAC method, MAGDM and probabilistic T-spherical hesitant fuzzy set theory.
Practical implications
The approach established can be used in a variety of scenarios, including decision making, engineering, and economics. An explanatory example is illustrated which shows the superiority and effectiveness of our proposed technique.
Originality/value
If a T-spherical fuzzy MAGDM problem under the probabilistic scenario needs to be evaluated, the involvement of probabilities in fuzzy system will be lost because of no information. This work fills a gap in literature by establishing the notion of probabilistic t-spherical hesitant fuzzy set to deal with the ambiguity, uncertainty in decision making problems.
Keywords
Acknowledgements
The work was supported by National Natural Science Foundation of China (Nos. 71871001, 72001001); Natural Science Foundation for Distinguished Young Scholars of Anhui Province (No. 1908085J03); Research Funding Project of Academic and technical leaders and reserve candidates in Anhui Province (No.2018H179).
Conflict of interest: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Citation
Gurmani, S.H., Chen, H. and Bai, Y. (2023), "An extended MABAC method for multiple-attribute group decision making under probabilistic T-spherical hesitant fuzzy environment", Kybernetes, Vol. 52 No. 10, pp. 4041-4060. https://doi.org/10.1108/K-01-2022-0137
Publisher
:Emerald Publishing Limited
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