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A consensus reaching process with hesitant fuzzy elements considers the individuals best and worst consensus levels

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Abstract

The purposes of the study: to address the situation where multi-criteria decision-making (MCDM) problems with hesitant fuzzy elements (HFEs), this study develops group decision-making method considering the individuals best and worst consensus levels simultaneously. Procedures: first, the concepts of individual best and worst consensus levels are proposed, and then, the concept of acceptable consensus level is developed. Second, several optimization models are constructed for improving the consensus levels. Third, the proposed consensus checking and improving processes are extended to incomplete evaluation information. Fourth, an algorithm is designed for deriving the priority weights of decision-makers. Finally, an illustrative example in conjunction with comparative analysis is provided. Findings: the concept of acceptable individual consensus level with HFEs not only overcomes the shortcoming of difficult to achieve owing to too restricted, but also the loss of information owing to too loose. The consensus improving process considers all the evaluation information and avoids the loss of information. Conclusions: Several programming models are constructed to improve the consensus level with HFEs. This provides the direction of the decision-makers to revise their evaluation values, and the consensus improving process is time-saving and easy to extend to incomplete evaluation information.

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Acknowledgements

The authors thank the anonymous reviewers and the editor for their insightful and constructive comments and suggestions that have led to an improved version of this paper. This work was supported by the National Natural Science Foundation of China (No.72061026), the Natural Science Foundation of Guangxi (No. 2020GXNSFAA297239), the Science and Technology Plan of Guangxi (No. gui ke AD20238006) and Young Teachers’ Basic Scientific Research Ability in Universities of Guangxi (Nos. 2022KY0387, 2021KY1563 and 2021KY1560).

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Authors and Affiliations

  1. School of Logistics Management and Engineering, Nanning Normal University, Nanning, 530001, People’s Republic of China

    Jian Li & Qiongxia Chen

  2. Guangxi Agricultural Vocational and Technical University, Nanning, 530007, People’s Republic of China

    Li-li Niu & Limei Wei

  3. Guangxi Key Lab of Human-Machine Interaction and Intelligent Decision, Nanning, 530001, People’s Republic of China

    Jian Li

  4. Guangxi Medical University Cancer Hospital, Nanning, 530021, People’s Republic of China

    Feilong Li

  5. School of Mathematics and Information Science, Guangxi University, Nanning, 530004, People’s Republic of China

    Zhong-xing Wang

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  1. Jian Li
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Correspondence to Qiongxia Chen.

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Authors Jian Li, Li-li Niu, Qiongxia Chen, Feilong Li, Limei Wei and Zhong-xing Wang declare that they have no conflict of interest.

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Li, J., Niu, Ll., Chen, Q. et al. A consensus reaching process with hesitant fuzzy elements considers the individuals best and worst consensus levels. Knowl Inf Syst 65, 3665–3693 (2023). https://doi.org/10.1007/s10115-023-01874-x

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