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A survey of decision-making methods with probabilistic linguistic information: bibliometrics, preliminaries, methodologies, applications and future directions

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Abstract

Probabilistic linguistic term set (PLTS) has been proposed to tackle qualitative information efficiently in the decision-making process to achieve computing with expressions, which can be regarded as an advanced process of computing with words. The PLTS plays an important role in decision making by providing a comprehensive way for representing complex linguistic information. Owning to its usefulness and efficiency, the PLTS has attracted a lot of researchers’ attention, and fruitful research achievements regarding it has been published since it was introduced in 2016. As the probabilistic linguistic theory is still in its infancy, a survey of it contributes to understanding the previous topics and the current issues, and predicting the future research directions in this area. To implement these goals, this paper is organized by bibliometric analysis, definitions, multiple criteria decision-making methods, preference relations, and applications. Twelve future research directions related to the probabilistic linguistic decision-making theory are indicated. This paper provides some insights for researchers and practitioners who have interest in complex linguistic decision making.

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Acknowledgements

The work was supported by the National Natural Science Foundation of China (Nos. 71771156, 71771155, 71971145).

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Authors and Affiliations

  1. Business School, Sichuan University, Chengdu, 610064, Sichuan, China

    Huchang Liao, Xiaomei Mi & Zeshui Xu

  2. School of Computer and Software, Nanjing University of Information Science and Technology, Nanjing, 210044, China

    Zeshui Xu

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  1. Huchang Liao
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  2. Xiaomei Mi
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  3. Zeshui Xu
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Correspondence to Zeshui Xu.

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Appendix

Appendix

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Liao, H., Mi, X. & Xu, Z. A survey of decision-making methods with probabilistic linguistic information: bibliometrics, preliminaries, methodologies, applications and future directions. Fuzzy Optim Decis Making 19, 81–134 (2020). https://doi.org/10.1007/s10700-019-09309-5

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