Consensus model for probabilistic linguistic multi-attribute group decision-making based on incomplete social trust networks
International Journal of Intelligent Computing and Cybernetics
ISSN: 1756-378X
Article publication date: 17 September 2024
Issue publication date: 11 November 2024
Abstract
Purpose
Experts may adjust their assessments through communication and mutual influence, and this dynamic evolution relies on the spread of internal trust relationships. Due to differences in educational backgrounds and knowledge experiences, trust relationships among experts are often incomplete. To address such issues and reduce decision biases, this paper proposes a probabilistic linguistic multi-attribute group decision consensus model based on an incomplete social trust network (InSTN).
Design/methodology/approach
In this paper, we first define the new trust propagation operators based on the operations of Probability Language Term Set (PLTS) with algebraic t-conorm and t-norm, which are combined with trust aggregation operators to estimate InSTN. The adjustment coefficients are then determined through trust relations to quantify their impact on expert evaluation. Finally, the particle swarm algorithm (PSO) is used to optimize the expert evaluation to meet the consensus threshold.
Findings
This study demonstrates the feasibility of the method through the selection of treatment plans for complex cases. The proposed consensus model exhibits greater robustness and effectiveness compared to traditional methods, mainly due to the effective regulation of trust relations in the decision-making process, which reduces decision bias and inconsistencies.
Originality/value
This paper introduces a novel probabilistic linguistic multi-attribute swarm decision consensus model based on an InSTN. It proposes a redefined trust propagation and aggregation approach to estimate the InSTN. Moreover, the computational efficiency and decision consensus accuracy of the proposed model are enhanced by using PSO optimization.
Keywords
Acknowledgements
This paper would like to thank the editors and the anonymous referees for their professional comments, which improved the quality of the manuscript. This work was funded in part by the National Natural Science Foundation of China (No. 12271211), the Open Fund of Digital Fujian Big Data Modeling and Intelligent Computing Institute, Pre-Research Fund of Jimei University.
Citation
Kang, K., Xie, J., Liu, X. and Qiu, J. (2024), "Consensus model for probabilistic linguistic multi-attribute group decision-making based on incomplete social trust networks", International Journal of Intelligent Computing and Cybernetics, Vol. 17 No. 4, pp. 844-868. https://doi.org/10.1108/IJICC-07-2024-0332
Publisher
:Emerald Publishing Limited
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