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Dynamic multi-attribute grey target group decision model based on quantum-like Bayesian networks

Na Zhang (Business School, Nanjing University of Information Science and Technology, Nanjing, China) (Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, The Research Institute for Risk Governance and Emergency Decision-Making, Nanjing, China)
Haiyan Wang (Business School, Nanjing University of Information Science and Technology, Nanjing, China)
Zaiwu Gong (School of Management Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, China) (Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, The Research Institute for Risk Governance and Emergency Decision-Making, Nanjing, China)

Grey Systems: Theory and Application

ISSN: 2043-9377

Article publication date: 29 November 2023

Issue publication date: 15 January 2024

114

Abstract

Purpose

Grey target decision-making serves as a pivotal analytical tool for addressing dynamic multi-attribute group decision-making amidst uncertain information. However, the setting of bull's eye is frequently subjective, and each stage is considered independent of the others. Interference effects between each stage can easily influence one another. To address these challenges effectively, this paper employs quantum probability theory to construct quantum-like Bayesian networks, addressing interference effects in dynamic multi-attribute group decision-making.

Design/methodology/approach

Firstly, the bull's eye matrix of the scheme stage is derived based on the principle of group negotiation and maximum satisfaction deviation. Secondly, a nonlinear programming model for stage weight is constructed by using an improved Orness measure constraint to determine the stage weight. Finally, the quantum-like Bayesian network is constructed to explore the interference effect between stages. In this process, the decision of each stage is regarded as a wave function which occurs synchronously, with mutual interference impacting the aggregate result. Finally, the effectiveness and rationality of the model are verified through a public health emergency.

Findings

The research shows that there are interference effects between each stage. Both the dynamic grey target group decision model and the dynamic multi-attribute group decision model based on quantum-like Bayesian network proposed in this paper are scientific and effective. They enhance the flexibility and stability of actual decision-making and provide significant practical value.

Originality/value

To address issues like stage interference effects, subjective bull's eye settings and the absence of participative behavior in decision-making groups, this paper develops a grey target decision model grounded in group negotiation and maximum satisfaction deviation. Furthermore, by integrating the quantum-like Bayesian network model, this paper offers a novel perspective for addressing information fusion and subjective cognitive biases during decision-making.

Keywords

Acknowledgements

This work was supported by National Social Science Foundation (Grant No. 2023BMZ046), Jiangsu University Philosophy and Social Science Research Project (Grant No. 2022SJZD080), Jiangsu Province Social Science Fund Project (Grant No. 22EYB001).

Citation

Zhang, N., Wang, H. and Gong, Z. (2024), "Dynamic multi-attribute grey target group decision model based on quantum-like Bayesian networks", Grey Systems: Theory and Application, Vol. 14 No. 1, pp. 209-231. https://doi.org/10.1108/GS-08-2023-0072

Publisher

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Emerald Publishing Limited

Copyright © 2023, Emerald Publishing Limited

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