Research on Decision-Making Consensus Methods for Groups of Different Scales and Visualization of the Discussion Opinions Convergence Process

DOI: https://doi.org/10.62517/jes.202602213

Author(s)

Hengshan Zong*, Yang Li

Affiliation(s)

China Aerospace Academy of Systems Science and Engineering, Beijing, China *Corresponding Author

Abstract

With the continuous and rapid development of big data, cloud computing, and artificial intelligence technologies, a large number of complex giant systems have emerged in various fields of society. Faced with complex decision-making problems, theories and methods related to group consensus decision-making have gradually become a research hotspot. Aiming at the deficiencies in existing group consensus decision-making research, such as poor method universality, difficulty in intuitively displaying the opinion convergence process, and large gaps in decision-making efficiency among groups of different scales, this paper conducts a systematic study on multi-scale group consensus decision-making methods and the visualization of the dynamic convergence process of discussion opinions. The experimental results show that the scale-adaptive consensus decision-making model constructed in this paper can effectively improve the consensus formation efficiency of various groups and reduce the consumption of the decision-making process. Meanwhile, the built visualization system can fully display the whole process of opinion evolution and convergence, providing an intuitive basis and technical support for the optimization and adjustment of group decision-making schemes.

Keywords

Group Consensus; Decision-Making Method; Expert Collaboration; Cluster Analysis; Visualization

References

[1]Dalkey N, Helmer O. An experimental application of the Delphi method to the use of experts. Management Science, 1963, 9(3): 458-467. [2]Delbecq A L, Van de Ven A H, Gustafson D H. Group Techniques for Program Planning: A Guide to Nominal Group and Delphi Processes. Glenview: Scott Foresman, 1975. [3]Nadkarni S, Shenoy P P. A Causal Mapping Approach to Constructing Bayesian Networks. Decision Support Systems, 2004, 38: 259-281. [4]Hassani H, Razavi R, Saif M, et al. Reinforcement learning-based feedback and weight-adjustment mechanisms for consensus reaching in group decision making. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2022, 53(1): 354-366. [5]Deffuant G, Neau D, Amblard F, et al. Mixing Beliefs Among Interacting Agents. Advances in Complex Systems, 2000, 3: 87-98. [6]Hegselmann R, Krause U. Opinion Dynamics Driven by Various Ways of Averaging. Computational Economics, 2005, 25(4): 381-380. [7]Liu Y Z, Fan Z P, Li M Y. A Risk-type Fuzzy Multi-attribute Decision-Making Method Considering Decision-Makers Giving Reference Points. Systems Engineering and Electronics, 2014, 36(7): 1358-1367. [8]Wang J Q. A Multi-criteria Linguistic Group Decision-Making Method with Incomplete and Uncertain Information. Control and Decision, 2007, 22(4): 394-398. [9]Xu X H, Xia Y. Conflict-oriented Interval Fuzzy Multi-criteria Group Decision-Making Method and Its Application in Investment Decision-Making. Journal of University of Electronic Science and Technology of China (Social Sciences Edition), 2021, 23(3): 24-30. [10]Zhang H J, Wang F, Dong Q X. Research Progress and Prospect of Group Consensus Decision-Making. Journal of University of Electronic Science and Technology of China (Social Sciences Edition), 2021, 23(2): 26-37. [11]Li J, Zhang P Z, Jiang Y Z. Automatic Visual Clustering of Discussion Topics in Group Decision Support Systems. Journal of Systems & Management, 2009, 18(3): 325-331. [12]Xu X H, Yin X P, Zhong X Y, et al. A Review of Large-Scale Group Decision-Making Theories and Methods: Problems and Challenges. Information and Control, 2021, 50(1): 54-64. [13]Xiong C Q, Li D H. Consensus Achievement Model and Its Implementation in the Hall for Workshop of Metasynthetic Engineering. Computer Integrated Manufacturing Systems, 2008, 14(10): 1913-1918. [14]Wang D L, Dai R W. Research on the Convergence of Expert Group Thinking. Journal of Management Sciences in China, 2002, 5(2): 1-5.