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Multi-round minimum cost consensus model with objectivity-fairness driven feedback mechanism
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AI
DOI：10.1016/j.inffus.2023.102185.png)
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摘要
En 中文
In traditional group decision-making (GDM) and consensus reaching process (CRP), it may raise the issue of fairness for the moderator to subjectively assign each decision-maker's (DM's) weight and unit cost, and it is sometimes difficult to reach consensus with only one round of the CRP. In this paper, the impact of the aforementioned situations on the consensus is first analyzed, and then two specific improvement methods are accordingly provided. Based on which, the definitions of DM's closeness centrality, affiliated subgroup as well as individual consensus level are given, and some incentives and penalties regarding DM's weight and unit cost are used during the CRP, so as to improve the applicability and operability of the minimum cost consensus (MCC) in practical GDM problems while ensuring the fairness among DMs and the objectivity of data. Moreover, the single-round MCC is extended into the multi-round MCC by virtue of designing iterative methods on DM's opinion, weight and unit cost, building the multi-round minimum cost consensus model (MRMCCM) with objectivity-fairness driven feedback mechanism, and presenting a detailed procedure alongside its algorithm of the multi-round CRP. Finally, a comprehensive evaluation case of financial product under the multi-round consensus validates the effectiveness and practicality of the new proposal, while its comparative analysis with other consensus models shows that the MRMCCM and the CRP with feedback mechanism help motivate DMs to reach higher-quality consensus at lower cost.
Keyword:
Group decision-making
Consensus reaching process
Multi-round minimum cost consensus model
Feedback mechanism
Objectivity and fairness
期刊
IF:
15.5
论文数:
4.3K
被引数:
2.7W
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