Linear uncertain extensions of the minimum cost consensus model based on uncertain distance and consensus utility

被引:42
作者
Guo, Weiwei [1 ,2 ]
Gong, Zaiwu [1 ,2 ]
Xu, Xiaoxia [1 ,2 ,5 ]
Krejcar, Ondrej [3 ,4 ]
Herrera-Viedma, Enrique [5 ,6 ]
机构
[1] Nanjing Univ Informat Sci & Technol, Minist Educ, Sch Management Sci & Engn, Nanjing 210044, Peoples R China
[2] Nanjing Univ Informat Sci & Technol, Collaborat Innovat Ctr Forecast & Evaluat Meteoro, Nanjing 210044, Peoples R China
[3] Univ Hradec Kralove, Fac Informat & Management, Ctr Basic & Appl Res, Hradec Kralove, Czech Republic
[4] Univ Teknol Malaysia, Malaysia Japan Int Inst Technol MJIIT, Kuala Lumpur, Malaysia
[5] Univ Granada, Andalusian Res Inst Data Sci & Computat Intellige, Granada 18071, Spain
[6] Southwestern Univ Finance & Econ, Sch Business Adm, Chengdu 610074, Peoples R China
基金
中国国家自然科学基金;
关键词
Group decision-making; Linear uncertain consensus; Minimum-cost consensus; Consensus utility; Uncertainty theory; GROUP DECISION-MAKING; SOCIAL NETWORK; REACHING PROCESS; MAXIMUM-RETURN; FEEDBACK; ADJUSTMENT; CHALLENGES; MECHANISM; ATTITUDES; SELECTION;
D O I
10.1016/j.inffus.2020.12.002
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Uncertainty theory adopts the belief degree and uncertainty distribution to ensure good alignment with a decision-maker's uncertain preferences, making the final decisions obtained from the consensus-reaching process closer to the actual decision-making scenarios. Under the constraints of the uncertain distance measure and consensus utility, this article explores the minimum-cost consensus model under various linear uncertainty distribution-based preferences. First, the uncertain distance is used to measure the deviation between individual opinions and the consensus through uncertainty distributions. A nonlinear analytical formula is derived to avoid the computational complexity of integral and piecewise function operations, thus reducing the calculation cost of the uncertain distance measure. The consensus utility function defined in this article characterizes the adjustment value and degree of aggregation of individual opinions. Three new consensus models are constructed based on the consensus utility and linear uncertainty distribution. The results show that, in complex group decision-making contexts, the uncertain consensus models are more flexible than traditional minimum-cost consensus models: compared with the high volatility of the adjusted opinions in traditional deterministic consensus models with crisp number-based preferences, the variation trends of both individual adjusted opinions and the collective opinion with a linear uncertainty distribution are much smoother and the fitting range is closer to reality. The introduction of the consensus utility not only reflects the relative changes of individual opinions, but also accounts for individual psychological changes during the opinion-adjustment process. Most importantly, it reduces the cost per unit of consensus utility, facilitates the determination of the optimal threshold for the consensus utility, and improves the efficiency of resource allocation.
引用
收藏
页码:12 / 26
页数:15
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