吉林大学学报(理学版) ›› 2026, Vol. 64 ›› Issue (1): 93-0103.

• • 上一篇    下一篇

 基于多路网络结构检测的群体共识决策方法

凌子健, 杨有龙, 黄安   

  1. 西安电子科技大学 数学与统计学院, 西安 710126
  • 收稿日期:2024-11-23 出版日期:2026-01-26 发布日期:2026-01-26
  • 通讯作者: 杨有龙 E-mail:ylyang@mail.xidian.edu.cn

Group Consensus Decision-Making Method Based on Multilayer Network Structure Detection

LING Zijian, YANG Youlong, HUANG An   

  1. School of Mathematics and Statistics, Xidian University, Xi’an 710126, China
  • Received:2024-11-23 Online:2026-01-26 Published:2026-01-26

摘要: 针对大规模群体决策中多层关系利用不足导致的质量和效率问题, 提出一种基于多路网络结构检测的群体共识决策方法. 该方法通过将决策者多层关系建模为可区分耦合组织, 开发交互式重启随机游走算法映射意见传播, 检测社区结构和影响力分布, 并采用近邻近似增量计算优化检测效率. 算例与仿真结果验证了其能强化强影响力决策者的主导作用、 降低冲突, 实现高共识与高效计算的平衡, 为复杂耦合环境下群体决策提供有效途径.

关键词: 群体决策, 社会网络分析, 多路网络框架, 结构检测

Abstract: Aiming at the quality and efficiency problems caused by insufficient utilization of multilayer relations in large-scale group decision-making, we proposed  a group consensus decision-making method based on multilayer network structure detection. The method  modelled multilayer relations of decision-makers as distinguishable coupled organizations, developed  an interactive restart random walk algorithm to map opinion propagation, detected community structure and influence distribution, and optimized detection efficiency by using nearest neighbor approximation incremental computing. The calculation  examples and simulation results verify that it can strengthen the leading role of decision-makers with strong influence, reduce conflicts, achieve the balance between high consensus and efficient computing, and provide an effective approach for group decision-making in complex coupled environments.

Key words:  , group decision-making, social network analysis, multilayer network framework, structure detection

中图分类号: 

  • TP391