Negative collaboration risk analysis and control in manufacturing service collaboration based on complex network evolutionary game

被引:0
|
作者
Sun, Hanlin [1 ]
Zhang, Yongping [2 ]
Liu, Bo [2 ]
Sheng, Guojun [3 ]
Cheng, Ying [2 ]
Zuo, Ying [2 ]
Tao, Fei [2 ,4 ]
机构
[1] Beihang Univ, Sino French Engineer Sch, Beijing 100191, Peoples R China
[2] Beihang Univ, Sch Automat Sci & Elect Engn, Beijing 100191, Peoples R China
[3] COSMO Ind Intelligence Res Inst Co Ltd, Qingdao 266426, Peoples R China
[4] Beihang Univ, Int Res Inst Multidisciplinary Sci, Digital Twin Int Res Ctr, Beijing 100191, Peoples R China
基金
中国国家自然科学基金;
关键词
Manufacturing service collaboration; Collaboration behavior; Negative collaboration risk; Risk control;
D O I
10.1016/j.eswa.2024.125545
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In the era of the digital economy, manufacturing service collaboration (MSC) effectively addresses user personalization and customization through networked collaboration among service providers. However, opportunistic negative collaboration behaviors within the network can lead to risk generation, risk propagation and potential dysfunction of the entire collaboration network. Traditional risk control strategies are often based on experience and lack predictive validation. To improve the efficiency of risk control strategy formulation and validate the effectiveness of risk control, the article proposes a negative collaboration risk control optimal strategy exploration method. This method can realize effective optimal decision-making for risk control and effectiveness validation by combining the complex network evolutionary game and Q-learning. The experiment results show that this method is able to formulate situation-specific risk control strategies and keep negative collaboration providers below 10%, effectively controlling MSC risk.
引用
收藏
页数:13
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