基于复杂网络的航空制造供应链关键节点识别研究

随着不稳定因素的增加以及航空制造供应链的参与主体增多,航空制造供应链的管理所面临的风险也随之增大。因此针对航空制造供应链网络的风险管理,以复杂网络为工具研究供应链网络中的关键节点识别问题,从而帮助航空供应链提升抗风险能力。通过分析我国航空制造供应链网络现状和特点,提出供应链形成机制并划分供应链层级,对航空制造供应链进行构建及指标界定,对度中心性、介数中心性、接近中心性三种经典中心性算法以及传统K-Shell 分解算法进行加权改进;结合熵值-TOPSIS 法提出一种针对加权网络的供应链关键节点识别算法——WKC 算法,通过构造网络来进行算例分析,验证该种算法的有效性。结果表明：本文提出的WKC 算法原理科学、计算复杂度较低,为航空制造等高端装备制造业供应链的风险管理提供了一定的参考。

Research on key nodes identification of aviation manufacturing supply chain based on complex network

With the increasing instability of the world situation and the participation of more participants in the aviation manufacturing supply chain, the risks faced by the management of the aviation manufacturing supply chain also increase. Therefore, this paper focuses on risk management in the aviation manufacturing supply chain network, using complex networks as a tool to study the identification of key nodes in the supply chain network, in order to help the aviation supply chain improve its risk resistance ability. By analyzing the current situation and characteristics of China"s aviation manufacturing supply chain network, the aviation manufacturing supply chain complex network is constructed and indicators are defined by proposing the formation mechanism of the supply chain and dividing the supply chain hierarchy. Three classical centrality algorithms, namely degree centrality, betweenness centrality and closeness centrality, and the traditional K-Shell method are weighted and improved. And in combination with the entropy-TOPISIS method, a WKC algorithm for identifying the key nodes of the supply chain for the weighted network is proposed. The feasibility and validity of this algorithm are verified by constructing a network to analyze a numerical example. The results indicate that the WKC algorithm proposed in this paper has scientific principles, low computational complexity, and provides a certain reference for risk management in the supply chain of high-end equipment manufacturing industries such as aviation manufacturing.