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

With the increasing instability and the participation of more participants in the aviation manufacturing supply chain,the risks faced by the management of the aviation manufacturing supply chain is also increased. For the risk management in the aviation manufacturing supply chain network,the complex...

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Bibliographic Details
Published inHangkong Gongcheng Jinzhan Vol. 14; no. 6; pp. 167 - 177
Main Authors HUANG Hui, LI Ruiqi
Format Journal Article
LanguageChinese
Published Editorial Department of Advances in Aeronautical Science and Engineering 01.12.2023
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Summary:With the increasing instability and the participation of more participants in the aviation manufacturing supply chain,the risks faced by the management of the aviation manufacturing supply chain is also increased. For the risk management in the aviation manufacturing supply chain network,the complex network is taken as a tool to study the identification of key nodes in the supply chain network 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 formation mechanism of the supply chain and dividing the supply chain hierarchy are proposed to construct the aviation manufacturing supply chain complex network and define the indicators. 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 show that the proposed WKC algorithm has scientific principles and 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.
ISSN:1674-8190
DOI:10.16615/j.cnki.1674-8190.2023.06.19