Abstract
In order to improve the reliability of aviation airline network, this paper presents an empirical analysis on the airline network structure of an aviation company in China from the perspective of complex network, and the calculation result of the statistical features and degree distribution of the network, proves that the network is a small-world network and a scale-free network. Four indicators, i.e. degree, closeness, vertex betweenness and flow betweenness, are utilized for aviation network centralization so as to distinguish the most appropriate method. The influence of nodes in local network is to be measured through the indicators. The results show that vertex betweenness can achieve the best aviation network centralization effect. Specifically, the centrality degree reaches 95.87%. On this basis, the network reliability is analyzed to discover that when two nodes with maximum degree or maximum betweenness are removed, the network performance is reduced by a half. Eventually, countermeasures are proposed for further improvement according to the results. In other words, complex network method is feasible used to analyze the topological structure and statistical features of aviation network. Based on this, a study is conduced to the network reliability and suggestions are proposed for optimizing the aviation network.
Highlights
Aviation network refers to an airline system constituted by airlines connected in a certain way in a district, serving as a basis for the production and development of the airline company
Most studies (Barrat et al, 2005) focus on the analysis on physical statistical features of aviation network structure and the evolution of overall topological structure, while only a few studies are made on the analysis of route network with social network methods (Porta et al, 2006)
Complex network theory is applied, an aviation network structure model is built for China Southern Airlines (CSA), and its structure is analyzed
Summary
Aviation network refers to an airline system constituted by airlines connected in a certain way in a district, serving as a basis for the production and development of the airline company. In the complex network theory (Newman, 2003), the indicators reflecting the statistical features of network structure are mainly degree of nodes, average degree, average path length, density, clustering coefficient, etc. Airport nodes in the aviation network of CSA are sorted according to the degree and the betweenness value in descending order, and the airport based on a relatively big degree and that, based on a relatively big betweenness, are removed orderly, the average path length, the clustering coefficient, and the network efficiency of the network are calculated respectively, and changes of the average path length, the clustering coefficient and the network efficiency corresponding to the decrease of the airport number are counted and compared, the contents indicated in Fig., Fig. 5 and Table 5 are respectively obtained.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
