Abstract
Airline network, including airports as network nodes and flight routes as directed network edges, has a lot of special features such as departure and arrival times, air ticket budget, flight capacity, transportation cost, etc. Thus, analyzing network behavior and service performance for such a network is much more difficult than that for many other networks. In this paper, taking China domestic airline network as a representative, we try to discuss the reachability issue for each airport respectively, which could reflect its regional connectivity level and service quality of civil aviation. More specifically, we evaluate reachability through many features including node degree, betweenness, closeness, etc. To get the values of some features, we design a fast Dijkstra-based all-pair shortest path algorithm with both time and budget requirements, then use Fenwick Tree to further improve the time efficiency. Finally, we implement Analytic Hierarchy Process (AHP) to convert the reachability feature into numerical values for all airports to measure their service qualities precisely. Our results for China domestic airline network with 210 airports and 69,160 flight routes will definitely become a guide to airline companies and civil aviation administration for their further development and management.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Barros, C.P., Peypoch, N.: An evaluation of European airlines’s operational performance. Int. J. Prod. Econ. 122(2), 525–533 (2009)
Bowen, B.D., Headley, D.E.: Evaluation of the US airline industry: the airline quality rating 2012 (2013)
Brandes, U.: A faster algorithm for betweenness centrality. J. Math. Sociol. 25(2), 163–177 (2001)
Dijkstra, E.W.: A note on two problems in connexion with graphs. Numerische Mathematik 1(1), 269–271 (1959)
Fenwick, P.M.: A new data structure for cumulative frequency tables. Softw. Pract. Experience 24(3), 327–336 (1994)
Fredman, M.L., Tarjan, R.E.: Fibonacci heaps and their uses in improved network optimization algorithms. J. ACM (JACM) 34(3), 596–615 (1987)
Freeman, L.C.: A set of measures of centrality based on betweenness. Sociometry 40, 35–41 (1977)
Freeman, L.C.: Centrality in social networks conceptual clarification. Soc. Netw. 1(3), 215–239 (1978)
Guimera, R., Amaral, L.A.N.: Modeling the world-wide airport network. Eur. Phys. J. B-Condens. Matter Complex Syst. 38(2), 381–385 (2004)
Kourtellis, N., Alahakoon, T., Simha, R., Iamnitchi, A., Tripathi, R.: Identifying high betweenness centrality nodes in large social networks. Soc. Netw. Anal. Min. 3(4), 899–914 (2013)
Lee, S.H., Choi, J.Y., Yoo, S.H., Oh, Y.G.: Evaluating spatial centrality for integrated tourism management in rural areas using GIS and network analysis. Tourism Manag. 34, 14–24 (2013)
Sabidussi, G.: The centrality index of a graph. Psychometrika 31(4), 581–603 (1966)
Tsaur, S.H., Chang, T.Y., Yen, C.H.: The evaluation of airline service quality by fuzzy MCDM. Tourism Manag. 23(2), 107–115 (2002)
Watts, D.J., Strogatz, S.H.: Collective dynamics of small-world networks. Nature 393(6684), 440–442 (1998)
Yu, M.M.: Assessment of airport performance using the SBM-NDEA model. Omega 38(6), 440–452 (2010)
Acknowledgement
This work has been supported in part by the China 973 project (2014CB340303), the National Natural Science Foundation of China (No. 61571441, 61672353, 61472252, 61133006), and the Opening Project of Key Lab of Information Network Security of Ministry of Public Security (The Third Research Institute of Ministry of Public Security) Grant number C15602.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing AG
About this paper
Cite this paper
You, X., Gao, X., Dang, Y., Chen, G., Wang, X. (2016). A Comprehensive Reachability Evaluation for Airline Networks with Multi-constraints. In: Chan, TH., Li, M., Wang, L. (eds) Combinatorial Optimization and Applications. COCOA 2016. Lecture Notes in Computer Science(), vol 10043. Springer, Cham. https://doi.org/10.1007/978-3-319-48749-6_3
Download citation
DOI: https://doi.org/10.1007/978-3-319-48749-6_3
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-48748-9
Online ISBN: 978-3-319-48749-6
eBook Packages: Computer ScienceComputer Science (R0)