DocumentCode :
69815
Title :
Algebraic Connectivity Maximization for Air Transportation Networks
Author :
Peng Wei ; Spiers, Gregoire ; Dengfeng Sun
Author_Institution :
Oper. Res. & Adv. Analytics, American Airlines, Fort Worth, TX, USA
Volume :
15
Issue :
2
fYear :
2014
fDate :
Apr-14
Firstpage :
685
Lastpage :
698
Abstract :
It is necessary to design a robust air transportation network. An experiment based on the real air transportation network is performed to show that algebraic connectivity is a fair measure for network robustness under random failures. Therefor, the goal of this paper is to maximize algebraic connectivity. Some researchers solve the maximization of the algebraic connectivity by choosing the weights for the edges in the graph. Others focus on the best way to add edges in a network in order to optimize the connectivity. In this paper, the authors formulate a new air transportation network model and show that the corresponding algebraic connectivity optimization problem is interesting because the two subproblems of adding edges and choosing edge weights cannot be treated separately. The new problem is formulated and exactly solved in a small air transportation network case. The authors also propose the approximation algorithm in order to achieve better efficiency. For large networks, the semidefinite programming with cluster decomposition is first presented. Moreover, the algebraic connectivity maximization for directed networks is discussed. Simulations are performed for a small-scale case, large-scale problem, and directed network problem.
Keywords :
air traffic; graph theory; optimisation; transportation; air transportation networks; algebraic connectivity maximization; algebraic connectivity optimization problem; approximation algorithm; cluster decomposition; directed network problem; directed networks; edge weights; fair measure; graph; large-scale problem; network robustness; random failures; robust air transportation network model; semidefinite programming; Aircraft; Airports; Fuels; Measurement; Meteorology; Robustness; Air transportation; large-scale systems; optimization methods;
fLanguage :
English
Journal_Title :
Intelligent Transportation Systems, IEEE Transactions on
Publisher :
ieee
ISSN :
1524-9050
Type :
jour
DOI :
10.1109/TITS.2013.2284913
Filename :
6648670
Link To Document :
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