This paper describes a model for the US air transportation network employing the multitier evolution concept. In an attempt to concisely represent the dynamics behind the complex network structure, a network is decomposed into multiple tiers. The primary tier is for a network of major hub airports whereas the secondary tier is for non-hub airports. A network evolution algorithm is utilized for modeling the primary tier. The main idea in primary tier is considering chronological and spatial network evolution. The secondary tier engages an access algorithm for tier switching and a shortest-path-finding algorithm for multi-stop routings. These algorithms find the shortest route combinations. The outcomes from these processes are combined together and the complete air transportation network topology is created. Given the simplicity of the algorithms, the overall result adequately agrees to the historical data. Finally, in order to figure out the impact on the network from other transportation technologies, ondemand aviation service is applied for a case study and how it affects established network properties is analyzed.
[1]
Richard Bellman,et al.
ON A ROUTING PROBLEM
,
1958
.
[2]
Andreas T. Ernst,et al.
Hub Arc Location Problems: Part I - Introduction and Results
,
2005,
Manag. Sci..
[3]
F. CampbellJ.,et al.
Hub Arc Location Problems
,
2005
.
[4]
Dimitri N. Mavris,et al.
Demand-centric Analysis of the Air Transportation System
,
2008
.
[5]
Jitesh H. Panchal,et al.
Modeling Airline Decisions on Route Planning Using Discrete Choice Models
,
2015
.
[6]
Dimitri N. Mavris,et al.
Aviation Demand Forecasts through Validation of an Agent- Based Multimodal Transportation Model
,
2011
.
[7]
David Levinson,et al.
Topological Evolution of Surface Transportation Networks
,
2007,
Comput. Environ. Urban Syst..
[8]
Eunsuk Yang,et al.
A design methodology for evolutionary air transportation networks
,
2009
.
[9]
Edsger W. Dijkstra,et al.
A note on two problems in connexion with graphs
,
1959,
Numerische Mathematik.