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Abstract

flight routing and scheduling model is under development that predicts airline routing and scheduling under airport capacity constraints. It consists of several components describing different aspects of the air transport system, including passenger demand, airline competition, flight delay, and airline cost. These models are integrated into a flight routing and scheduling model in which an objective function is defined to maximize airline system profit within a routing network, subject to constraints. This framework allows the relationships between fares, passenger demand, infrastructure capacity constraints, flight delays, flight frequencies, and routing network to be simulated. In this paper the integrated flight routing and scheduling model is first applied to a series of simple theoretical routing networks to illustrate its capabilities. With increasing airport capacity constraints the results show an increase in average fares, a decrease in O-D passenger demand, and a shift in flight routing away from the most constrained airports. The model is then applied to a network of airports in the United States with 2005 population, income and airport capacity inputs. With further development the model is to be applied to forecasting air traffic system growth, including network and schedule changes resulting from increasing delays, in the Aviation Integrated Modelling (AIM) project under development at the University of Cambridge. Copyright © 2008 by Antony D. Evans, Andreas Schafer, and Lynnette Dray.


Original document

The different versions of the original document can be found in:

http://dx.doi.org/10.2514/6.2008-8855
http://bullfinch.arct.cam.ac.uk/Documents/ATIO2008_RoutingScheduling.pdf,
http://old-www.arct.cam.ac.uk/Documents/ATIO2008_RoutingScheduling.pdf,
http://discovery.ucl.ac.uk/1368162,
https://www.researchgate.net/profile/Antony_Evans3/publication/242309771_Modelling_Airline_Network_Routing_and_Scheduling_under_Airport_Capacity_Constraints/links/555f9db708ae6f4dcc9271a4.pdf?disableCoverPage=true,
https://academic.microsoft.com/#/detail/2017425815
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Document information

Published on 01/01/2008

Volume 2008, 2008
DOI: 10.2514/6.2008-8855
Licence: CC BY-NC-SA license

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