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Multiairport Capacity Management: Genetic Algorithm With Receding Horizon

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3 Author(s)
Xiao-Bing Hu ; Dept. of Informatics, Sussex Univ., Brighton ; Wen-Hua Chen ; Di Paolo, E.

The inability of airport capacity to meet the growing air traffic demand is a major cause of congestion and costly delays. Airport capacity management (ACM) in a dynamic environment is crucial for the optimal operation of an airport. This paper reports on a novel method to attack this dynamic problem by integrating the concept of receding horizon control (RHC) into a genetic algorithm (GA). A mathematical model is set up for the dynamic ACM problem in a multiairport system where flights can be redirected between airports. A GA is then designed from an RHC point of view. Special attention is paid on how to choose those parameters related to the receding horizon and terminal penalty. A simulation study shows that the new RHC-based GA proposed in this paper is effective and efficient to solve the ACM problem in a dynamic multiairport environment

Published in:

Intelligent Transportation Systems, IEEE Transactions on  (Volume:8 ,  Issue: 2 )

Date of Publication:

June 2007

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