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Multiairport capacity management: genetic algorithm with receding horizon

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posted on 17.11.2008 by Xiao-Bing Hu, Wen-Hua Chen, Ezequiel A. Di Paolo
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.

History

School

  • Aeronautical, Automotive, Chemical and Materials Engineering

Department

  • Aeronautical and Automotive Engineering

Citation

HU, X-B., CHEN, W-H. and DI PAOLO, E.A., 2007. Multiairport capacity management: genetic algorithm with receding horizon. IEEE transactions on intelligent transportation systems. 8(2), pp. 254-263.

Publisher

© IEEE

Publication date

2007

Notes

This is a journal article. It was published in the journal, IEEE Transactions on Intelligent Transportation Systems [© IEEE]and is also available at: http://ieeexplore.ieee.org. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

ISSN

1524-9050

Language

en

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