Multiairport capacity management: genetic algorithm with receding horizon
journal contributionposted on 17.11.2008 by Xiao-Bing Hu, Wen-Hua Chen, Ezequiel A. Di Paolo
Any type of content formally published in an academic journal, usually following a peer-review process.
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.
- Aeronautical, Automotive, Chemical and Materials Engineering
- Aeronautical and Automotive Engineering