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


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    Title :

    Multiairport Capacity Management: Genetic Algorithm With Receding Horizon


    Contributors:


    Publication date :

    2007-06-01


    Size :

    332557 byte




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English




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