Airport declared capacity sets the limits of the number of slots in a Level 3 airport that can be allocated per unit of time. Setting higher level of declared capacity may cause airport congestion and flight delays when the operating capacity is low during adverse weather conditions, while setting lower declared capacity may result in a waste of scarce airport resources if operating capacity is high. Determination of declared capacity facing great uncertainty is critical and yet challenging. However, less work has been done in this area. This paper proposes a data-driven framework for setting declared capacity at a Level 3 airport. First, a K-means based clustering algorithm is developed to obtain the prevalent operating scenarios of the airport. Then, a stochastic model is proposed to determine the number of slots created in each period. We select Guangzhou Baiyun Airport for the case study and obtain the declared capacity with different parameters. This article provides a novel method for determining airport declared capacity, which may further improve slot utilization and reduce flight delays.


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    Titel :

    Robust estimation of airport declared capacity


    Beteiligte:
    Xu, Mengting (Autor:in) / Wang, Mengyin (Autor:in) / Wang, Yanjun (Autor:in) / Delahaye, Daniel (Autor:in)


    Erscheinungsdatum :

    08.10.2022


    Format / Umfang :

    812495 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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