The operation of an airport is a very complex task involving many actors. The primary mission of airport management is to provide sufficient capacity and the best working conditions to all airlines, ground handling, and service provider companies. Flight gate assignment is one of the essential planning problems airport management needs to address, assigning incoming aircraft to the available gates or stands while satisfying operational constraints. Generally, flight arrivals and departures are considered deterministic, and various operational research methods have been applied to solve this combinatorial problem. However, in real-life scenarios, deterministic solutions are generally infeasible because arrival and departure times are uncertain. It is crucial to deal with these uncertainties to create a robust schedule. In this study, we develop a Reinforcement Learning (RL) algorithm to solve the flight gate assignment problem since it is a sequential decision-making method and allows adaptive solutions to address urgent and frequent changes.


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    Titel :

    Flight Gate Assignment Problem with Reinforcement Learning


    Weitere Titelangaben:

    Lect. Notes in Networks, Syst.


    Beteiligte:
    Kahraman, Cengiz (Herausgeber:in) / Sari, Irem Ucal (Herausgeber:in) / Oztaysi, Basar (Herausgeber:in) / Cebi, Selcuk (Herausgeber:in) / Cevik Onar, Sezi (Herausgeber:in) / Tolga, A. Çağrı (Herausgeber:in) / Muhafız Yıldız, Müge (Autor:in) / Avcı, Umut (Autor:in) / Örnek, Mustafa Arslan (Autor:in) / Öztürk, Cemalettin (Autor:in)

    Kongress:

    International Conference on Intelligent and Fuzzy Systems ; 2023 ; Istanbul, Türkiye August 22, 2023 - August 24, 2023



    Erscheinungsdatum :

    17.08.2023


    Format / Umfang :

    8 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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