Aircraft sequencing and scheduling are significant operations for air traffic controllers and pilots. This study presents a mixed-integer linear programming model to minimize the average delay per aircraft for the single and mixed operations runway. Due to the complexity of the problem, the genetic algorithm, tabu search, and simulated annealing algorithms were applied to solve this problem. In addition, the results of the three different meta-heuristic algorithms were compared with the first-come first-served approach and each other. The results demonstrated that all algorithms could noticeably decrease the average delay per aircraft compared to the first-come first-served approach.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Meta-Heuristic Algorithms for Aircraft Sequencing and Scheduling Problem


    Weitere Titelangaben:

    Sustainable aviat.


    Beteiligte:
    Karakoc, T. Hikmet (Herausgeber:in) / Colpan, Can Ozgur (Herausgeber:in) / Dalkiran, Alper (Herausgeber:in) / Cecen, Ramazan Kursat (Autor:in) / Durmazkeser, Yunus (Autor:in)

    Erschienen in:

    Progress in Sustainable Aviation ; Kapitel : 6 ; 107-118


    Erscheinungsdatum :

    26.11.2022


    Format / Umfang :

    12 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    A heuristic algorithm for aircraft landing scheduling problem

    Guliashki, Vassil / Music, Gasper / Marinova, Galia | IEEE | 2023


    An Effective Meta-Heuristic Technique for Solving Train Scheduling Problem

    Khan, M.B. / Fan, W. / Zhang, D. et al. | British Library Conference Proceedings | 2007


    An Effective Meta-Heuristic Technique for Solving Train Scheduling Problem

    Khan, M. B. / Fan, Wangbo / Zhang, Dianye | ASCE | 2007



    Exact and Heuristic Algorithms for Runway Scheduling

    Malik, Waqar A. / Jung, Yoon C. | NTRS | 2016