A two-stage stochastic programming algorithm based on particle swarm optimization is proposed for an optimal and robust design in the aircraft sequencing and scheduling problem. The first and second stage decision problems are defined as aircraft sequencing and scheduling, respectively, and the uncertainties that arise from the aircraft flight time between two successive fixes are considered. Particle swarm optimization is utilized for a randomized search to make the first stage decision under incomplete information about uncertain parameters. In addition, the random key representation is adopted to apply particle swarm optimization to a discrete aircraft sequencing problem. Then, the second stage decision is made using mixed integer linear programming after the realization of the uncertain parameters. The performance of the proposed algorithm is verified by numerical simulations.


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    Titel :

    Two-Stage Stochastic Programming Based on Particle Swarm Optimization for Aircraft Sequencing and Scheduling


    Beteiligte:
    Hong, Youkyung (Autor:in) / Choi, Byunghun (Autor:in) / Kim, Youdan (Autor:in)


    Erscheinungsdatum :

    01.04.2019


    Format / Umfang :

    2785937 byte




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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