This paper studies the problem of flight scheduling optimization strategy. According to the published airport capacity, flight connectivity, and so on, the flight scheduling model is established. With the goal of minimizing the adjustment amount and maximizing the number of flights, the optimal scheduling strategy of major airlines is obtained. First, analyze the existing airline scheduling strategy, count the actual capacity of each airport at each time, compare with the saturated capacity of each airport, and find that the actual capacity of multiple airports at multiple times exceeds the saturated capacity. Then, on this basis, the connectivity constraints of the front, back flights are added, and the adjustment time constraints are changed to soft constraints. To maximize the number of scheduled flights, minimize the adjustment time, and minimize the number of flights beyond the adjustment range, this paper establishes a flight adjustment strategy model under the condition of connection. In this paper, the flight optimization problem is solved based on particle swarm optimization and diffusion phenomenon. Combining the degree of flight congestion with the diffusion energy and the degree of airport congestion with the diffusion probability, the dynamic planning of flight scheduling under the constraint of airport capacity is realized.


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    Titel :

    Flight Scheduling Optimization Model and Algorithm


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Jia, Limin (Herausgeber:in) / Ou, Dongxiu (Herausgeber:in) / Liu, Hui (Herausgeber:in) / Zong, Fang (Herausgeber:in) / Wang, Pangwei (Herausgeber:in) / Zhang, Mingfang (Herausgeber:in) / Yang, Le (Autor:in) / Dai, Meize (Autor:in) / Zhang, Huimin (Autor:in) / Yang, Dikai (Autor:in)

    Kongress:

    International Conference on Artificial Intelligence and Autonomous Transportation ; 2024 ; Beijing, China December 06, 2024 - December 08, 2024



    Erscheinungsdatum :

    31.03.2025


    Format / Umfang :

    8 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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