The increasing demand for air travel combined with uncertainties has put additional strain on airport infrastructure and ground handling resources. To improve the efficiency of airport operations, in this paper, We firstly perform an in-depth analysis of the A-SMGCS dataset for Singapore Changi Airport, and then propose taxiing routing solutions for both landing and departure aircraft with involved departure uncertainty, formulating the problem as a mixed-integer quadratic programming (MIQP) problem. The proposed model considers the waypoint- based conflict checking, as well as incorporates anti-overtaking constraints, and head-on constraints exclusive for bidirected graph, aiming to minimize the taxiing time as well as the gap with the scheduled in-block time for landing aircraft and scheduled take-off time for departure aircraft. The presence of departure uncertainty prompts us to build a stochastic model, where constraints with stochastic variables are converted into corresponding chance constraints under designated confidence levels. Incorporating stochastic factors enhances the resilience and dependability of our solution. To evaluate the efficiency of our proposed method, we have elaborately investigated the computational complexity under various test scales, and analyzed how changes in uncertainty and confidence levels impact routing and scheduling solutions on a simplified Singapore Changi Airport network, which could provide significant reference for other work.


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    Titel :

    Joint Arrival-Departure Taxiway Scheduling Considering Departure Uncertainty


    Beteiligte:
    Zhang, Yi (Autor:in) / Zhang, Yicheng (Autor:in) / Zhang, Sheng (Autor:in) / Huang, Liping (Autor:in) / Yin, Yifang (Autor:in)


    Erscheinungsdatum :

    2023-09-24


    Format / Umfang :

    567621 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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