Abstract Metro lines of some mega cities usually suffer from extreme congestions in peak hours, leading to serious operation risks. To relieve the extreme saturation for overcrowded metro lines, this study explores a novel train operation strategy, i.e., flexibly allocating the capacities through reserving carriages at different stations according to the time-variant passenger demand. With this strategy, the train capacities are reasonably distributed to each station, especially for stations with large passenger flows, so as to balance the passenger accumulation over the whole line. A nonlinear integer programming model is developed by considering the passenger dynamics, and an efficient variable neighborhood search (VNS) algorithm is developed to solve the problem of interest. Finally, a set of numerical experiments with real-world data from Beijing metro Batong line are conducted to verify the performance and effectiveness of the proposed model and algorithm. The experimental results show that our proposed approach can effectively obtain high-quality carriage reservation plans in a short computing time, and the generated plans can well balance the passenger accumulation at all involved stations.

    Highlights We flexibly allocate capacities through reserving and releasing carriages in each service-train. We formulate a nonlinear integer programming model to optimize the problem of interest. We design an effective variable neighborhood search algorithm to solve the problem. We present numerical experiments to quantify the potential benefits of our methodology.


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    Titel :

    Flexible train capacity allocation for an overcrowded metro line: A new passenger flow control approach


    Beteiligte:
    Shi, Jungang (Autor:in) / Qin, Tan (Autor:in) / Yang, Lixing (Autor:in) / Xiao, Xiaofang (Autor:in) / Guo, Junhua (Autor:in) / Shen, Yong (Autor:in) / Zhou, Housheng (Autor:in)


    Erscheinungsdatum :

    2022-04-05




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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