Highlights We propose an event-driven train scheduling model for an urban rail transit network. Passenger demands, transfers, and passenger flow splitting are considered. The obtained non-fixed headway train schedules have a better performance.

    Abstract This paper considers the train scheduling problem for an urban rail transit network. We propose an event-driven model that involves three types of events, i.e., departure events, arrival events, and passenger arrival rates change events. The routing of the arriving passengers at transfer stations is also included in the train scheduling model. Moreover, the passenger transfer behavior (i.e., walking times and transfer times of passengers) is also taken into account in the model formulation. The resulting optimization problem is a real-valued nonlinear nonconvex problem. Nonlinear programming approaches (e.g., sequential quadratic programming) and evolutionary algorithms (e.g., genetic algorithms) can be used to solve this train scheduling problem. The effectiveness of the event-driven model is evaluated through a case study.


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    Title :

    Passenger-demands-oriented train scheduling for an urban rail transit network


    Contributors:


    Publication date :

    2015-07-16


    Size :

    23 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English






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