Highlights We present a new mixed integer linear programming formulation of the rolling stock scheduling problem. We develop an exact solution approach using Branch-and-Price methodology. A computational study based on a real-life case study from the Danish state Railways.

    Abstract How to best reschedule their fleet of rolling stock units during a disruption is an optimization problem regularly faced by railway operators. Despite the problem’s high complexity, it is still usually solved manually. In this paper we propose a path based mathematical formulation and solve it using a Branch-and-Price algorithm. We demonstrate that, unlike flow based approaches, our formulation is more easily extended to handle certain families of constraints, such as train unit maintenance restrictions. The proposed algorithm is benchmarked on several real-life instances provided by the suburban railway operator in Copenhagen, DSB S-tog. When used in combination with a lower bound method taken from the literature we show that near-optimal solutions to this rescheduling problem can be found within a few seconds. Furthermore, we show that the proposed methodology can be used, with minor modification, on a tactical planning level, where it produces near-optimal rolling stock schedules in minutes of CPU time.


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    Title :

    A Branch-and-Price algorithm for railway rolling stock rescheduling


    Contributors:


    Publication date :

    2017-03-08


    Size :

    23 pages




    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English





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