HighlightsWe propose a methodology for delivering non-discriminatory train dispatching solutions.We formulate the non-discriminatory train dispatching problem as mixed integer linear programming models.We formalize equity of train delays by soft objective function or hard constraints.Our methodology provides support for managing railway traffic in a non-discriminatory manner.

    AbstractTrain dispatching is vital for the punctuality of train services, which is critical for a train operating company (TOC) to maintain its competitiveness. Due to the introduction of competition in the railway transport market, the issue of discrimination is attracting more and more attention. This paper focuses on delivering non-discriminatory train dispatching solutions while multiple TOCs are competing in a rail transport market, and investigating impacting factors of the inequity of train dispatching solutions. A mixed integer linear programming (MILP) model is first proposed, in which the inequity of competitors (i.e., trains and TOCs) is formalized by a set of constraints. In order to provide a more flexible framework, a model is further reformulated where the inequity of competitors is formalized as the maximum individual deviation of competitors’ delay cost from average delay cost in the objective function. Complex infrastructure capacity constraints are considered and modelled through a big M-based approach. The proposed models are solved by a standard MILP solver. A set of comprehensive experiments is conducted on a real-world dataset adapted from the Dutch railway network to test the efficiency, effectiveness, and applicability of the proposed models, as well as determine the trade-off between train delays and delay equity.


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    Titel :

    Non-discriminatory train dispatching in a rail transport market with multiple competing and collaborative train operating companies


    Beteiligte:
    Luan, Xiaojie (Autor:in) / Corman, Francesco (Autor:in) / Meng, Lingyun (Autor:in)


    Erscheinungsdatum :

    2017-04-20


    Format / Umfang :

    27 pages




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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