Railway organizations are currently engaged in the pursuit of digitalizing rail freight transportation to optimize resource utilization and increase revenue. The use of IoT technology combined with real-time information enables train management systems to provide accurate GPS data. However, freight transport operators frequently encounter the challenge of rescheduling freight trains in real-time without the aid of a decision-making system. To overcome this obstacle, an IoT-based real-time rake schedular-reschedular heuristic has been developed. Computational studies have demonstrated that this heuristic is both efficient in terms of runtime and produces high-quality solutions. The implementation of this approach would enable freight transport operators to optimize their business operations, increase their monthly revenue, and re-schedule their rakes efficiently.


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    Titel :

    Efficient Decision-Making for Rail Freight Operators: A Real-Time IoT-Based Approach for Rake Rescheduling


    Beteiligte:
    Kumar, Gaurav (Autor:in) / Kumar, Akhilesh (Autor:in)


    Erscheinungsdatum :

    2023-12-18


    Format / Umfang :

    658577 byte




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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