Fleet management applications are used for vehicle tracking purposes and mechanic diagnostic purposes to troubleshoot vehicle problems. As well as fleet management used in vehicle maintenance, improving vehicle and driver performance, speed control, fuel management, and many other different areas in transport businesses to improve business operation in different aspects. The usage of fleet management systems improves fleet productivity and efficiency, reduces transportation costs, and minimizes vehicle investment risk. For businesses like cash in transit, fleet systems are used to monitor their operations and also to ensure secure transport. This research proposes a systematic procedure to the Cash-In-Transit (CIT) division of a transportation company to develop an automated system for the allocation of vehicles and drivers for their daily operations. The division receives CIT job requests from customer locations of different geographical areas. Based on daily job requirements, routes for vehicle operations are identified, and resources for each route are allocated by considering different factors such as productivity, cost reduction, secure transport, condition of the vehicle, the distance of the task locations, and the number of jobs that can be covered in one route within a day, vehicle availability, and profit. Since the CIT operating unit uses both company-owned vehicles and hired vehicles for their operations, there should be a scientific process to assign both company-owned and hired vehicles profitably. The proposed solution aims to overcome the issues and unjustified matters identified in the current manual process and reduce the complexity in the allocation method.


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    Titel :

    Automated Fleet Management System for CIT Operations


    Beteiligte:

    Erscheinungsdatum :

    19.05.2021


    Anmerkungen:

    oai:zenodo.org:4772637
    Journal of Advancement in Software Engineering and Testing 4(1) 1-7



    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Klassifikation :

    DDC:    629




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