Ride-sharing services, such as those offered by companies like Uber, have gained significant popularity for transporting passengers from one location to another. However, the current model only allows for the provision of a single service at a time. Consequently, if a vehicle is carrying passengers, it cannot simultaneously provide food packet delivery or other services. In this paper, we present an optimized multi-fold service approach, enabling vehicles to carry passengers while also offering additional services like a parcel, medicine box and food packet delivery. To achieve optimal solutions for all four services, we employ a multi-objective algorithm that determines routes balancing and optimizing these services together. Our proposed algorithm provides both analytical and strategic solutions. The analytical solution addresses real-life problems using goal programming, while the strategic solution considers real vehicle situations utilizing set theory concepts. Comparative analysis against other vehicular models demonstrates the superior performance of our proposed model in terms of time and space complexity. Moreover, our model offers a greater number of services compared to the existing system. We evaluate the performance of our model using a randomly self-prepared dataset, and the quick response for each service affirms its potential integration with future vehicles.


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    Titel :

    Optimizing Dynamic Ride Sharing with Multiple Objectives


    Weitere Titelangaben:

    SN COMPUT. SCI.


    Beteiligte:

    Erschienen in:

    Erscheinungsdatum :

    21.10.2023




    Medientyp :

    Aufsatz (Zeitschrift)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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