This study addresses the vehicle routing problem with different vehicle types such as drones and trucks, where trucks make a single tour and drones make multiple tours. All vehicle types move independently of each other and leave the depot, serve customers, and return to the depot. While trucks are allowed to go to more than one customer on a single tour, drones are allowed to go to only one customer on a single tour due to their low payload capacities. Truck loading capacity, drone payload capacity, and drone charging capacity were taken into account. Drones are allowed to make multi-tours during one charging period. Some special customers are served only by drones or only by trucks. The problem aims to minimize total tardiness according to the customer's due dates by determining the routes of all vehicle types and customer visit orders. For this purpose, a new mixed integer linear mathematical model (MILP) has been developed. Optimal results were obtained with the MILP model for small data sets containing various combinations of the number of customers and vehicles. The simulation annealing (SA) algorithm was developed in order to find a feasible solution in large data sets in a short time. In this algorithm, swap move-based and two-stage neighborhood search methods are used. While the SA algorithm finds the optimal results found by the MILP model for small data sets, it can also find feasible solutions for large data sets in a very short time.


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    Titel :

    Modified Simulated Annealing Algorithm for Drone and Truck Routing Problem


    Weitere Titelangaben:

    Lect.Notes Mechanical Engineering


    Beteiligte:
    Durakbasa, Numan M. (Herausgeber:in) / Gülen, Kemal Güven (Herausgeber:in) / Aral, İlayda (Autor:in) / Özkan, Onur (Autor:in) / Kizilay, Damla (Autor:in)

    Kongress:

    The International Symposium for Production Research ; 2024 ; Budva, Montenegro October 09, 2024 - October 11, 2024



    Erscheinungsdatum :

    03.05.2025


    Format / Umfang :

    15 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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