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A Simulated Annealing Heuristic Approach for the Energy Minimizing Electric Vehicle Routing Problem with Drones

In: Disruptive Technologies and Optimization Towards Industry 4.0 Logistics

Author

Listed:
  • Nikolaos A. Kyriakakis

    (Technical University of Crete)

  • Themistoklis Stamadianos

    (Technical University of Crete)

  • Magdalene Marinaki

    (Technical University of Crete)

  • Yannis Marinakis

    (Technical University of Crete)

Abstract

The Electric Vehicle Routing Problem with Drones (EVRPD) is a recently proposed VRP that combines two state-of-the-art means of transportation, electric ground vehicles (EVs) and drones, intending to minimize total energy consumption. The payload weight is considered the element that has the greatest impact on the energy consumption rate. The EVRPD assumes packages of different weight classes. The EVs serve as mobile depots, from which drones are deployed to deliver the packages. Both vehicle types have quantity, weight, and energy limitations. The Simulated Annealing heuristic of this research follows a population-based approach, which utilizes neighborhood operators to evolve the solutions. Three different temperature decaying strategies are tested on the EVRPD benchmark instances found in the literature, and their computational results are compared and discussed.

Suggested Citation

  • Nikolaos A. Kyriakakis & Themistoklis Stamadianos & Magdalene Marinaki & Yannis Marinakis, 2024. "A Simulated Annealing Heuristic Approach for the Energy Minimizing Electric Vehicle Routing Problem with Drones," Springer Optimization and Its Applications, in: Athanasia Karakitsiou & Athanasios Migdalas & Panos M. Pardalos (ed.), Disruptive Technologies and Optimization Towards Industry 4.0 Logistics, pages 227-246, Springer.
  • Handle: RePEc:spr:spochp:978-3-031-58919-5_8
    DOI: 10.1007/978-3-031-58919-5_8
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