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An Adaptive Memetic Algorithm for Dynamic Electric Vehicle Routing Problem with Time-Varying Demands

Author

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  • Na Wang
  • Yihao Sun
  • Hongfeng Wang

Abstract

Dynamic electric vehicle routing problem (DEVRP) is an extension of the electric vehicle routing problem (EVRP) into dynamic logistical transportation system such that the demand of customer may change over time. The routing decision of DEVRP must concern with the driving range limitation of electric vehicle (EV) in a dynamic environment since both load degree and battery capacity are variable according to the time-varying demands. This paper proposes an adaptive memetic algorithm, where a special encoding strategy, an adaptive local search operator, and an economical random immigrant scheme are employed in the framework of evolutionary algorithm, to solve DEVRP efficiently. Numeric experiments are carried out upon a series of test instances that are constructed from a stationary VRP benchmark. The computational results show that the proposed algorithm is more effective in finding high-quality solution than several peer algorithms as well as significant in improving the capacity of the routing plan of EVs in dynamic transportation environment.

Suggested Citation

  • Na Wang & Yihao Sun & Hongfeng Wang, 2021. "An Adaptive Memetic Algorithm for Dynamic Electric Vehicle Routing Problem with Time-Varying Demands," Mathematical Problems in Engineering, Hindawi, vol. 2021, pages 1-10, March.
    • Handle: RePEc:hin:jnlmpe:6635749
    DOI: 10.1155/2021/6635749
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    Cited by:

    1. Leandro do C. Martins & Rafael D. Tordecilla & Juliana Castaneda & Angel A. Juan & Javier Faulin, 2021. "Electric Vehicle Routing, Arc Routing, and Team Orienteering Problems in Sustainable Transportation," Energies, MDPI, vol. 14(16), pages 1-30, August.
    2. Xabier A. Martin & Marc Escoto & Antoni Guerrero & Angel A. Juan, 2024. "Battery Management in Electric Vehicle Routing Problems: A Review," Energies, MDPI, vol. 17(5), pages 1-25, February.

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