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Bi-Level Fleet Dispatching Strategy for Battery-Electric Trucks: A Real-World Case Study

Author

Listed:
  • Dongbo Peng

    (Department of Electric and Computer Engineering, University of California Riverside, Riverside, CA 92521, USA)

  • Zhouqiao Zhao

    (Department of Electric and Computer Engineering, University of California Riverside, Riverside, CA 92521, USA)

  • Guoyuan Wu

    (Center for Environmental Research & Technology, University of California Riverside, Riverside, CA 92507, USA)

  • Kanok Boriboonsomsin

    (Center for Environmental Research & Technology, University of California Riverside, Riverside, CA 92507, USA)

Abstract

Driven by new regulations concerning greenhouse gas (GHG) emissions in the transportation sector, battery-electric trucks (BETs) are considered one of the sustainable freight transportation solutions. In this paper, a dispatching problem of the BET fleet is formulated as a capacitated electric vehicle routing problem (VRP) with pick-up and delivery. As the BET dispatching problem is NP-hard, the performance of existing approaches deteriorates in large instance problems, especially when the customers have different preferences and constraints. This article proposes a bi-level strategy that incorporates routing zone partitioning and metaheuristic-based vehicle routing to solve the large-scale BET dispatching problem, considering the delivery types, limited travel distances, and cargo payloads. We apply this strategy to a real-world fleet dispatching scenario with around 300 customer positions for pickups and drop-offs. The experimental results demonstrate that the proposed bi-level strategy can reduce total travel distance and travel time by 24–31%, compared to the baseline strategy implemented in the real world.

Suggested Citation

  • Dongbo Peng & Zhouqiao Zhao & Guoyuan Wu & Kanok Boriboonsomsin, 2023. "Bi-Level Fleet Dispatching Strategy for Battery-Electric Trucks: A Real-World Case Study," Sustainability, MDPI, vol. 15(2), pages 1-15, January.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:2:p:925-:d:1024878
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    References listed on IDEAS

    as
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