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Goods Delivery with Electric Vehicles: Electric Vehicle Routing Optimization with Time Windows and Partial or Full Recharge

Author

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  • Tomislav Erdelić

    (Faculty of Transport and Traffic Sciences, University of Zagreb, Vukelićeva 4, 10000 Zagreb, Croatia)

  • Tonči Carić

    (Faculty of Transport and Traffic Sciences, University of Zagreb, Vukelićeva 4, 10000 Zagreb, Croatia)

Abstract

With the rise of the electric vehicle market share, many logistic companies have started to use electric vehicles for goods delivery. Compared to the vehicles with an internal combustion engine, electric vehicles are considered as a cleaner mode of transport that can reduce greenhouse gas emissions. As electric vehicles have a shorter driving range and have to visit charging stations to replenish their energy, the efficient routing plan is harder to achieve. In this paper, the Electric Vehicle Routing Problem with Time Windows (EVRPTW), which deals with the routing of electric vehicles for the purpose of goods delivery, is observed. Two recharge policies are considered: full recharge and partial recharge. To solve the problem, an Adaptive Large Neighborhood Search (ALNS) metaheuristic based on the ruin-recreate strategy is coupled with a new initial solution heuristic, local search, route removal, and exact procedure for optimal charging station placement. The procedure for the O ( 1 ) evaluation in EVRPTW with partial and full recharge strategies is presented. The ALNS was able to find 38 new best solutions on benchmark EVRPTW instances. The results also indicate the benefits and drawbacks of using a partial recharge strategy compared to the full recharge strategy.

Suggested Citation

  • Tomislav Erdelić & Tonči Carić, 2022. "Goods Delivery with Electric Vehicles: Electric Vehicle Routing Optimization with Time Windows and Partial or Full Recharge," Energies, MDPI, vol. 15(1), pages 1-27, January.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:1:p:285-:d:716114
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    References listed on IDEAS

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    5. Davis, Brian A. & Figliozzi, Miguel A., 2013. "A methodology to evaluate the competitiveness of electric delivery trucks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 49(1), pages 8-23.
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    Cited by:

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    4. Nan Ding & Jingshuai Yang & Zhibin Han & Jianming Hao, 2022. "Electric-Vehicle Routing Planning Based on the Law of Electric Energy Consumption," Mathematics, MDPI, vol. 10(17), pages 1-27, August.
    5. Yanfei Zhu & Chunhui Li & Kwang Y. Lee, 2022. "The NR-EGA for the EVRP Problem with the Electric Energy Consumption Model," Energies, MDPI, vol. 15(10), pages 1-12, May.
    6. Seyfi, Majid & Alinaghian, Mahdi & Ghorbani, Erfan & Çatay, Bülent & Saeid Sabbagh, Mohammad, 2022. "Multi-mode hybrid electric vehicle routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 166(C).
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    8. Wojciech Cieslik & Weronika Antczak, 2023. "Research of Load Impact on Energy Consumption in an Electric Delivery Vehicle Based on Real Driving Conditions: Guidance for Electrification of Light-Duty Vehicle Fleet," Energies, MDPI, vol. 16(2), pages 1-19, January.

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