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Location planning of electric vehicle charging station with users’ preferences and waiting time: multi-objective bi-level programming model and HNSGA-II algorithm

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  • Bo Zhang
  • Meng Zhao
  • Xiangpei Hu

Abstract

Interactive users’ preferences and waiting time together have great impact on charging station network design of electric vehicles (EVs), but only waiting time was considered in previous studies. To fill this research gap, this paper addresses a location planning problem for EV charging stations, which considers users’ preferences and waiting time simultaneously. The problem is formulated as a multi-objective bi-level programming model, the upper level model determines locations and capacity options of charging stations with the objectives of minimising total cost and minimising total service tardiness, and the lower level model determines the allocation of users to stations with the objective of minimising total travel time. A hybrid non-dominated sorting genetic algorithm II (HNSGA-II) with embedded level determination algorithm (LDA) and a partial enumeration algorithm (PEA) are proposed, respectively, to solve the model. Furthermore, managerial analysis is implemented to verify the advantages of considering users’ preferences in reducing charging service tardiness and saving cost compared with the mode of no considering users’ preferences. And sensitivity analysis is also performed to provide managerial insights for EV charging station location practice. Finally, a real-world case study is conducted to verify the applicability of the proposed approach in solving practical location planning problems.

Suggested Citation

  • Bo Zhang & Meng Zhao & Xiangpei Hu, 2023. "Location planning of electric vehicle charging station with users’ preferences and waiting time: multi-objective bi-level programming model and HNSGA-II algorithm," International Journal of Production Research, Taylor & Francis Journals, vol. 61(5), pages 1394-1423, March.
  • Handle: RePEc:taf:tprsxx:v:61:y:2023:i:5:p:1394-1423
    DOI: 10.1080/00207543.2021.2023832
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    Cited by:

    1. Zhang, Fan & Lv, Huitao & Xing, Qiang & Ji, Yanjie, 2024. "Deployment of battery-swapping stations: Integrating travel chain simulation and multi-objective optimization for delivery electric micromobility vehicles," Energy, Elsevier, vol. 290(C).
    2. Zongfeng Zou & Weihao Yang & Shirley Ye Sheng & Xin Yan, 2024. "Research on the Location Selection Problem of Electric Bicycle Battery Exchange Cabinets Based on an Improved Immune Algorithm," Sustainability, MDPI, vol. 16(19), pages 1-21, September.
    3. Park, Junseok & Moon, Ilkyeong, 2023. "A facility location problem in a mixed duopoly on networks," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 175(C).
    4. Pourvaziri, H. & Sarhadi, H. & Azad, N. & Afshari, H. & Taghavi, M., 2024. "Planning of electric vehicle charging stations: An integrated deep learning and queueing theory approach," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 186(C).
    5. Rosebell Paul & Mercy Paul Selvan, 2024. "Predicting and Forecasting of Vehicle Charging Station Using ECNN with DHFO Algorithm," Energies, MDPI, vol. 17(17), pages 1-25, August.

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