IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v16y2024i8p3439-d1379249.html
   My bibliography  Save this article

Electric Vehicle Routing Problem with States of Charging Stations

Author

Listed:
  • Gitae Kim

    (Department of Industrial Management Engineering, Hanbat National University, Daejeon 34158, Republic of Korea)

Abstract

This paper proposes an electric vehicle routing problem, considers the states of charging stations and suggests solution strategies. The charging of electric vehicles is a main issue in the field of electric vehicle routing. There are many studies that find the locations of charging stations, recharging functions for the batteries of vehicles, and so on. However, the state of charging stations significantly affects the routes of electric vehicles, which is not much explored. The states may include open or closed charging stations, occupied or empty charging slots, and so on. This paper investigates how the states of charging stations are estimated and how routing strategies are determined. We formulate a mixed integer programming model and suggest how to solve the problem with an exact method. Numerical examples provide the optimal routing strategies of electric vehicles for the changing environments regarding the states of charging stations.

Suggested Citation

  • Gitae Kim, 2024. "Electric Vehicle Routing Problem with States of Charging Stations," Sustainability, MDPI, vol. 16(8), pages 1-17, April.
  • Handle: RePEc:gam:jsusta:v:16:y:2024:i:8:p:3439-:d:1379249
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/16/8/3439/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2071-1050/16/8/3439/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xiao, Yiyong & Zhang, Yue & Kaku, Ikou & Kang, Rui & Pan, Xing, 2021. "Electric vehicle routing problem: A systematic review and a new comprehensive model with nonlinear energy recharging and consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    2. Nolz, Pamela C. & Absi, Nabil & Feillet, Dominique & Seragiotto, Clóvis, 2022. "The consistent electric-Vehicle routing problem with backhauls and charging management," European Journal of Operational Research, Elsevier, vol. 302(2), pages 700-716.
    3. Michael Schneider & Andreas Stenger & Dominik Goeke, 2014. "The Electric Vehicle-Routing Problem with Time Windows and Recharging Stations," Transportation Science, INFORMS, vol. 48(4), pages 500-520, November.
    4. Montoya, Alejandro & Guéret, Christelle & Mendoza, Jorge E. & Villegas, Juan G., 2017. "The electric vehicle routing problem with nonlinear charging function," Transportation Research Part B: Methodological, Elsevier, vol. 103(C), pages 87-110.
    5. Schneider, M. & Stenger, A. & Goeke, D., 2014. "The Electric Vehicle Routing Problem with Time Windows and Recharging Stations," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 62382, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    6. Marius M. Solomon, 1987. "Algorithms for the Vehicle Routing and Scheduling Problems with Time Window Constraints," Operations Research, INFORMS, vol. 35(2), pages 254-265, April.
    7. Schneider, M. & Stenger, A. & Hof, J., 2015. "An Adaptive VNS Algorithm for Vehicle Routing Problems with Intermediate Stops," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 63500, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cortés-Murcia, David L. & Prodhon, Caroline & Murat Afsar, H., 2019. "The electric vehicle routing problem with time windows, partial recharges and satellite customers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 130(C), pages 184-206.
    2. Maximilian Schiffer & Michael Schneider & Grit Walther & Gilbert Laporte, 2019. "Vehicle Routing and Location Routing with Intermediate Stops: A Review," Transportation Science, INFORMS, vol. 53(2), pages 319-343, March.
    3. Raeesi, Ramin & Zografos, Konstantinos G., 2022. "Coordinated routing of electric commercial vehicles with intra-route recharging and en-route battery swapping," European Journal of Operational Research, Elsevier, vol. 301(1), pages 82-109.
    4. Dönmez, Sercan & Koç, Çağrı & Altıparmak, Fulya, 2022. "The mixed fleet vehicle routing problem with partial recharging by multiple chargers: Mathematical model and adaptive large neighborhood search," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 167(C).
    5. Sadati, Mir Ehsan Hesam & Çatay, Bülent, 2021. "A hybrid variable neighborhood search approach for the multi-depot green vehicle routing problem," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 149(C).
    6. Erfan Ghorbani & Mahdi Alinaghian & Gevork. B. Gharehpetian & Sajad Mohammadi & Guido Perboli, 2020. "A Survey on Environmentally Friendly Vehicle Routing Problem and a Proposal of Its Classification," Sustainability, MDPI, vol. 12(21), pages 1-71, October.
    7. Xiao, Yiyong & Zhang, Yue & Kaku, Ikou & Kang, Rui & Pan, Xing, 2021. "Electric vehicle routing problem: A systematic review and a new comprehensive model with nonlinear energy recharging and consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    8. Yusuf Yilmaz & Can B. Kalayci, 2022. "Variable Neighborhood Search Algorithms to Solve the Electric Vehicle Routing Problem with Simultaneous Pickup and Delivery," Mathematics, MDPI, vol. 10(17), pages 1-22, August.
    9. Raeesi, Ramin & Zografos, Konstantinos G., 2020. "The electric vehicle routing problem with time windows and synchronised mobile battery swapping," Transportation Research Part B: Methodological, Elsevier, vol. 140(C), pages 101-129.
    10. Koyuncu, Işıl & Yavuz, Mesut, 2019. "Duplicating nodes or arcs in green vehicle routing: A computational comparison of two formulations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 122(C), pages 605-623.
    11. Asghari, Mohammad & Mirzapour Al-e-hashem, S. Mohammad J., 2021. "Green vehicle routing problem: A state-of-the-art review," International Journal of Production Economics, Elsevier, vol. 231(C).
    12. Markov, Iliya & Varone, Sacha & Bierlaire, Michel, 2016. "Integrating a heterogeneous fixed fleet and a flexible assignment of destination depots in the waste collection VRP with intermediate facilities," Transportation Research Part B: Methodological, Elsevier, vol. 84(C), pages 256-273.
    13. 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.
    14. Malladi, Satya S. & Christensen, Jonas M. & Ramírez, David & Larsen, Allan & Pacino, Dario, 2022. "Stochastic fleet mix optimization: Evaluating electromobility in urban logistics," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 158(C).
    15. Schiffer, Maximilian & Walther, Grit, 2018. "Strategic planning of electric logistics fleet networks: A robust location-routing approach," Omega, Elsevier, vol. 80(C), pages 31-42.
    16. Hao Qiang & Rui Ou & Yanchun Hu & Zhenyu Wu & Xiaohua Zhang, 2023. "Path Planning of an Electric Vehicle for Logistics Distribution Considering Carbon Emissions and Green Power Trading," Sustainability, MDPI, vol. 15(22), pages 1-16, November.
    17. Qiuping Ni & Yuanxiang Tang, 2023. "A Bibliometric Visualized Analysis and Classification of Vehicle Routing Problem Research," Sustainability, MDPI, vol. 15(9), pages 1-37, April.
    18. Sohrabi, Somayeh & Ziarati, Koorush & Keshtkaran, Morteza, 2020. "A Greedy Randomized Adaptive Search Procedure for the Orienteering Problem with Hotel Selection," European Journal of Operational Research, Elsevier, vol. 283(2), pages 426-440.
    19. Guy Desaulniers & Fausto Errico & Stefan Irnich & Michael Schneider, 2016. "Exact Algorithms for Electric Vehicle-Routing Problems with Time Windows," Operations Research, INFORMS, vol. 64(6), pages 1388-1405, December.
    20. Li, Lu & Lo, Hong K. & Huang, Wei & Xiao, Feng, 2021. "Mixed bus fleet location-routing-scheduling under range uncertainty," Transportation Research Part B: Methodological, Elsevier, vol. 146(C), pages 155-179.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:16:y:2024:i:8:p:3439-:d:1379249. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.