IDEAS home Printed from https://ideas.repec.org/a/hin/jnlmpe/8795284.html
   My bibliography  Save this article

Electric Vehicle Routing Problems with Stochastic Demands and Dynamic Remedial Measures

Author

Listed:
  • Xianlong Ge
  • Ziqiang Zhu
  • Yuanzhi Jin

Abstract

With the rapid development of e-commerce, logistic enterprises must better predict customer demand to improve distribution efficiency, so as to deliver goods in advance, which makes logistics stochastic and dynamic. In order to deal with this challenge and respond to the concept of “green logistics,” an electric vehicle routing problem with stochastic demands (EVRPSD) and proactive remedial measures is investigated, and an EVRPSD model with probability constraints is established. At the same time, a hybrid heuristic algorithm, combining a saving method and an improved Tabu search algorithm, is proposed to solve the model. Moreover, two insertion strategies with the greedy algorithm for charging stations and dynamic nodes are introduced. Finally, a large number of experimental data show that the heuristic algorithm proposed in this paper is feasible and effective.

Suggested Citation

  • Xianlong Ge & Ziqiang Zhu & Yuanzhi Jin, 2020. "Electric Vehicle Routing Problems with Stochastic Demands and Dynamic Remedial Measures," Mathematical Problems in Engineering, Hindawi, vol. 2020, pages 1-15, August.
  • Handle: RePEc:hin:jnlmpe:8795284
    DOI: 10.1155/2020/8795284
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/MPE/2020/8795284.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/MPE/2020/8795284.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2020/8795284?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhang, Xiangyi & Chen, Lu & Gendreau, Michel & Langevin, André, 2022. "A branch-and-cut algorithm for the vehicle routing problem with two-dimensional loading constraints," European Journal of Operational Research, Elsevier, vol. 302(1), pages 259-269.
    2. Ji, Bin & Zhang, Zheng & Yu, Samson S. & Zhou, Saiqi & Wu, Guohua, 2023. "Modelling and heuristically solving many-to-many heterogeneous vehicle routing problem with cross-docking and two-dimensional loading constraints," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1219-1235.
    3. 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.
    4. Zheng Zhang & Bin Ji & Samson S. Yu, 2023. "An Adaptive Tabu Search Algorithm for Solving the Two-Dimensional Loading Constrained Vehicle Routing Problem with Stochastic Customers," Sustainability, MDPI, vol. 15(2), pages 1-23, January.
    5. Abbas Tarhini & Kassem Danach & Antoine Harfouche, 2022. "Swarm intelligence-based hyper-heuristic for the vehicle routing problem with prioritized customers," Annals of Operations Research, Springer, vol. 308(1), pages 549-570, January.
    6. Cherkesly, Marilène & Gschwind, Timo, 2022. "The pickup and delivery problem with time windows, multiple stacks, and handling operations," European Journal of Operational Research, Elsevier, vol. 301(2), pages 647-666.

    More about this item

    Statistics

    Access and download statistics

    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:hin:jnlmpe:8795284. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.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.