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Electric Vehicle Routing Problems with Stochastic Demands and Dynamic Remedial Measures

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  • 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
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    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. Vanny Minanda & Yun-Chia Liang & Angela H. L. Chen & Aldy Gunawan, 2024. "Application of an Improved Harmony Search Algorithm on Electric Vehicle Routing Problems," Energies, MDPI, vol. 17(15), pages 1-22, July.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. 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.

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