Electric location routing problem under energy consumption uncertainty

被引：0
作者：
Wang, Dan [1 ]
Zhou, Hong [2 ]
Zheng, Wei-Bo [3 ]
机构：
[1] Logistics School, Beijing Wuzi University, Beijing
[2] School of Economics and Management, Beihang University, Beijing
[3] China Astronautics Standard Institute, Beijing
来源：
Kongzhi yu Juece/Control and Decision | 2024年 / 39卷 / 10期
关键词：
adaptive large variable neighborhood search; electric vehicle; location-routing problem; robust optimization; uncertainty;
D O I：
10.13195/j.kzyjc.2023.0231
中图分类号：
学科分类号：
摘要：
With the growing attention to the sustainability, the environmentally friendly electric vehicles gradually occupy a major position in logistics distribution. However, due to the limited travel distance, the electric vehicles need to visit recharging stations. In real life, the uncertainty of electricity consumption affects the location of charging stations. Therefore, this paper studies the electric location routing problem under energy consumption uncertainty. The mathematical model of the problem is given in combination with robust optimization theory. To solve large-scale computing instances, this paper constructs an algorithm as well as several new neighborhoods based on the adaptive large-neighborhood algorithm. Computational experiments show that the proposed model performs well and is suitable for real life. © 2024 Northeast University. All rights reserved.
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收藏
页码：3422 / 3430
页数：8
相关论文
共 26 条
  • [1] Dong J, Liu C Z, Lin Z H., Charging infrastructure planning for promoting battery electric vehicles: An activity-based approach using multiday travel data, Transportation Research Part C: Emerging Technologies, 38, pp. 44-55, (2014)
  • [2] Arslan O, Karasan O E., A Benders decomposition approach for the charging station location problem with plug-in hybrid electric vehicles, Transportation Research Part B: Methodological, 93, pp. 670-695, (2016)
  • [3] Chen R, Qian X W, Miao L X, Et al., Optimal charging facility location and capacity for electric vehicles considering route choice and charging time equilibrium, Computers & Operations Research, 113, (2020)
  • [4] Ghamami M, Kavianipour M, Zockaie A, Et al., Refueling infrastructure planning in intercity networks considering route choice and travel time delay for mixed fleet of electric and conventional vehicles, Transportation Research Part C: Emerging Technologies, 120, (2020)
  • [5] Yang J, Sun H., Battery swap station location-routing problem with capacitated electric vehicles, Computers & Operations Research, 55, pp. 217-232, (2015)
  • [6] Schiffer M, Walther G., The electric location routing problem with time windows and partial recharging, European Journal of Operational Research, 260, 3, pp. 995-1013, (2017)
  • [7] Hof J, Schneider M, Goeke D., Solving the battery swap station location-routing problem with capacitated electric vehicles using an AVNS algorithm for vehicle-routing problems with intermediate stops, Transportation Research Part B: Methodological, 97, pp. 102-112, (2017)
  • [8] Yang S Y, Ning L J, Shang P, Et al., Augmented Lagrangian relaxation approach for logistics vehicle routing problem with mixed backhauls and time windows, Transportation Research Part E: Logistics and Transportation Review, 135, (2020)
  • [9] Li Y, Zhang P W, Wu Y F., Public recharging infrastructure location strategy for promoting electric vehicles: A bi-level programming approach, Journal of Cleaner Production, 172, pp. 2720-2734, (2018)
  • [10] Keskin M, Catay B., Partial recharge strategies for the electric vehicle routing problem with time windows, Transportation Research Part C: Emerging Technologies, 65, pp. 111-127, (2016)
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