Routing and charging optimization for electric bus operations

The transition to alternative energy sources and the adoption of on-demand operating modes in urban bus systems are crucial steps towards reducing carbon footprints and improving public transit services. This paper presents a two-phase approach for the collaborative optimization of charging schedules and passenger services, aimed at enhancing the operation of on-demand electric bus systems. First, the authors propose a label-setting dynamic programming algorithm that enables the efficient generation of bus-trips for each bus line in response to passenger requests. Second, they introduce a time–space network optimization model that facilitates integrated multiple bus-trip planning for the transit network, involving multiple bus lines and charging spots. The model selects bus-trips from various time–space arcs, which represent passenger carrying, bus deployment, and bus charging activities. To validate the effectiveness of their approach, they conduct a case study using real-world data from bus lines in Beijing, China. Computational results demonstrate that their approach can handle on-demand electric bus operations within minutes of solution time, efficiently serving over 2,000 passengers. Practically, their approach achieves a notable reduction in average transit time and effectively reduces the waste of public transit resources. The proposed approach can serve as a beneficial tool for decision-makers and operators seeking to enhance the performance and environmental impact of their electric bus systems.

• Record URL:
  https://doi.org/10.1016/j.tre.2023.103372
• Record URL:
  http://www.sciencedirect.com/science/article/pii/S1366554523003605
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/13665545
• Supplemental Notes:
  • © 2023 Elsevier Ltd. All rights reserved. Abstract reprinted with permission of Elsevier.
• Authors:
  • Zhang, Wei
  • Liu, Jiahui
  • Wang, Kai
  • 0000-0002-3040-0422
  • Wang, Liang
• Publication Date: 2024-1

Language

• English

Media Info

• Media Type: Web
• Features: Figures; References; Tables;
• Pagination: 103372
• Serial:
  • Transportation Research Part E: Logistics and Transportation Review
  • Volume: 181
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 1366-5545
  • Serial URL: http://www.sciencedirect.com/science/journal/13665545

Subject/Index Terms

• TRT Terms: Bus transit operations; Electric buses; Electric vehicle charging; Optimization; Routing
• Geographic Terms: Beijing (China)
• Subject Areas: Energy; Planning and Forecasting; Public Transportation; Vehicles and Equipment;

Filing Info

• Accession Number: 01903036
• Record Type: Publication
• Files: TRIS
• Created Date: Dec 22 2023 8:46AM