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Integrated optimization of timetabling and Electric Vehicle Scheduling

Vladimir Stadnichuk et al.

EURO Journal on Transportation and Logistics2025https://doi.org/10.1016/j.ejtl.2025.100168article
AJG 2ABDC B
Weight
0.50

What the paper says

We tackle the integrated planning problem of periodic timetabling and electric vehicle scheduling, crucial for cities transitioning to electric bus fleets. Given existing timetables, we allow only minor modifications and propose an iterative solution approach that addresses the Electric Vehicle Scheduling Problem (EVSP) in each iteration. Due to the NP-hard nature of EVSP, we employ well-established heuristics and evaluate the quality of the solutions obtained. Specifically, we establish tight approximation bounds for certain iterative heuristics that first solve the Vehicle Scheduling Problem and subsequently adjust solutions to meet battery constraints. We make several key contributions: We provide general insights into heuristic solution quality, establish theoretical performance bounds, and validate these findings through a case study using real-world data from Aachen, Germany. Additionally, we employ our iterative framework to derive managerial insights for bus operators in Aachen by quantifying potential gains from adjusting the timetable to support the transition to a fully electric bus fleet. • We tackle integrated planning for timetabling and electric vehicle scheduling. • Novel iterative framework to solve the integrated planning problem. • We prove new, tight approximation bounds for some types of heuristics in electric vehicle scheduling. • Real-world case study for Aachen, Germany. • Managerial insights quantify gains from timetable adjustments for a fully electric bus fleet transition.

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Cite this paper

https://doi.org/https://doi.org/10.1016/j.ejtl.2025.100168

Or copy a formatted citation

@article{vladimir2025,
  title        = {{Integrated optimization of timetabling and Electric Vehicle Scheduling}},
  author       = {Vladimir Stadnichuk et al.},
  journal      = {EURO Journal on Transportation and Logistics},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1016/j.ejtl.2025.100168},
}

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Integrated optimization of timetabling and Electric Vehicle Scheduling

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.