Author
Listed:
- Hou, Xuejing
- Zhang, Lun
- Chen, Shuiwang
- Wu, Lingxiao
Abstract
Airports are increasingly introducing electric towing vehicles to facilitate their transitions toward environmentally sustainable operations, aiming to reduce greenhouse gas emissions. Efficient fleet scheduling is crucial for airport operators to meet the growing demand for aircraft taxiing while ensuring high operational efficiency. This paper investigates a fleet scheduling problem involving task assignment, route planning and charging planning. Additionally, some practical requirements are incorporated, including a nonlinear charging profile, an on-demand charging strategy and conflict-free aircraft routing. The problem is formulated as a mixed-integer nonlinear programming model to minimize the total operational cost. To improve tractability, the original model is transformed into a mixed-integer linear programming (MILP) formulation, and three groups of valid inequalities are introduced to strengthen the model. We propose a rolling horizon method capable of solving problems across various scales. Extensive numerical experiments are conducted to evaluate the performance of the proposed model and solution method. Computational results demonstrate that the developed valid inequalities help accelerate solution process and the proposed method outperforms a standard MILP solver in both solution quality and computational efficiency for medium-scale and large-scale instances. We conduct a case study based on real-world data to evaluate the model’s practical applicability. The results of sensitivity analysis provide managerial insights for airport operators to design optimal scheduling schemes.
Suggested Citation
Hou, Xuejing & Zhang, Lun & Chen, Shuiwang & Wu, Lingxiao, 2026.
"Fleet scheduling for electric towing of aircraft with nonlinear charging profile and on-demand charging strategy,"
Journal of Air Transport Management, Elsevier, vol. 136(C).
Handle:
RePEc:eee:jaitra:v:136:y:2026:i:c:s0969699726000700
DOI: 10.1016/j.jairtraman.2026.103034
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