Abstract: Electrification of ground service vehicles has emerged as a new trend in airport ground operations. Insufficient number of vehicles and improper scheduling are significant contributors to flight delays. Existing research on the scheduling of airport ground support vehicles predominantly focuses on fuel-powered vehicles. This paper studies the scheduling problem of airport electric ferry vehicles under the condition of limited vehicle resources. Considering the flight service priorities, we construct a bi-objective mixed-integer programming model with the objective of minimizing the flight delay cost and the vehicle idling time. To improve the solving efficiency, according to the characteristics of the model, an improved genetic algorithm is integrated within the framework of the boxed line method to solve it. The effectiveness of this algorithm compared with the ε-constraint method and the classical genetic algorithm is validated through a comparative analysis using the actual flight data from a hub airport. This study provides a theoretical foundation and practical guidance for the scheduling operations of electric ferry vehicles at airports, holding significant implications for promoting the green transformation of airports, enhancing passenger satisfaction and improving operational efficiency.

Key words: electric ferry vehicle, mixed-integer programming, boxed line method, genetic algorithm