Bi-objective collaborative scheduling optimization of airport ferry vehicle and tractor

Abstract

With the continuous growth of aviation business, the flight ground support capability of airport is facing great challenges. The resources of ferry vehicle and tractor are important factors that restrict the flight service level of the airport. This paper analyses the collaborative scheduling of airport ferry vehicle and tractor through innovatively constructing a bi-objective mixed integer programming model, one objective is to minimize the number of ferry vehicles and tractors, and the other is to balance the vehicle usage. To deal with this problem, two methods based on standard particle swarm optimization are adopted: The lexicographic method and Pareto method, and virtual flights are introduced for the convenience of particle coding. The effectiveness and comparison of two methods are illustrated by employing the real flight data of Beijing Capital International Airport. The results of this study may provide reference for the evaluation and optimization of the airport ground support vehicles.