Two-stage scheduling of apron support vehicles considering multi-vehicle coordination

Abstract

Large airport apron support vehicles have always been facing great operating pressure, and the coordination constraints of various apron support services and dynamic flight information pose higher challenges to vehicle scheduling. Considering the differences in vehicle operation constraints in three different modes: continuous work, continuous work with capacity constraints, and round-trip work, a multi-vehicle coordinated apron support vehicle scheduling model is established with the goal of minimizing the number of vehicles and the total driving distance. According to the actual operation of the airport, the model is solved in two stages. In the static stage, an NSGA II algorithm integrating local search is designed, and in the dynamic stage, a neighborhood search algorithm is designed to solve the multi-vehicle coordinated scheduling problem. Data simulation results show that compared with first-come-first-served, the number of vehicles and the total driving distance in the static scheduling stage are reduced by 18.9%and respectively 8.9%; the dynamic scheduling stage results can maintain the number of vehicles in the original scheduling plan, and the adjustment of driving distance is reduced compared with the large-scale neighborhood search algorithm 25.8% . The research results can provide certain guiding significance for the scheduling management and decision-making of apron support vehicles in large airports.