Landing scheduling for carrier aircraft fleet considering bolting probability and aerial refueling

Recovery is a crucial supporting process for carrier aircraft, where a reasonable landing scheduling is expected to guide the fleet landing safely and quickly. Currently, there is little research on this topic, and most of it neglects potential influence factors, leaving the corresponding supporting efficiency questionable. In this paper, we study the landing scheduling problem for carrier aircraft considering the effects of bolting and aerial refueling. Based on the analysis of recovery mode involving the above factors, two types of primary constraints (i.e., fuel constraint and wake interval constraint) are first described. Then, taking the landing sequencing as decision variables, a combinatorial optimization model with a compound objective function is formulated. Aiming at an efficient solution, an improved firefly algorithm is designed by integrating multiple evolutionary operators. In addition, a dynamic replanning mechanism is introduced to deal with special situations (i.e., the occurrence of bolting and fuel shortage), where the high efficiency of the designed algorithm facilitates the online scheduling adjustment within seconds. Finally, numerical simulations with sufficient and insufficient fuel cases are both carried out, highlighting the necessity to consider bolting and aerial refueling during the planning procedure. Simulation results reveal that a higher bolting probability, as well as extra aerial refueling operations caused by fuel shortage, will lead to longer recovery complete time. Meanwhile, due to the strong optimum-seeking capability and solution efficiency of the improved algorithm, adaptive scheduling can be generated within milliseconds to deal with special situations, significantly improving the safety and efficiency of the recovery process. An animation is accessible at bilibili.com/video/BV1QprKY2EwD. • A landing sequencing model considering bolting rate and aerial refueling is built. • An improved firefly algorithm shows superiority in solution efficiency. • A dynamic replanning mechanism is integrated to deal with bolting and fuel-shortage. • Results reveal that neglecting bolting and refueling will lead to poor performance.