A hierarchical human-machine-collaborative decision-making method for carrier-based aircraft flight planning

Objectives Carrier-based aircraft serve as the core combat force of an aircraft carrier, and their sortie rate is a key indicator for evaluating the carrier's operational effectiveness. Under operational conditions with limited deck space and constrained support resources, developing efficient and feasible flight plans for carrier-based aircraft becomes a critical challenge for improving sortie efficiency and overall combat capability. Taking the operational environment of Nimitz-class aircraft carriers as the research context, a hierarchical human-in-the-loop decision-making method is proposed to achieve efficient and coordinated optimization of sortie and recovery sequences, as well as support operation execution orders for carrier-based aircraft. Methods A priority ranking mechanism integrating multiple key indicators was first developed to comprehensively assess the status of carrier-based aircraft and the urgency and importance of their support operations. Building upon this, a hierarchical reinforcement learning algorithm was designed, taking into account the structural characteristics of both the aircraft layer and the support operation layer, to jointly optimize the execution sequence of aircraft and their support operations, thereby achieving globally efficient decision-making. To further enhance decision quality, a commander feedback mechanism was incorporated, along with a dynamic switching function to enable adaptive collaboration between the intelligent agent and human commander. Extensive comparative experiments were conducted in a simulated environment based on the Nimitz-class aircraft carrier. Results Experimental results demonstrate that the proposed method reduces the total completion time and waiting time of support operations by an average of 20.9% and 31.2%, respectively, compared to baseline algorithms, thereby validating its effectiveness and practical value in carrier-based aircraft flight planning decisions. Conclusions The results of this study provide valuable insights for supporting decision-making in multi-wave flight planning of carrier-based aircraft.