Mission planning for multi-aircraft material delivery considering complex environments

This paper focuses on the task allocation and path planning problem for aircraft material delivery, considering two complexity factors: aircraft loss caused by malicious interference and delivery timeliness. It establishes an objective function to be optimized, which includes aircraft loss, total mileage, and untimely supply rate. Meanwhile, it proposes an optimization approach based on prior knowledge such as "task merging" and "saturation supply", and implements an improved genetic algorithm. Simulation results show that the improved genetic algorithm with fused prior knowledge addresses the slow convergence problem caused by a large search space, improving the solution speed and optimization effect of the model.