Joint Scheduling of UAV Releasing Based on Improved Genetic Algorithm

Aiming at the multi-stage scheduling optimization problem of UAV, this paper first proposes a UAV scheduling method based on improved genetic algorithm, which optimizes population initialization, improves crossover and mutation operations, and then introduces dynamic mutation rate and local search strategy. Experimental results show that the improved genetic algorithm has significant advantages in total scheduling time and convergence. Secondly, aiming at the route scheduling problem of functional vehicles, an optimization model considering the constraints of time, space and resources is established. With the goal of minimizing the release time and the waiting time for resource conflict, the optimal route is obtained. Finally, the joint scheduling mode is proposed, which integrates the scheduling tasks through the time synchronization mechanism to optimize the task connection and resource allocation. The comparative analysis shows that the joint scheduling mode reduces the overall scheduling time by 16%, and releases more UAVs with increment from 33.% to 100% in the same time, having a more better performance in more shorter and urgent time demand.