UA V Swarm Scheduling Based on Weighted Multi-Objective Particle Swarm Algorithm

In order to solve the problem of low node allocation efficiency of UAV swarms in forest fire disaster relief scenarios, a weighted multi-objective particle swarm UAV swarm scheduling algorithm was proposed, and the visualization of simulation scheduling was realized. Through the improvement of the target point allocation model, the standardization of the target point weight, and the definition of the comprehensive evaluation index of the UAV, after selecting the UAV with the optimal performance and the largest distribution probability, the remaining UAVs are distributed according to the average probability. Scheduling to improve the real-time performance of UAV swarm scheduling. Finally, through the simulation experiment and performance analysis of the simulation system, the results show that the improved algorithm of UAV swarm scheduling average convergence time is reduced by about 30s compared with the original algorithm, has better convergence, and the UAV swarm scheduling efficiency is improved.