In the multi-objective optimization and decision-making problem of multi-objective and multi-unmanned aerial vehicle (UAV),which has many constraints,complex and coupling,the traditional particle swarm optimization (PSO) algorithm is easy to fall into the local optimal in the optimization.Therefore,a hybrid particle swarm optimization algorithm based on simulated annealing (SA-PSO) is proposed.Based on the background of the attack task,comprehensively considers the physical performance constraints of the UAV,builds the minimum fitness function of the track length and the minimum fitness function of the threat cost to construct the objective function.First,use the Voronoi diagram and the Dijkstra algorithm for path planning,then a hybrid particle swarm optimization algorithm based on simulated annealing is used for task assignment.The simulation results show that the proposed algorithm combines the advantages of simulated annealing algorithm (SA) and particle PSO,which can quickly solve the approximate optimal solution of UAV task planning and is compatible with PSO algorithm.Compared with the SA algorithm,better results is obtained when there are enough evolution times.