To solve the problem in path planning for multiple UAVs, a hybrid Particle Swarm Optimization (PSO) algorithm is adopted, and the sum total of the cost function of each UAV's path is guaranteed to a minimum. The city environment, including buildings and other obstacles and threatening areas with radar interference, is modeled. The method of setting up a number of waypoints and then inserting the split point is used. Then, the hybrid PSO algorithm with differential evolution operations and adaptive inertia weight strategies is used for path planning of multiple UAVs. Finally, the validity of the algorithm is verified by simulations.