This paper addresses the optimization deployment of jamming devices for efficiently disrupting enemy communication networks. It innovatively integrates Particle Swarm Optimization (PSO) with Harris Hawk Optimization (HHO) algorithms to propose a hybrid strategy (PSO-HHO). This approach aims to dynamically adjust the spatial distribution of jamming devices, significantly enhancing coverage efficiency and interference intensity on key nodes. Intelligent optimization algorithms have become research hotspots due to their global search capabilities and strong adaptability; however, single algorithms face limitations in complex multi-objective optimization problems. To address this, the paper combines PSO and HHO algorithms, employing dynamic inertia weight adjustment, introducing crossover mutation, and incorporating early stopping mechanisms. This ensures a balance between global search and local exploitation capabilities while designing multidimensional fitness functions and incorporating distance penalty terms to strengthen constraint satisfaction. Simulation results demonstrate that the hybrid algorithm can quickly find optimal solutions in jammer optimization deployment and effectively adapt to different battlefield environments, thereby improving interference effectiveness.