For the collaborative optimization problem of multiple unmanned aerial vehicles (UAVs) jamming the ground communication networks，this paper aims to minimize the maximum power of multiple jamming UAVs under the constraint of suppressing the entire communication network.The complex interference resource allocation problem is transformed into a traditional combinatorial optimization problem with constraints.A hybrid particle swarm optimization (HPSO) algorithm based on particle swarm optimization(PSO) is designed，which simultaneously optimizes the three-dimensional positions of UAVs and the jammer power by treating them as particle positions，and incorporates a weapon threat model. HPSO algorithm，sparrow search algorithm and genetic algorithm arecompared through simulation experiment.The results show that HPSO algorithm has faster convergence speed and can efficiently find suitable UAV deployment solutions.In mission scenarios with different numbers of UAVs，HPSO algorithm demonstrates effective jamming performance and strong stability，making it a more suitable algorithm for optimizing the task of multi-UAV cooperatively jamming the ground communication networks.The research findings provide an effective solution and algorithm for multi-UAV cooperatively jamming the ground communication networks，which is of great significance for enhancing unmanned cyber-electronic warfare capabilities.