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Aiming at the problems of complicated deployment structure of routing nodes in wireless networks, high economic cost and poor communication quality, an adaptive routing node deployment strategy (ADS) based on optimized hybrid particle swarm algorithm (HPSO) is proposed. This paper takes the lowest deployment cost as the algorithm optimization goal, takes wireless networking node communication, spatial coverage integrity and other characteristics as constraints, through optimizing HPSO combined with ADS, to obtain the best routing node deployment within the application range. First, establish the deployment cost model of the wireless communication network routing node, the deployment communication distance relationship model, the node communication load model, and the free space loss model. According to the model, determine the algorithm optimization target and algorithm restriction conditions. Then the HPSO is optimized, and the elimination mechanism and the diversity supplement mechanism are added to improve the accuracy of algorithm optimization without reducing the efficiency of the algorithm. For spatially adjacent routing nodes, ADS is designed and deployed, and the visual domain model is optimized at the same time to reduce the range of feasible points in ADS and improve the deployment efficiency of the next node. In this method, HPSO and genetic algorithm (GA) algorithm and artificial immune algorithm (AIA) are combined with ADS for comparative experiments. The simulation results show that the method in this paper improves the algorithm efficiency by 14~33% and reduces the deployment cost of routing nodes by 8~10% on the basis of ensuring the communication quality of the wireless communication network.