Deployment problem of Wireless Sensor Networks based on Adaptive Particle Swarm Optimization

In response to the shortcomings of particle swarm optimization (PSO) such as insufficient global search, susceptibility to local optima, and slow convergence speed, this paper proposes an improved adaptive PSO (APSO). Firstly, a superior point set is employed for particle population initialization, achieving a more uniform and extensive particle distribution. Secondly, during the particle velocity update phase, an adaptive Levy flight acceleration coefficient is introduced along with adjustments to the social learning factor, emphasizing global search. Finally, in the particle position update phase, an adaptive scaling factor is introduced to intelligently adjust particle position weights, aiding in obtaining superior solutions. The proposed APSO is applied to the wireless sensor network deployment problem, and experimental results demonstrate its outstanding performance in solving optimization problems.