Particle Swarm Optimization Algorithm Based on Factor Selection Strategy
Jiapeng Lv, Xianjun Shi · 2019
The classical particle swarm optimization algorithm will cause premature stagnation due to the limitation of particle diversity, and thus fall into local optimum. In order to overcome the above shortcomings, this paper proposes a particle swarm optimization algorithm based on particle swarm number selection strategy based on the idea of particle swarm. In the different stages of the particle swarm search process, different parameter selection strategies are adopted to improve the global search ability. The simulation results show that the method is effective and superior in solving the optimization problem of complex problems.