Study on The Nonlinear Strategy of Inertia Weight in Particle Swarm Optimization

Particle swarm optimization (PSO) as an efficient and powerful problem-solving strategy has been widely used, but the appropriate adjustment of its inertia weight usually requires a lot of time and labor. In this paper, a nonlinear variation strategy to inertia weight is presented. The results obtained through the proposed method are compared with existing PSO algorithms. Finally, the simulation results show that the proposed method can provide faster convergence and optimal solution with better accuracy.