A Modified Particle Swarm Optimization for the Applications of Electromagnetic Devices

Particle Swarm Optimization (PSO) is a global search algorithm based on swarm intelligence. The PSO is becoming more popular because of solving complex and complicated benchmark optimization problems. The mathematical model of PSO is easy due to few control parameters. However, the PSO algorithm are stuck due to premature convergence while dealing with high dimensional problems. To handle this issue the current research paper introducing especial best particle that incorporated in the updating equations. Also, the novel best particle control the diversity of the search process and keep a decent balance between the exploration and exploitation searches. The experimental outcomes demonstrates that the novel algorithm performs well as compared to other one.