Particle swarm optimisation by adding Gaussian disturbance item guided by hybrid narrow centre

Abstract

This study proposed the optimised PSO algorithm after the addition of Gaussian disturbance guided by hybrid narrow centre. By combining narrow centre and improved narrow centre particles, the hybrid narrow centre can be constructed. In the updating formula of particle velocity, Gaussian disturbance item controlled by hybrid narrow centre is used for replacing self-cognition item. Owing to the guidance of hybrid narrow centre, the convergence is accelerated, while the introduction of Gaussian disturbance can prevent the particles from falling into local optimum. The combination of hybrid narrow centre and Gaussian disturbance can effectively avoid premature convergence and greatly increase convergence rate.