A Study of Particle Swarm Optimization with Considering More Local Best Particles
Yen-Ching Chang, Li‐Chun Lai, Chin-Chen Chueh, Yongxuan Xu, Cheng-Hsueh Hsieh · Advances in intelligent systems research/Advances in Intelligent Systems Research · 2013
The velocity updating formula of the standard particle swarm optimization (PSO) only considers two particles: the local best particle and the global best particle.The global best particle can be viewed as the optimal one of all local best particles.In order to improve the optimizing performance and exploit all existing resources as fully as possible, we further study other local best particles how to affect the results of optimization in this paper.Experimental results show that a suitable selection of the number of local best particles will result in higher performance.