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
Available Online September 2013.
- 10.2991/icsecs-13.2013.24How to use a DOI?
- optimization; particle swarm; algorithm; particle swarm optimization
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.
- © 2013, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Yen-Ching Chang AU - Li-Chun Lai AU - Chin-Chen Chueh AU - Yongxuan Xu AU - Cheng-Hsueh Hsieh PY - 2013/09 DA - 2013/09 TI - A Study of Particle Swarm Optimization with Considering More Local Best Particles BT - Proceedings of the 2013 International Conference on Software Engineering and Computer Science PB - Atlantis Press SP - 116 EP - 119 SN - 1951-6851 UR - https://doi.org/10.2991/icsecs-13.2013.24 DO - 10.2991/icsecs-13.2013.24 ID - Chang2013/09 ER -