Title :
Group-decided particle swarm optimization
Author :
Yang, Hongjuan ; Cui, Zhihua ; Wang, Liang ; Cai, Xingjuan ; Tan, Ying ; Wu, Jianna
Author_Institution :
Complex Syst. & Comput. Intell. Lab., Taiyuan Univ. of Sci. & Technol., Taiyuan, China
Abstract :
In particle swarm optimization algorithm, computational efficiency is one key problem to affect the algorithm performance due to the dynamic balance between exploration and exploitation capabilities. In this paper, a new strategy, one group-decided position is regarded as the attraction center to provide more chances to search the local optimum. This group-decided position is estimated with all particles´ fitness change ratios. Simulation results show it is effective and efficiency.
Keywords :
group theory; particle swarm optimisation; computational efficiency; exploitation capability; exploration capability; group decided particle swarm optimization; particles fitness change ratios; Benchmark testing; Decision making; Educational institutions; Heuristic algorithms; Humans; Particle swarm optimization; Simulation;
Conference_Titel :
Cognitive Informatics & Cognitive Computing (ICCI*CC ), 2011 10th IEEE International Conference on
Conference_Location :
Banff, AB
Print_ISBN :
978-1-4577-1695-9
DOI :
10.1109/COGINF.2011.6016166
