文献类型：期刊文献

英文题名：Co-evolutionary cultural based particle swarm optimization algorithm

作者：Sun, Yang[1]; Zhang, Lingbo[1]; Gu, Xingsheng[1]

机构：[1] Research Institute of Automation, East China University of Science and Technology, 200237, Shanghai, China

年份：2010

卷号：98 CCIS

期号：PART 2

起止页码：1

外文期刊名：Communications in Computer and Information Science

收录：EI(收录号：20104513368890)

语种：英文

外文关键词：Intelligent computing - Particle swarm optimization (PSO)

摘要：Particle swarm optimization (PSO), cultural algorithm (CA) and co-evolutionary algorithm (CEA) are all research hotspots in the field of intelligent computing. In order to apply their advantages, a hybrid algorithm CECBPSO is proposed in this paper. In the hybridization, PSO is introduced into the framework of CA, and then a co-evolutionary mechanism between two cultural based PSO algorithms is established. In this way, useful experiences can be exchanged among the populations, and randomly reinitialized particles are introduced into the algorithm. Both of them can help the algorithm improving the efficiency and escape the local optima when the particles get premature. The performance is evaluated on five test functions. Simulation results show that the hybridizing of the three algorithms greatly improves the performance. ? 2010 Springer-Verlag.