期刊名称：Journal of Theoretical and Applied Information Technology
印刷版ISSN：1992-8645
电子版ISSN：1817-3195
出版年度：2013
卷号：48
期号：2
页码：1109-1114
出版社：Journal of Theoretical and Applied
摘要：Quantum-behaved particle swarm optimization (QPSO) is a good optimization technique which has been successfully applied in many research and application areas. But traditional QPSO algorithm is easy to fall into local optimum and the rate of convergence is slow. To solve these problems, an improved algorithm based on dynamic adjustment of the acceleration factor is proposed. The experiments on high dimensional function optimization showed that the improved algorithm has more powerful global exploration ability and faster convergence speed.
关键词：QPSO; Accelerating Factor; Function Optimization
