摘要
将微粒群算法与并行计算模型相结合,基于三种不同的并行计算模型(带中央控制器的并行计算模型、环形结构带缓存区的并行计算模型、BSP并行计算模型),设计出相应的并行微粒群算法,并对并行算法性能进行详细分析。大量实验表明:子种群之间的通讯周期是个重要的可变参数,当选取合适时,能提高解的质量以及算法的收敛性和最优性。
In the paper, the parallel particle swarm optimization （PSO） are designed based on three parallel computation models which include parallel computation model with central controller, ring-structure model with buffers, and BSP parallel computation model. The results of experiment show that the period of communication is key parameter. If an apropriate period of communication is chosen, the quality of the result and the performance of algorithm can be improved.
出处
《微电子学与计算机》
CSCD
北大核心
2007年第9期25-28,共4页
Microelectronics & Computer
基金
教育部重点科研基金项目(204018)
