Particle Fish Swarm Algorithm

摘要：

A novel intelligent optimization algorithm called as particle fish swarm algorithm (PFSA) is presented in this paper. PFSA is inspired from artificial fish swarm algorithm (AFSA) and particle swarm optimization (PSO), and it can overcome the weakness of AFSA to quickly and precisely search out the optimum solution in optimization problems. In order to study the performance of PFSA, four well-known benchmark functions are optimized by PFSA and AFSA in the simulation experiments, the results show that the performance of PFSA is better than AFSA. In other word, PFSA has good performances (e.g. fast convergence speed and nice precision) to achieve the global best solution in the optimization problems.

关键词： particle fish swarm algorithm artificial fish swarm algorithm function optimization

作者: Zushun Wu Zhangji Zhao Sisi Jiang Xuechi Zhang

作者单位: College of Information Science and Technology Beijing Normal University Beijing, China Department of Physics, School of Science Harbin Institute of Technology,Harbin, China Department of Electronics, School of Information Science Beijing Normal University Beijing, China

会议类型: 国际会议

会议名称: The 2011 International Workshop on Internet of Things Technology and Innovative Application Design(2011年国际物联网技术与创新应用设计研讨会IOT Workshop 2011)

会议地点: 北京

会议语种:英文

页码: 555-558

在线出版日期: 2011-08-24（万方平台首次上网日期，不代表论文的发表时间）