Improved particle swarm optimization algorithm in dynamic environment

摘要：

　　In this paper,The improved Particle Swarm Optimization in dynamic objective function environment(DOFPSO)is purposed.The dynamic environment will change with the time t.The DOFPSO algorithm discuss that how to determine changes of the time(environment)and how to keep population diversity.The improved algorithm has the ability to fast response the change of environment and could find the best fitness value quickly.The results of experiment indicate that DOFPSO is more effective than particle swarm optimization(PSO)and restart method particle swarm optimization(RMPSO)in the response of change of environment and fast convergence.

关键词： Particle Swarm Optimization Dynamic Environment Convergence

作者: Changcheng Xiang Xuegang Tan Yi Yang

作者单位: Key Laboratory of Biologic Resources Protection and Utilization,Hubei Minzu University,Enshi,Hubei,4 College of Science,Hubei Minzu University,Enshi,445000,China

会议类型: 国际会议

会议名称: 第26届中国控制与决策会议(2014 CCDC)

会议地点: 长沙

会议语种:英文

页码: 3098-3102

在线出版日期: 2014-05-31（万方平台首次上网日期，不代表论文的发表时间）