%0 Journal Article
%T The global convergence analysis of particle swarm optimization algorithm based on Markov chain<br>马尔科夫链的粒子群优化算法全局收敛性分析
%A REN Zi-hui
%A WANG Jian
%A GAO Yue-lin
%A <br>任子晖
%A 王坚
%A 高岳林
%J 控制理论与应用
%D 2011
%I 
%X We analyze the global convergence of particle swarm optimization(PSO) algorithm. The one-step transition probabilities of particle velocity and particle position are calculated. Several properties about this Markov chain are investigated. The reducibility and nonhomogeneity are proved. It is shown that the particle state space is non-recurrent. These properties show the nonexistence of conditions for this Markov chain to be a stationary process. Thus, we con rm from the transition probability that the PSO algorithm is not global convergent.
%K particle swarm optimization(PSO)
%K transition probability
%K Markov chain
%K state space
%K global convergence<br>粒子群优化
%K 转移概率
%K Markov链
%K 状态空间
%K 全局收敛性
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=0CD9FECB0C9F583BD4D4AA4982B8A8B1&yid=9377ED8094509821&vid=D3E34374A0D77D7F&iid=E158A972A605785F&sid=8C5DE51F0A009A0F&eid=4D4C81DBA842B7BD&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=0&reference_num=20