%0 Journal Article
%T Memetic algorithms in dynamic environments<br>动态环境中的Memetic算法
%A WANG Hong-feng
%A WANG Ding-wei
%A HUANG Min
%A <br>王洪峰
%A 汪定伟
%A 黄敏
%J 控制理论与应用
%D 2010
%I 
%X Based on particle swarm optimization(PSO), we propose a memetic algorithm for solving dynamic optimization problems which are widely concerned from the evolutionary computation community. In this algorithm, a fuzzy cognition local search method is employed for improving the quality of individuals and a self-organized random immigrant scheme is used to further enhance the exploration capacity in a local version of PSO with a ring-shape topology structure. Experimental study over a series of dynamic test benchmark problems shows that the proposed PSO-based Memetic algorithm is robust and adaptable in the dynamic environments.
%K Memetic algorithm
%K PSO
%K local search
%K dynamic optimization problem<br>Memetic算法
%K 粒子群优化算法
%K 局域搜索
%K 动态优化问题
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=ED61EB2874B72CFBE64983C1064C8D06&yid=140ECF96957D60B2&vid=DB817633AA4F79B9&iid=5D311CA918CA9A03&sid=6B1D468AD7B8ADD8&eid=305A58D956DD6BAF&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=0&reference_num=0