%0 Journal Article
%T Improved particle swarm optimization based on genetic hybrid genes<br>基于遗传交叉因子的改进蜂群优化算法*
%A LUO Jun
%A FAN Peng-cheng
%A <br>罗钧
%A 樊鹏程
%J 计算机应用研究
%D 2009
%I 
%X A drawback of artificial bee colony algorithm is easily trapped in a local optimal solution.The paper presented an improved artificial bee colony algorithm based on genetic hybrid gene.The food sources were multiple by the selection and hybridization of genetic arithmetic.The import of hybrid genes improved excellent performance of particles and reduced likelihood on getting into local optimization.Experimental results show that the new algorithm can greatly improve the global convergence ability and enhance the rate of convergence.
%K bee colony algorithm
%K hybrid genes
%K nectar amounts
%K genetic arithmetic<br>蜂群算法
%K 交叉因子
%K 收益度
%K 遗传算法
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=08B14751C8A3D115EAC23214C3010133&yid=DE12191FBD62783C&vid=96C778EE049EE47D&iid=F3090AE9B60B7ED1&sid=25C4D6992F9AA731&eid=5722C61591BFF98C&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=7