%0 Journal Article
%T Multi-model function optimization based on immune clonal memetic algorithm<br>免疫文化基因算法求解多模态函数优化问题
%A LIU He-an
%A ZHANG Qun-hui
%A <br>刘合安
%A 张群慧
%J 计算机应用研究
%D 2012
%I 
%X For finding all the extreme solutions for multi-model function optimization, this paper proposed an immune clonal optimization memetic algorithm. The algorithm used the danger signal to adaptively guide the clonal, mutation and selection operators. And it also used the Baldwin learning mechanism for the local search, to enhance the searching ability for the best solutions. The experimental results show that the algorithm has higher precise solution.
%K immune optimization
%K multi-model function
%K memetic algorithm
%K danger signal<br>免疫优化
%K 多模函数
%K 文化基因算法
%K 危险信号
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=8D8174D12B4331BF18C6E69C2D86EF2D&yid=99E9153A83D4CB11&vid=771469D9D58C34FF&iid=59906B3B2830C2C5&sid=0E45B776841B116A&eid=64D4A64EBB3B6E7E&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=15