%0 Journal Article
%T Research Progress on Intelligent Optimization Guidance Approaches Using Knowledge<br>基于知识的智能优化引导方法研究进展
%A XING Li-Ning
%A CHEN Ying-Wu
%A <br>邢立宁
%A 陈英武
%J 自动化学报
%D 2011
%I 
%X To improve the performance of intelligent optimization approaches, many researchers have used knowledge to strengthen the optimization process guidance. The intelligent optimization guidance using knowledge is reviewed in this work. The intelligent optimization guidance is normally executed via artificial intelligence approaches and special knowledge models. Also, some researchers have proposed algorithms which have a double layer evolution mechanism. These improved approaches can discover some knowledge from the previous iterations, then use the discoverd knowledge to guide the subsequent iterations.
%K Artificial intelligence
%K intelligent optimization approaches
%K guidance
%K global convergence
%K genetic algorithm
%K knowledge model<br>人工智能
%K 智能优化算法
%K 引导
%K 全局收敛
%K 遗传算法
%K 知识模型
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=E76622685B64B2AA896A7F777B64EB3A&aid=B3C7018AFD6E5639D58D4AF26734CACC&yid=9377ED8094509821&vid=42425781F0B1C26E&iid=708DD6B15D2464E8&sid=9A3A88A3A0B8496C&eid=80AD5907B47936EE&journal_id=0254-4156&journal_name=自动化学报&referenced_num=0&reference_num=54