%0 Journal Article
%T Artificial immune network multi-agent optimization strategy for dynamic environment<br>动态环境的人工免疫网络多Agent优化策略
%A SHI Xu-hua
%A QIAN Feng
%A <br>史旭华
%A 钱锋
%J 控制理论与应用
%D 2011
%I 
%X Based on the idea of biological immune network and multi-agent technology, an artificial immune network multi-agent optimization strategy for dynamic environment(Dmaopt-aiNet) is proposed. The strategy with the target of global optimization introduces neighborhood clonal selection, neighborhood competition and neighborhood collaborative operators. Simultaneously, self-confidence of each agent can be automatically adjusted. In the optimizing process, some strategies such as double-agent network structure, double-mutation strategy and dynamic environmental monitoring are involved. Theoretical analysis shows that Dmaopt-aiNet algorithm is global convergence. Experimental results and comparison illustrate that Dmaopt-aiNet in dealing with high-dimensional dynamic optimization problems is more superior and can accurately determines the location of the optimum with good effectiveness and efficiency.
%K immune network
%K multi-agent
%K dynamic environment
%K optimization<br>免疫网络
%K 多Agent
%K 动态环境
%K 优化
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=970898A57DFC021F93AB51667BAED7F7&aid=B3D98CE6B86D816DFE7EE0A9913D1336&yid=9377ED8094509821&vid=D3E34374A0D77D7F&iid=DF92D298D3FF1E6E&sid=9BA5B7BDD4CE0596&eid=8587C7CAA7A3D0DB&journal_id=1000-8152&journal_name=控制理论与应用&referenced_num=0&reference_num=25