%0 Journal Article
%T Spatially-Structured Sharing Technique for Multimodal Problems
%A Grant Dick Peter Whigham
%A <br>Grant Dick
%A Peter Whigham
%J 计算机科学技术学报
%D 2008
%I 
%X Spatially-structured populations are one approach to increasing genetic diversity in an evolutionary algorithm (EA). However, they are susceptible to convergence to a single peak in a multimodal fitness landscape. Niching methods, such as fitness sharing, allow an EA to maintain multiple solutions in a single population, however they have rarely been used in conjunction with spatially-structured populations. This paper introduces local sharing, a method that applies sharing to the overlapping demes of a spatially-structured population. The combination of these two methods succeeds in maintaining multiple solutions in problems that have previously proved difficult for sharing alone (and vice-versa).
%K evolutionary algorithm
%K multimodal problem domain
%K sharing
%K spatially-structured population<br>进化算法
%K 多形态问题
%K 分配
%K 空间结构
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=F57FEF5FAEE544283F43708D560ABF1B&aid=C3B6E6EBBD9CB08555FE06FEF1B124AA&yid=67289AFF6305E306&vid=EA389574707BDED3&iid=CA4FD0336C81A37A&sid=0401E2DB1F51F8DE&eid=228A710F49B6CE58&journal_id=1000-9000&journal_name=计算机科学技术学报&referenced_num=0&reference_num=32