Multi-Modal Search with Convex Bounding Neighbourhood

摘要：

This paper presents a new dynamic method of subpopulation in solving multi-modal search problems with evolutionary algorithms. The new method identify the modes found at each generation and equalises the subpopulation sizes assigned to each mode. Modes are identified sequentially starting with the highest fitness mode. Mode membership is determined by successive grouping of fitness dominated convex bounding neighbours, starting from the fittest individual. This new dynamic modal subpopulation approach is able to fmd a representative sample of optima for multi-modal landscape with infinite number of global and local optima with uneven heights and non-uniform distribution. The algorithm also facilitates parallel implementation.

关键词： Multi-modal search evolutionary computation parallel algorithm subpopulation techniques

作者: D.H.M.NGUYEN K.P.WONG C.Y.CHUNG

作者单位: School of Engineering Science, Murdoch University Computational Intelligence Applications Research Laboratory, Department of Electrical Engineering,Th

会议类型: 国际会议

会议名称: 2006 International Conference on Machine Learning and Cybernetics(IEEE第五届机器学习与控制论坛)

会议地点: 大连

会议语种:英文

页码: 2081-2086

在线出版日期: 2006-08-13（万方平台首次上网日期，不代表论文的发表时间）