Spatially-Structured Sharing Technique for Multimodal Problems

作     者：Grant Dick Peter Whigham 

作者机构：Department of Information ScienceUniversity of OtagoDunedin 

出 版 物：《Journal of Computer Science & Technology》 (计算机科学技术学报（英文版）)

年 卷 期：2008年第23卷第1期

页      面：64-76页

核心收录：

学科分类：08[工学] 081202[工学-计算机软件与理论] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：evolutionary algorithm multimodal problem domain sharing spatially-structured population 

摘      要：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）.