文章基本信息

标题：Analysis of the Performance of Genetic Multi-Step Search in Interpolation and Extrapolation Domain
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作者：Yoshiko Hanada ; Tomoyuki Hiroyasu ; Mitsuji Muneyasu 等
期刊名称：人工知能学会論文誌
印刷版ISSN：1346-0714
电子版ISSN：1346-8030
出版年度：2009
卷号：24
期号：1
页码：136-146
DOI：10.1527/tjsai.24.136
出版社：The Japanese Society for Artificial Intelligence
摘要：In combinatorial problems Genetic Algorithms (GAs) actualize effectual searches using genetic operators for inheritance and acquisition of characteristics. These two classes of search, focusing on inheritance or acquisition, are called, respectively, the interpolation search and the extrapolation search by introducing a distance measure. dMSXF and dMSMF is a promising interpolation/extrapolation-directed method based on neighborhood search. The previous experiments qualitatively demonstrated the effectiveness of dMSXF+dMSMF, under using sophisticated neighborhood structures and distance metrics that adequately perceive the characteristics of each problem. In this paper, we analyse overall local search performance and behavior of dMSXF and dMSMF with NK model which explains various intrinsic structures observed in combinatorial problems. In addition, parameter presumption of dMSXF and dMSMF are discussed focusing on the correlation length which is one of indicators for the epistasis intensity.
关键词：genetic algorithm ; local search ; combinatorial optimization ; performance analysis ; NK Model