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.
2009 JSAI (The Japanese Society for Artificial Intelligence)