A Study of Genetic Algorithms Using Fuzzy Clustering

Abstract

Lots of Genetic Algorithms (GA), such as distributed or parallel methods, have been proposed. These GA methods classified into two types. One type is a coarse grained GA. The other type is a fine grained GA. The individuals of both methods are classified by crisp clustering. Therefore, we can see the GA method using fuzzy clustering as one of the new approaches for distributed or parallel GA methods. In this paper, we propose the GA method using fuzzy clustering. We also discuss about behaviors of our GA via experiments of a function optimization problem.