Evolving similarity coefficients for the solution of cellular manufacturing problems

The cell formation problem is a classic manufacturing optimization problem associated with the implementation of a cellular manufacturing system. A variety of hierarchical clustering procedures have been proposed for the solution of this problem. Essential for the operation of a clustering procedure is the determination of a form of similarity between the objects that are going to be grouped. In this paper we employ a Genetic Programming algorithm for the evolution of new similarity coefficients for the solution of simple cell formation problems. Evolved coefficients are tested against the well-known Jaccard's similarity coefficient on a large number of problems taken from the literature.