Evolving knowledge for the solution of clustering problems in cellular manufacturing

Hierarchical clustering has been widely used for the solution of problems in the area of cellular manufacturing. Hierarchical clustering procedures utilize coefficients that quantify the level of similarity between pairs of machines or parts in the plant. An evolutionary methodology is proposed for the construction of new similarity coefficients that can be used by standard hierarchical clustering methodologies for the solution of cell-formation problems. A typical application is presented for the simplest case of the cell-formation problem. However, alternative similarity coefficients can be evolved for advanced formulations of the problem by suitably modifying the set of fitness cases that constitute the environment of the evolutionary process.