Machine-part cell formation for maximum grouping efficacy based on genetic algorithm

Cellular manufacturing system (CMS) makes use of application of group technology. The objective of cell formation problems (CFP) in CMS is to identify part families and machine cells in order to minimize the intercellular movement and to maximize the machine utilization within a cell. Previous study in CFP generally focused on maximizing grouping efficacy (GC) by minimizing exceptional elements as well as void elements. In this paper, a genetic algorithm heuristic is presented. Computational experiments were carried out with 20 benchmark problem sets. Computational results show that the proposed heuristic has shown to produce solutions in terms of GC that are either better than or competitive with the existing algorithms.