A genetic algorithm approach to cellular manufacturing systems

Abstract

A genetic algorithm (GA) metaheuristic-based cell formation procedure is presented in this paper. The cell formation problem solved here is to simultaneously group machines and part-families into cells so that intercellular movements are minimized. An option for considering the minimization of cell load variation is included and another, which combines minimization of intercellular movements and cell load-variation, exists. The algorithm solves this problem through improving a cell configuration using the GA metaheuristic. The designer is allowed to specify the number of cells required a priori and impose lower and upper bounds on cell size. This makes the GA scheme flexible for solving the cell formation problems. The solution procedure was found to perform well on tested large-scale problems and published data sets. Moreover, the proposed procedure compares very favorably to a well-known algorithm, and another TSP-based heuristic available in the literature. The results of computational tests presented are very encouraging.