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Abstract
This paper presents a comprehensive mathematical model and a genetic-algorithm-based heuristic for the formation of part families and machine cells in the design of cellular manufacturing systems. The model incorporates dynamic cell configuration, alternative routings, sequence of operations, multiple units of identical machines, machine capacity, workload balancing among cells, operation cost, subcontracting cost, tool consumption cost, set-up cost and other practical constraints. To solve this model efficiently, a two-phase genetic-algorithm-based heuristic was developed. In the first phase, independent cells are formed which are relatively simple to generate. In the second phase, the solution found during the first phase is gradually improved to generate cells optimizing inter-cell movement and other cost terms of the model. A number of numerical examples of different sizes are presented to demonstrate the computational efficiency of the heuristic developed.
Acknowledgement
This research is supported by a Discovery Grant from NSERC, Canada, and by the Faculty Research Support Fund from the Faculty of Engineering and Computer Science, Concordia University, Montreal, Quebec, Canada. The authors sincerely thank the two anonymous referees for their thorough review of and valuable comments on an early version of this paper.
