Abstract
Cellular manufacturing is the implementation of group technology in the manufacturing process. A key issue during the design of a cellular manufacturing system is the configuration of machine cells and part families within the plant. In this paper we present a hierarchical clustering procedure for the solution of the cell-formation problem which is based on the use of Genetic Programming for the evolution of similarity coefficients between pairs of machines in the plant. The performance of the methodology is illustrated on a number of test problems taken from the literature.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Mitrovanov, S.P., 1966. The Scientific Principles of Group Technology, National Lending Library Translation, Boston Spa, Yorkshire, U.K.
Koza, J.R., 1992. Genetic Programming: On the programming of computers by means of natural selection. MIT Press. Cambridge.
Dimopoulos, C., and Zalzala AMS., 1999. Recent developments in evolutionary computation for manufacturing optimisation: problems, solutions and comparisons. IEEE Transactions in Evolutionary Computation, in print.
Burbidge, J.L., 1971. Production Flow Analysis. Production Engineer50: 139–152.
Singh, N., 1993. Cellular manufacturing systems: an invited review. European Journal of Operational Research69: 284–291.
Offodile, O.F., Mehrez, A., and Grznar, J., 1994. Cellular manufacturing: a taxonomic review framework. Journal of Maniefacturing Systems13: 196–220.
Selim, M.H., Askin, R.G., and Vakharia, A.J., 1998. Cell formation in group technology: review, evaluation and directions for future research. Computers & Industrial Engineering34: 3–20.
McAuley, J., 1972. Machine grouping for efficient production. Production Engineer 51:53–57.
Sharker, B.R., 1986. The resemblance coeficients in group technology: a survey and comparative study of relational metrics. Computers & Industrial Engineering30: 103–116.
Kumar, C.S., and Chandrasekharan, M.P., 1990. Grouping efficacy: a quantitative criterion for goodness of block diagonal forms of binary matrices in group technology. Int.J. of Production Research28: 603–612.
Chandrasekharan, M.P., and Rajagopalan, R., 1989. GROUPABILITY: an analysis of the properties of binary data matrices for group technology. Int.J. of Production Research27: 1035–1052.
Kumar, K.R., and Vannelli, A., 1987. Strategic subcontrcting for efficient disaggregated manufacturing. Int.J. of Production Research25: 1715–1728
Seifoddini, H., 1989. Single linkage vs. average linkage clustering in machine cells formation application. Computers & Industrial Engineering16: 419–426.
Stanfel, L.E., 1985. Machine clustering for economic production”, Engineering Costs & Production Economics9: 73–81.
Chandrasekharan, M.P., and Rajagopalan, R., 1987. ZODIAC-an algorithm for concurrent formation of part families and machine-cells. Int.J. of Production Research25: 835–850.
Srinivasan, G, and Narendran, T.T., 1991. GRAFICS-a nonhierarchical clustering algorithm for group technology. Int.J. of Production Research29: 463–478.
Cheng, C.H., Gupta, Y.P., Lee, W.H., and Wong, K.F., 1998. A TSP-based heuristic for forming machine groups and part families. Int.J. of Production Research36: 13251–337.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2000 Springer-Verlag London
About this paper
Cite this paper
Dimopoulos, C., Mort, N. (2000). A Genetic Programming-based Hierarchical Clustering Procedure for the solution of the Cell-Formation Problem. In: Parmee, I.C. (eds) Evolutionary Design and Manufacture. Springer, London. https://doi.org/10.1007/978-1-4471-0519-0_17
Download citation
DOI: https://doi.org/10.1007/978-1-4471-0519-0_17
Publisher Name: Springer, London
Print ISBN: 978-1-85233-300-3
Online ISBN: 978-1-4471-0519-0
eBook Packages: Springer Book Archive