Abstract
In the ideal case, cell design produces perfectly independent machine cells. That is, all operations of parts in a part family are completed within a single machine cell. However, the ideal case is rarely realized in practice. Very often, some of the parts in a part family have to move between machine cells to use machines in different cells. Consequently, the degree of machine cell independence is reduced by intercell moves.
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References
Askin, R.G. and Subramanian, S.P., 1987, A cost-based heuristic for group technology configuration, Internationaljournal of Production Research, 25, 101–113.
Askin, R.G. and Chiu, K., 1990, A graph partitioning procedure for machine assignment and cell formation, Internationaljournal of Production Research, 28, 1555–1572.
Ballakur, A. and Steudel, HJ., 1987, A within-cell utilization based heuristic for designing cellular manufacturing systems, International Journal of Production Research, 25, 639–665.
Boctor, F.F., 1991, A linear formulation of the machine-part cell formation problem, International Journal of Production Research, 29, 343–356.
Boe, W.J. and Cheng, C.H., 1991, A close neighbor algorithm for a designing cellular manufacturing system, International Journal of Production Research, 29, 2097–2116.
Bruns, R., 1993, Direct chromosome representation and advanced genetic operators for production scheduling. Proceedings of the Fifth International Conference on Genetic Algorithms, 352–359.
Burbidge, J.L., 1989, Production Flow Analysis, Clarendon Press, Oxford
Chandrasekharan, M.P. and Rajagopalan, R., 1987, ZODIAC — an algorithm for concurrent formation of part-families and machine-cells, International Journal of Production Research, 25, 835–850.
Chen, C.L, Cotruvo, N.A., and Baek, W., A simulated annealing solution to cell formation problem, Internationaljournal of Production Research, 33, 2601–2614.
Chen, S.J. and Cheng, C.S., 1995, A neural network-based cell formation algorithm in cellular manufacturnig, International Journal of Production Research, 33, 293–318.
Del Valle, A.G., Balarezo, S., and Tejero, J., 1994, A heuristic workload-based model to form cells by minimizing intercellular movements, International Journal of Production Research, 32, 2275–2285.
Fonseca, C.M. and Fleming, P.J., 1993, Genetic algorithms for multiobjective optimization: formulation, discussion and generalization, Proceedings of the Fifth International Conference on Genetic Algorithms, 416–423.
Gunasingh, R.K. and Lashkari, R.S., 1989, The cell formation problem in cellular manufacturing systems—a sequential modelling approach, Computers and Industrial Engineering, 16, 469–476.
Gupta, Y.P., Gupta, M.C., Kumar, A., and Sundaram, C., 1995, Minimizing total intercell and intracell moves in cellular manufacturing: a genetic algorithm approach, International Journal of Computer Integrated Manufacturing, 8, 92–101.
Gupta, Y.P., Gupta, M.C., Kumar, A., and Sundaram, C., 1996, A genetic algorithm-based approach to cell composition and layout design problems. International Journal of Production Research, 34, 447–482.
Harhalakis, G., Nagi, R., and Proth, J.M., 1990, An efficient heuristic in manufacturing cell formation for group technology applications. International Journal of Production Research, 28, 185–198.
Juliff, K., 1993, A multi-chromosome genetic algorithm for pallet loading, Proceedings of the Fifth International Conference on Genetic Algorithms, 467–473.
King, J.R., 1980, Machine-component group formation in production flow analysis: an approach using a rank order clustering algorithm, International Journal of Production Research, 18, 213–232.
King, J.R. and Nakornchai V., 1982, Machine-component group formation in group technology: review and extension, International Journal of Production Research, 20, 117–133.
Kusiak, A. and Chow, W.S., 1987, Efficient solving of the group technology problem, Journal of Manufacturing Systems, 6, 117–124.
Levine, D.M., 1993, A genetic algorithm for the set partitioning problem, Proceedings of the Fifth International Conference on Genetic Algorithms, 481–487.
Logendran, R., 1990, A workload based model for minimizing total intercell and intracell moves in cellular manufacturing, International Journal of Production Research, 28, 913–925.
Logendran, R., 1991, Impact of sequence of operations and layout of cells in cellular manufacturing, International Journal of Production Research, 29, 375–390.
McAuley, A., 1972, Machine grouping for efficient production, Production Engineer, 51, 53–57.
Michalewicz, Z., 1992, Genetic Algorithm + Data Structure = Evolution Programs, Springer-Verlag, Hong Kong.
Seifoddini, H. and Wolfe, P.M., 1986, Application of the similarity coefficient method in group technology, HE Transactions, 18, 271–277.
Srinivasan, G., 1994, A clustering algorithm for machine cell formation in group technology using minimum spanning trees, International Journal of Production Research, 32, 2149–2158.
Srinivasan, G. and Narendran T.T., 1991, GRAFICS—a nonhierarchical clustering algorithm for group technology, Internationaljournal of Production Research, 29, 463–478.
Stanfel, L.F., 1985, Machine clustering for economic production, Engineering Costs and Production Economics, 9, 73–81.
Tabucanon, M.T. and Ojha, R., 1987, ICRMA—a heuristic approach for intercell flow reduction in cellular manufacturing systems, Material Flow, 4, 189–190.
Venugopal, V. and Narendran, T.T., 1992, A genetic algorithm approach to the machine-component grouping problem with multiple objectives, Computers and Industrial Engineering, 22, 469–480.
Waghodekar P.H. and Sahu S., 1984, Machine-component cell formation in group technology: MACE, International Journal of Production Research, 22, 937–948.
Wei, J.C. and Gaither, N., 1990, A capacity constrained multiobjective cell formation method, Journal of Manufacturing Systems, 9, 222–232.
Whitley D., 1989, The GENITOR algorithm and selection pressure: why rank-based allocation of reproductive trails is best, Proceedings of the Third International Conference on Genetic Algorithms, 116–121.
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Cheng, C.H., Lee, W.H., Miltenburg, J. (1998). A Bi-Chromosome Genetic Algorithm For Minimizing Intercell and Intracell Moves. In: Suresh, N.C., Kay, J.M. (eds) Group Technology and Cellular Manufacturing. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-5467-7_12
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DOI: https://doi.org/10.1007/978-1-4615-5467-7_12
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