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A mathematical programming model for system reconfiguration in a dynamic cellular manufacturing environment

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  • Mingyuan Chen

Abstract

In a dynamic manufacturing environment, manufacturing cell configurations based on current part mix and production process may need to be revised once the part mix or the production process has changed. However, machine and equipment moving costs make frequent reconfiguration uneconomical and sometimes impossible. Designing a sustainable cellular manufacturing system in a dynamic environment is studied in this paper. An integer programming model is developed to minimize material handling and machine costs as well as cell reconfiguration cost for a planning horizon of multiple time periods. Solving this integer programming problem is NP-complete. A decomposition approach is developed so that the decomposed subproblems can be solved with less computational effort. Dynamic programming is then employed to find a solution of the original problem. Numerical examples are presented to illustrate the model and the solution technique developed in this paper. Copyright Kluwer Academic Publishers 1998

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  • Mingyuan Chen, 1998. "A mathematical programming model for system reconfiguration in a dynamic cellular manufacturing environment," Annals of Operations Research, Springer, vol. 77(0), pages 109-128, January.
    • Handle: RePEc:spr:annopr:v:77:y:1998:i:0:p:109-128:10.1023/a:1018917109580
    DOI: 10.1023/A:1018917109580
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    Cited by:

    1. Defersha, Fantahun M. & Chen, Mingyuan, 2006. "A comprehensive mathematical model for the design of cellular manufacturing systems," International Journal of Production Economics, Elsevier, vol. 103(2), pages 767-783, October.
    2. Ah kioon, Steve & Bulgak, Akif Asil & Bektas, Tolga, 2009. "Integrated cellular manufacturing systems design with production planning and dynamic system reconfiguration," European Journal of Operational Research, Elsevier, vol. 192(2), pages 414-428, January.
    3. Arzi, Yohanan & Bukchin, Joseph & Masin, Michael, 2001. "An efficiency frontier approach for the design of cellular manufacturing systems in a lumpy demand environment," European Journal of Operational Research, Elsevier, vol. 134(2), pages 346-364, October.
    4. Safaei, N. & Saidi-Mehrabad, M. & Jabal-Ameli, M.S., 2008. "A hybrid simulated annealing for solving an extended model of dynamic cellular manufacturing system," European Journal of Operational Research, Elsevier, vol. 185(2), pages 563-592, March.
    5. Defersha, Fantahun M. & Chen, Mingyuan, 2008. "A linear programming embedded genetic algorithm for an integrated cell formation and lot sizing considering product quality," European Journal of Operational Research, Elsevier, vol. 187(1), pages 46-69, May.
    6. Safaei, Nima & Tavakkoli-Moghaddam, Reza, 2009. "Integrated multi-period cell formation and subcontracting production planning in dynamic cellular manufacturing systems," International Journal of Production Economics, Elsevier, vol. 120(2), pages 301-314, August.
    7. R Tavakkoli-Moghaddam & N Safaei & F Sassani, 2008. "A new solution for a dynamic cell formation problem with alternative routing and machine costs using simulated annealing," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(4), pages 443-454, April.

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