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A new solution for a dynamic cell formation problem with alternative routing and machine costs using simulated annealing

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  • R Tavakkoli-Moghaddam

    (University of Tehran
    The University of British Columbia)

  • N Safaei

    (Iran University of Science and Technology
    The University of British Columbia)

  • F Sassani

    (The University of British Columbia)

Abstract

This paper presents an integer-linear programming approach for a cell formation problem (CFP) in a dynamic environment with a multi-period planning horizon. The objectives are to minimize the inter-cell movement and machine costs simultaneously. In dynamic environments, the product mix and demand are different but deterministic in each period. As a consequence, the formed cells in the current period may not be optimal for the next period. Thus, the reconfiguration of cells is required. Reconfiguration consists of re-forming part families, machine groups, and machine relocation. The CFP belongs to the category of NP-hard problems, thus we develop an efficient simulated annealing (SA) method to solve such a problem. The proposed mathematical model is optimally solved and the associated results are compared with the results obtained by the SA run. The results show that the gap between optimal and SA solutions is less than 4%, which indicates the efficiency of the developed SA scheme.

Suggested Citation

  • 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.
    • Handle: RePEc:pal:jorsoc:v:59:y:2008:i:4:d:10.1057_palgrave.jors.2602436
    DOI: 10.1057/palgrave.jors.2602436
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    References listed on IDEAS

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    1. Montreuil, Benoit & Laforge, Andree, 1992. "Dynamic layout design given a scenario tree of probable futures," European Journal of Operational Research, Elsevier, vol. 63(2), pages 271-286, December.
    2. W.E. Wilhelm & C.C. Chiou & D.B. Chang, 1998. "Integrating design and planning considerations in cellular manufacturing," Annals of Operations Research, Springer, vol. 77(0), pages 97-107, January.
    3. 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.
    4. Caux, C. & Bruniaux, R. & Pierreval, H., 2000. "Cell formation with alternative process plans and machine capacity constraints: A new combined approach," International Journal of Production Economics, Elsevier, vol. 64(1-3), pages 279-284, March.
    5. Adil, Gajendra K. & Rajamani, Divakar & Strong, Doug, 1993. "A mathematical model for cell formation considering investment and operational costs," European Journal of Operational Research, Elsevier, vol. 69(3), pages 330-341, September.
    6. Xambre, Ana R. & Vilarinho, Pedro M., 2003. "A simulated annealing approach for manufacturing cell formation with multiple identical machines," European Journal of Operational Research, Elsevier, vol. 151(2), pages 434-446, December.
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    Cited by:

    1. Papaioannou, Grammatoula & Wilson, John M., 2010. "The evolution of cell formation problem methodologies based on recent studies (1997-2008): Review and directions for future research," European Journal of Operational Research, Elsevier, vol. 206(3), pages 509-521, November.

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