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EPQ models with varying setup cost

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  • Darwish, M.A.
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    Abstract

    In this paper, the classical economic production quantity (EPQ) model is generalized by considering a relationship between the setup cost and the production run length. The dependency between the setup cost and run length can be related to process deterioration and learning and forgetting effects. Two models are developed, the first of which is for the case when shortages are not allowed and the other one permits shortages. The cost functions associated with these models are proved to be convex and optimal solutions are determined. Results show that the relationship between setup cost and production run length has a significant impact on the optimal lot size and average total cost in the EPQ model. Numerical examples are presented to demonstrate the utility of the models.

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    File URL: http://www.sciencedirect.com/science/article/B6VF8-4PTW4MM-3/1/14aa8378c9e6a503af1084aef307c0fd
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    Bibliographic Info

    Article provided by Elsevier in its journal International Journal of Production Economics.

    Volume (Year): 113 (2008)
    Issue (Month): 1 (May)
    Pages: 297-306

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    Handle: RePEc:eee:proeco:v:113:y:2008:i:1:p:297-306

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    Web page: http://www.elsevier.com/locate/ijpe

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    References

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    1. Willard I. Zangwill, 1987. "From EOQ Towards ZI," Management Science, INFORMS, vol. 33(10), pages 1209-1223, October.
    2. Freimer, Michael & Thomas, Douglas & Tyworth, John, 2006. "The value of setup cost reduction and process improvement for the economic production quantity model with defects," European Journal of Operational Research, Elsevier, vol. 173(1), pages 241-251, August.
    3. Jaber, Mohamad Y. & Bonney, Maurice, 2003. "Lot sizing with learning and forgetting in set-ups and in product quality," International Journal of Production Economics, Elsevier, vol. 83(1), pages 95-111, January.
    4. Yang, Jiaqin & Deane, Richard H., 1993. "Setup time reduction and competitive advantage in a closed manufacturing cell," European Journal of Operational Research, Elsevier, vol. 69(3), pages 413-423, September.
    5. John P. Leschke & Elliott N. Weiss, 1997. "The Multi-Item Setup-Reduction Investment-Allocation Problem with Continuous Investment-Cost Functions," Management Science, INFORMS, vol. 43(6), pages 890-894, June.
    6. Evan L. Porteus, 1985. "Investing in Reduced Setups in the EOQ Model," Management Science, INFORMS, vol. 31(8), pages 998-1010, August.
    7. Darwish, M.A. & Ben-Daya, M., 2007. "Effect of inspection errors and preventive maintenance on a two-stage production inventory system," International Journal of Production Economics, Elsevier, vol. 107(1), pages 301-313, May.
    8. Anne M. Spence & Evan L. Porteus, 1987. "Setup Reduction and Increased Effective Capacity," Management Science, INFORMS, vol. 33(10), pages 1291-1301, October.
    9. Jaber, Mohamad Y. & Bonney, Maurice, 1999. "The economic manufacture/order quantity (EMQ/EOQ) and the learning curve: Past, present, and future," International Journal of Production Economics, Elsevier, vol. 59(1-3), pages 93-102, March.
    10. Salameh, M. K. & Jaber, M. Y., 2000. "Economic production quantity model for items with imperfect quality," International Journal of Production Economics, Elsevier, vol. 64(1-3), pages 59-64, March.
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    Cited by:
    1. Dellino, Gabriella & Kleijnen, Jack P.C. & Meloni, Carlo, 2010. "Robust optimization in simulation: Taguchi and Response Surface Methodology," International Journal of Production Economics, Elsevier, vol. 125(1), pages 52-59, May.
    2. Guchhait, Partha & Kumar Maiti, Manas & Maiti, Manoranjan, 2013. "Production-inventory models for a damageable item with variable demands and inventory costs in an imperfect production process," International Journal of Production Economics, Elsevier, vol. 144(1), pages 180-188.
    3. Nadeau, Marie-Claude & Kar, Ashish & Roth, Richard & Kirchain, Randolph, 2010. "A dynamic process-based cost modeling approach to understand learning effects in manufacturing," International Journal of Production Economics, Elsevier, vol. 128(1), pages 223-234, November.

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