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EPQ models with varying setup cost

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  • Darwish, M.A.

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.

Suggested Citation

  • Darwish, M.A., 2008. "EPQ models with varying setup cost," International Journal of Production Economics, Elsevier, vol. 113(1), pages 297-306, May.
  • Handle: RePEc:eee:proeco:v:113:y:2008:i:1:p:297-306
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    References listed on IDEAS

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    Cited by:

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    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. Javad Sadeghi & Seyed Taghi Akhavan Niaki & Mohammad Reza Malekian & Saeid Sadeghi, 2016. "Optimising multi-item economic production quantity model with trapezoidal fuzzy demand and backordering: two tuned meta-heuristics," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 10(2), pages 170-195.
    4. Glock, Christoph H. & Grosse, Eric H., 2021. "The impact of controllable production rates on the performance of inventory systems: A systematic review of the literature," European Journal of Operational Research, Elsevier, vol. 288(3), pages 703-720.
    5. 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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