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The Role of Items Quantity Constraint to Control the Optimal Economic Order Quantity

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  • Karzan Ghafour

Abstract

The obligation or the traditional question in inventory models is how much or how many of inventory items to order. In inventory control, the economic order quantity, EOQ is varies from model to another based on the variables and assumptions. This paper develops the EOQ using two deterministic inventory models (Purchases model and production model with shortage) of multi-items when the objective function is subjected to a constrained number of items quantities. The constraints are supposed to be active if the left-hand side does not satisfy the right-hand side condition. Thus, to achieve the new formula of multi-item EOQ in each of the two models with the constraint, Lagrange method have been used. Finally, to provide the proposed model a numerical example has been used.

Suggested Citation

  • Karzan Ghafour, 2017. "The Role of Items Quantity Constraint to Control the Optimal Economic Order Quantity," Modern Applied Science, Canadian Center of Science and Education, vol. 11(9), pages 1-61, September.
    • Handle: RePEc:ibn:masjnl:v:11:y:2017:i:9:p:61
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    References listed on IDEAS

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    1. Goyal, Suresh Kumar & Cardenas-Barron, Leopoldo Eduardo, 2002. "Note on: Economic production quantity model for items with imperfect quality - a practical approach," International Journal of Production Economics, Elsevier, vol. 77(1), pages 85-87, May.
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    4. Wee, H.M. & Yu, Jonas & Chen, M.C., 2007. "Optimal inventory model for items with imperfect quality and shortage backordering," Omega, Elsevier, vol. 35(1), pages 7-11, February.
    5. Khan, Mehmood & Jaber, Mohamad Y. & Bonney, Maurice, 2011. "An economic order quantity (EOQ) for items with imperfect quality and inspection errors," International Journal of Production Economics, Elsevier, vol. 133(1), pages 113-118, September.
    6. Leroy B. Schwarz, 2008. "The Economic Order-Quantity (EOQ) Model," International Series in Operations Research & Management Science, in: Dilip Chhajed & Timothy J. Lowe (ed.), Building Intuition, chapter 8, pages 135-154, Springer.
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    Cited by:

    1. Karzan Mahdi Ghafour & Abdulqadir Rahomee Ahmed Aljanabi, 2023. "The role of forecasting in preventing supply chain disruptions during the COVID-19 pandemic: a distributor-retailer perspective," Operations Management Research, Springer, vol. 16(2), pages 780-793, June.

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    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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