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Production and Inventory Model Using Net Present Value

Author

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  • Daning Sun

    (Department of Information Systems, Lingnan University, Tuen Mun, Hong Kong, and Faculty of Commerce, University of British Columbia, Vancouver, British Columbia, Canada V6T 1Z2)

  • Maurice Queyranne

    (Faculty of Commerce, University of British Columbia, Vancouver, British Columbia, Canada V6T 1Z2)

Abstract

Using the net present value is the standard methodology in theoretical analysis, and the most frequently used method for making financial decisions. However, net present value is rarely used in production and inventory decisions. The main reasons appear to be the complexity of the formulae and the robustness of the EOQ model. We investigate the general multiproduct, multistage production and inventory model using the net present value of its total cost as the objective function. A power-of-two heuristic gives us a near optimal solution to this problem. If the base period is fixed (or varied), the solution based on the best power-of-two heuristic will be within 6.2% (or 2.1% ) of the optimal. This result is surprisingly similar to models using the long-term average cost. The average cost does not reflect the time value of money. Does this mean that decisions based on average cost are significantly inferior to those based on net present value? The answer is quite surprising. If we include discounted production cost in the holding cost, it turns out that the decision based on average cost is only 9.6% (in terms of the net present value of the total cost) worse than the decision based on the net present value. However, the reorder interval based on the average cost could be much longer than that derived using net present value. This result shows that average cost is a good approximation to the net present value when the demands are deterministic.

Suggested Citation

  • Daning Sun & Maurice Queyranne, 2002. "Production and Inventory Model Using Net Present Value," Operations Research, INFORMS, vol. 50(3), pages 528-537, June.
  • Handle: RePEc:inm:oropre:v:50:y:2002:i:3:p:528-537
    DOI: 10.1287/opre.50.3.528.7744
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    References listed on IDEAS

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    1. Derek Atkins & Maurice Queyranne & Daning Sun, 1992. "Lot Sizing Policies for Finite Production Rate Assembly Systems," Operations Research, INFORMS, vol. 40(1), pages 126-141, February.
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    Cited by:

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    3. Serrano, Alejandro & Oliva, Rogelio & Kraiselburd, Santiago, 2017. "On the cost of capital in inventory models with deterministic demand," International Journal of Production Economics, Elsevier, vol. 183(PA), pages 14-20.
    4. Ghiami, Yousef, 2023. "An analysis on production and inventory models with discounted cash-flows," Omega, Elsevier, vol. 117(C).
    5. Giri, B. C. & Dohi, T., 2004. "Optimal lot sizing for an unreliable production system based on net present value approach," International Journal of Production Economics, Elsevier, vol. 92(2), pages 157-167, November.
    6. P. Majumder & U. K. Bera & M. Maiti, 2020. "An EPQ model of substitutable products under trade credit policy with stock dependent and random substitution," OPSEARCH, Springer;Operational Research Society of India, vol. 57(4), pages 1205-1243, December.
    7. B C Giri & T Dohi, 2005. "Exact formulation of stochastic EMQ model for an unreliable production system," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(5), pages 563-575, May.
    8. Beullens, Patrick & Janssens, Gerrit K., 2011. "Holding costs under push or pull conditions - The impact of the Anchor Point," European Journal of Operational Research, Elsevier, vol. 215(1), pages 115-125, November.
    9. Liu, Zugang & Cruz, Jose M., 2012. "Supply chain networks with corporate financial risks and trade credits under economic uncertainty," International Journal of Production Economics, Elsevier, vol. 137(1), pages 55-67.
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    11. Chen, Liang-Tu, 2014. "Optimal dynamic policies for integrated production and marketing planning in business-to-business marketplaces," International Journal of Production Economics, Elsevier, vol. 153(C), pages 46-53.

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