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Evaluating the robustness of lead time demand models

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  • Rossetti, Manuel D.
  • Yasin Ünlü
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    Abstract

    This paper examines the robustness of lead time demand models for the continuous review (r, Q) inventory policy. A number of classic distributions, (e.g. normal, lognormal, gamma, Poisson and negative binomial) as well as distribution selection rules are examined under a wide variety of demand conditions. First, the models are compared to each other by assuming a known demand process and evaluating the errors associated with using a different model. Then, the models are examined using a large sample of simulated demand conditions. Approximation results of inventory performance measures--ready rate, expected number of backorders and on-hand inventory levels are reported. Results indicate that distribution selection rules have great potential for modeling the lead time demand.

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    Bibliographic Info

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

    Volume (Year): 134 (2011)
    Issue (Month): 1 (November)
    Pages: 159-176

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    Handle: RePEc:eee:proeco:v:134:y:2011:i:1:p:159-176

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

    Related research

    Keywords: Lead time demand distribution Distribution selection rule Highly variable demand Re-order point re-order quantity policies;

    References

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    1. Bartezzaghi, Emilio & Verganti, Roberto & Zotteri, Giulio, 1999. "Measuring the impact of asymmetric demand distributions on inventories," International Journal of Production Economics, Elsevier, vol. 60(1), pages 395-404, April.
    2. Eliezer Naddor, 1978. "Note--Sensitivity to Distributions in Inventory Systems," Management Science, INFORMS, vol. 24(16), pages 1769-1772, December.
    3. Tadikamalla, Pandu R, 1984. "A comparison of several approximations to the lead time demand distribution," Omega, Elsevier, vol. 12(6), pages 575-581.
    4. Katrien Ramaekers & Gerrit K. Janssens, 2008. "On the choice of a demand distribution for inventory management models," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 2(4), pages 479-491.
    5. Shore, Haim, 1999. "Optimal solutions for stochastic inventory models when the lead-time demand distribution is partially specified," International Journal of Production Economics, Elsevier, vol. 59(1-3), pages 477-485, March.
    6. Leven, Erik & Segerstedt, Anders, 2004. "Inventory control with a modified Croston procedure and Erlang distribution," International Journal of Production Economics, Elsevier, vol. 90(3), pages 361-367, August.
    7. Teunter, Ruud & Dekker, Rommert, 2008. "An easy derivation of the order level optimality condition for inventory systems with backordering," International Journal of Production Economics, Elsevier, vol. 114(1), pages 201-204, July.
    8. Heuts, R.M.J. & Lieshout, J.T.H.C. van & Baken, K., 1986. "An inventory model: What is the influence of the shape of the lead time demand distribution?," Research Memorandum 205, Tilburg University, Faculty of Economics and Business Administration.
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    Cited by:
    1. Mekhtiev, Mirza Arif, 2013. "Analytical evaluation of lead-time demand in polytree supply chains with uncertain demand, lead-time and inter-demand time," International Journal of Production Economics, Elsevier, vol. 145(1), pages 304-317.

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