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Reorder level determination with serially-correlated demand

Author

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  • T L Urban

    (The University of Tulsa)

Abstract

This research analyses the effect of serially-correlated demand on the determination of appropriate reorder levels. While previous research has investigated this effect on the required levels of safety stock, the consequence of autocorrelation on the expected demand during lead time has been ignored. In this paper we examine the determination of accurate reorder levels for first-order autoregressive and moving average demand processes. A numeric analysis is then conducted to evaluate the effect of serial correlation on the service level provided, and indicates that existing approaches of managing serially-correlated demand can result in excessive inventories and shortages for high levels of autocorrelation.

Suggested Citation

  • T L Urban, 2000. "Reorder level determination with serially-correlated demand," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 51(6), pages 762-768, June.
    • Handle: RePEc:pal:jorsoc:v:51:y:2000:i:6:d:10.1057_palgrave.jors.2600945
    DOI: 10.1057/palgrave.jors.2600945
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    Citations

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    Cited by:

    1. Chandra, Charu & Grabis, Janis, 2008. "Inventory management with variable lead-time dependent procurement cost," Omega, Elsevier, vol. 36(5), pages 877-887, October.
    2. Trapero, Juan R. & Cardós, Manuel & Kourentzes, Nikolaos, 2019. "Empirical safety stock estimation based on kernel and GARCH models," Omega, Elsevier, vol. 84(C), pages 199-211.
    3. T C E Cheng & Y N Wu, 2005. "The impact of information sharing in a two-level supply chain with multiple retailers," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 56(10), pages 1159-1165, October.
    4. Kumar, Anupam & Evers, Philip T., 2015. "Setting safety stock based on imprecise records," International Journal of Production Economics, Elsevier, vol. 169(C), pages 68-75.
    5. Nasr, Walid W. & Maddah, Bacel, 2015. "Continuous (s, S) policy with MMPP correlated demand," European Journal of Operational Research, Elsevier, vol. 246(3), pages 874-885.
    6. Chandra, Charu & Grabis, Janis, 2005. "Application of multi-steps forecasting for restraining the bullwhip effect and improving inventory performance under autoregressive demand," European Journal of Operational Research, Elsevier, vol. 166(2), pages 337-350, October.
    7. Sarah M. Ryan, 2003. "Capacity expansion with lead times and autocorrelated random demand," Naval Research Logistics (NRL), John Wiley & Sons, vol. 50(2), pages 167-183, March.
    8. Hamister, James W. & Suresh, Nallan C., 2008. "The impact of pricing policy on sales variability in a supermarket retail context," International Journal of Production Economics, Elsevier, vol. 111(2), pages 441-455, February.
    9. Halkos, George & Kevork, Ilias, 2013. "Forecasting the optimal order quantity in the newsvendor model under a correlated demand," MPRA Paper 44189, University Library of Munich, Germany.
    10. Urban, Timothy L., 2005. "A periodic-review model with serially-correlated, inventory-level-dependent demand," International Journal of Production Economics, Elsevier, vol. 95(3), pages 287-295, March.

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