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Dynamic Modeling of Inventories Subject to Obsolescence

Author

Listed:
  • George W. Brown

    (University of California at Los Angeles)

  • John Y. Lu

    (IBM Federal Systems Division, Bethesda, Maryland)

  • Robert J. Wolfson

    (The RAND Corporation, Santa Monica, California)

Abstract

A class of models for optimizing inventory costs is presented which takes account of stochastic obsolescence of an inventory item. Obsolescence is defined as a demand state, in such a fashion as to permit appraisal, ex ante, of the probability of arrival of obsolescence at future times, under the assumption that there are many possible states of demand. Response to obsolescence is introduced by means of a Bayesian procedure. In the most complete model this is done by modification of the state probability vector of a Markov process. Optimization is accomplished by means of a dynamic program.

Suggested Citation

  • George W. Brown & John Y. Lu & Robert J. Wolfson, 1964. "Dynamic Modeling of Inventories Subject to Obsolescence," Management Science, INFORMS, vol. 11(1), pages 51-63, September.
    • Handle: RePEc:inm:ormnsc:v:11:y:1964:i:1:p:51-63
    DOI: 10.1287/mnsc.11.1.51
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    Citations

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    Cited by:

    1. Pinçe, Çerag & Dekker, Rommert, 2011. "An inventory model for slow moving items subject to obsolescence," European Journal of Operational Research, Elsevier, vol. 213(1), pages 83-95, August.
    2. Pinçe, C. & Dekker, R., 2010. "A Continuous Review Inventory Model with Advance Policy Change and Obsolescence," Econometric Institute Research Papers EI 2009-45, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    3. van Jaarsveld, W.L., 2010. "Estimating obsolescence risk from demand data - a case study," Econometric Institute Research Papers EI 2010-03, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    4. Israel David & Eitan Greenshtein & Avraham Mehrez, 1997. "A dynamic‐programming approach to continuous‐review obsolescent inventory problems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 44(8), pages 757-774, December.
    5. Song, Yuyue & Lau, Hoong Chuin, 2004. "A periodic-review inventory model with application to the continuous-review obsolescence problem," European Journal of Operational Research, Elsevier, vol. 159(1), pages 110-120, November.
    6. Higgins, Matthew J. & Yan, Xin & Chatterjee, Chirantan, 2021. "Unpacking the effects of adverse regulatory events: Evidence from pharmaceutical relabeling," Research Policy, Elsevier, vol. 50(1).
    7. Fleischhacker, Adam J. & Zhao, Yao, 2011. "Planning for demand failure: A dynamic lot size model for clinical trial supply chains," European Journal of Operational Research, Elsevier, vol. 211(3), pages 496-506, June.
    8. Markus Emsermann & Burton Simon, 2007. "Optimal Control of an Inventory with Simultaneous Obsolescence," Interfaces, INFORMS, vol. 37(5), pages 445-454, October.
    9. van Delft, Ch. & Vial, J. P., 1996. "Discounted costs, obsolescence and planned stockouts with the EOQ formula," International Journal of Production Economics, Elsevier, vol. 44(3), pages 255-265, July.
    10. van Jaarsveld, Willem & Dekker, Rommert, 2011. "Estimating obsolescence risk from demand data to enhance inventory control--A case study," International Journal of Production Economics, Elsevier, vol. 133(1), pages 423-431, September.
    11. Cobbaert, Koen & Van Oudheusden, Dirk, 1996. "Inventory models for fast moving spare parts subject to "sudden death" obsolescence," International Journal of Production Economics, Elsevier, vol. 44(3), pages 239-248, July.
    12. Bourquard, Brian A. & Bereguer, Gemma & Gray, Allan W. & Preckel, Paul, 2017. "Raw Material Variability in Food Manufacturing," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258268, Agricultural and Applied Economics Association.
    13. Cattani, Kyle D. & Souza, Gilvan C., 2003. "Good buy? Delaying end-of-life purchases," European Journal of Operational Research, Elsevier, vol. 146(1), pages 216-228, April.
    14. Bradley R. Staats & Diwas S. KC & Francesca Gino, 2018. "Maintaining Beliefs in the Face of Negative News: The Moderating Role of Experience," Management Science, INFORMS, vol. 64(2), pages 804-824, February.

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