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An EOQ Model with Random Variations in Demand

Author

Listed:
  • Percy H. Brill

    (Faculty of Business Administration, University of Windsor, Ontario, Canada N9B 3P4)

  • Ben A. Chaouch

    (Faculty of Business Administration, University of Windsor, Ontario, Canada N9B 3P4)

Abstract

This paper presents a model that incorporates variations in the demand rate at random time points into the inventory planning decision. These changes in demand may occur due to economic recessions, labor strife starting or ending, or other events that result in a period of time during which the rate of demand is shifted up or down from its current level. The paper uses system-point level-crossing theory to derive expressions for the distribution and expected value of on-hand inventory, ordering rate, and the expected total cost rate for a given ordering policy. A sensitivity analysis is conducted, and a number of qualitative properties are provided to illustrate the use of the results to obtain optimal order quantities.

Suggested Citation

  • Percy H. Brill & Ben A. Chaouch, 1995. "An EOQ Model with Random Variations in Demand," Management Science, INFORMS, vol. 41(5), pages 927-936, May.
    • Handle: RePEc:inm:ormnsc:v:41:y:1995:i:5:p:927-936
    DOI: 10.1287/mnsc.41.5.927
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    Citations

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    Cited by:

    1. Roni, Mohammad S. & Eksioglu, Sandra D. & Jin, Mingzhou & Mamun, Saleh, 2016. "A hybrid inventory policy with split delivery under regular and surge demand," International Journal of Production Economics, Elsevier, vol. 172(C), pages 126-136.
    2. Mohebbi, Esmail, 2006. "A production-inventory model with randomly changing environmental conditions," European Journal of Operational Research, Elsevier, vol. 174(1), pages 539-552, October.
    3. Tien-Yu Lin & Kuo-Lung Hou, 2015. "An imperfect quality economic order quantity with advanced receiving," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 23(2), pages 535-551, July.
    4. Ben A. Chaouch, 2007. "Inventory control and periodic price discounting campaigns," Naval Research Logistics (NRL), John Wiley & Sons, vol. 54(1), pages 94-108, February.
    5. Mohebbi, E., 2008. "A note on a production control model for a facility with limited storage capacity in a random environment," European Journal of Operational Research, Elsevier, vol. 190(2), pages 562-570, October.
    6. Kevin Hsu, Wen-Kai & Yu, Hong-Fwu, 2009. "EOQ model for imperfective items under a one-time-only discount," Omega, Elsevier, vol. 37(5), pages 1018-1026, October.
    7. Arnoud den Boer & Ohad Perry & Bert Zwart, 2018. "Dynamic pricing policies for an inventory model with random windows of opportunities," Naval Research Logistics (NRL), John Wiley & Sons, vol. 65(8), pages 660-675, December.
    8. Roni, Mohammad S. & Jin, Mingzhou & Eksioglu, Sandra D., 2015. "A hybrid inventory management system responding to regular demand and surge demand," Omega, Elsevier, vol. 52(C), pages 190-200.
    9. Salameh, M. K. & Jaber, M. Y., 2000. "Economic production quantity model for items with imperfect quality," International Journal of Production Economics, Elsevier, vol. 64(1-3), pages 59-64, March.
    10. Azoury, Katy S. & Miyaoka, Julia, 2020. "Optimal and simple approximate solutions to a production-inventory system with stochastic and deterministic demand," European Journal of Operational Research, Elsevier, vol. 286(1), pages 178-189.
    11. Brill, Percy H. & Yu, Kaiqi, 2011. "Analysis of risk models using a level crossing technique," Insurance: Mathematics and Economics, Elsevier, vol. 49(3), pages 298-309.

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