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The (s, Q) inventory model with Erlang lead time and deterministic demand

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Listed:
  • Jeon G. Kim
  • Daewon Sun
  • Xin James He
  • Jack C. Hayya

Abstract

We develop a simple, approximately optimal solution to a model with Erlang lead time and deterministic demand. The method is robust to misspecification of the lead time and has good accuracy. We compare our approximate solution to the optimal for the case where we have prior information on the lead‐time distribution, and another where we have no information, except for computer‐generated sample data. It turns out that our solution is as easy as the EOQ's, with an accuracy rate of 99.41% when prior information on the lead‐time distribution is available and 97.54–99.09% when only computer‐generated sample information is available. Apart from supplying the inventory practitioner with an easy heuristic, we gain insights into the efficacy of stochastic lead time models and how these could be used to find the cost and a near‐optimal policy for the general model, where both demand rate and lead time are stochastic. © 2004 Wiley Periodicals, Inc. Naval Research Logistics, 2004

Suggested Citation

  • Jeon G. Kim & Daewon Sun & Xin James He & Jack C. Hayya, 2004. "The (s, Q) inventory model with Erlang lead time and deterministic demand," Naval Research Logistics (NRL), John Wiley & Sons, vol. 51(6), pages 906-923, September.
    • Handle: RePEc:wly:navres:v:51:y:2004:i:6:p:906-923
    DOI: 10.1002/nav.20032
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    References listed on IDEAS

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    2. John P. Saldanha & Bradley S. Price & Douglas J. Thomas, 2023. "A nonparametric approach for setting safety stock levels," Production and Operations Management, Production and Operations Management Society, vol. 32(4), pages 1150-1168, April.

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