Safety stock determination with serially correlated demand in a periodic-review inventory system

John M. Charnes, Howard Marmorstein, Walter Zinn

Research output: Contribution to journalArticle

24 Scopus citations

Abstract

We consider a periodic-review inventory replenishment model with an order-up-to-/? operating doctrine for the case of deterministic lead times and a covariance-stationary stochastic demand process. A method is derived for setting the inventory safety stock to achieve an exact desired stockout probability when the autocovariance function for Gaussian demand is known. Because the method does not require that parametric time-series models be fit to the data, it is easily implemented in practice. Moreover, the method is shown to be asymptotically valid when the autocovariance function of demand is estimated from historical data. The effects on the stockout rate of various levels of autocorrelated demand are demonstrated for situations in which autocorrelation in demand goes undetected or is ignored by the inventory manager. Similarly, the changes to the required level of safety stock are demonstrated for varying levels of autocorrelation.

Original languageEnglish (US)
Pages (from-to)1006-1013
Number of pages8
JournalJournal of the Operational Research Society
Volume46
Issue number8
DOIs
StatePublished - Aug 1995

Keywords

  • Inventory

ASJC Scopus subject areas

  • Management Information Systems
  • Strategy and Management
  • Management Science and Operations Research
  • Marketing

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