Perfect simulation of an inventory model for perishable products

William L Cooper, Richard L. Tweedie

Research output: Contribution to journalArticlepeer-review

1 Scopus citations


We study an inventory model for perishable products with a critical-number ordering policy under the assumption that demand for the product forms an i.i.d. sequence, so that the state of the system forms a Markov chain. Explicit calculation of the stationary distribution has proved impractical in cases where items have reasonably long lifetimes and for systems with large under-up-to levels. Using the recently developed coupling-from-the-past method, we introduce a technique to estimate the stationary distribution of the Markov chain via perfect simulation. The Markov chain that results from the use of a critical-number policy is particularly amenable to these simulation techniques, despite not being ordered in its initial state, since the recursive equations satisfied by the Markov chain enable us to identify specific demand patterns where the backward coupling occurs.

Original languageEnglish (US)
Pages (from-to)229-243
Number of pages15
JournalStochastic Models
Issue number2
StatePublished - 2002

Bibliographical note

Funding Information:
*Work supported in part by NSF Grant DMS-9803682. **Corresponding author. E-mail:


  • Coupling from the past
  • Inventory model
  • Markov chain
  • Perfect simulation


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