Technical note-managing nonperishable inventories with learning about demand arrival rate through stockout times

Alain Bensoussan, Pengfei Guo

Research output: Journal article publicationJournal articleAcademic researchpeer-review

Abstract

We study a periodic review inventory model with a nonperishable product over an infinite planning horizon. The demand for the nonperishable product arrives according to a Poisson process. Lost sales are unobservable but the stockout times are observable. We formulate the problem as a dynamic programming model with learning on arrival rate according to stockout times and further simplify it by using unnormalized probabilities. We then compare the system performance with those under other two information scenarios where lost sales are observable or both lost sales and stockout times are unobservable. We show that the optimal inventory order-up-to level with observable stockout times is larger than the one with observable lost sales. We also show that more information improves the system performance.
Original languageEnglish
Pages (from-to)602-609
Number of pages8
JournalOperations Research
Volume63
Issue number3
DOIs
Publication statusPublished - 1 Jan 2015

ASJC Scopus subject areas

  • Computer Science Applications
  • Management Science and Operations Research

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