Improved inventory targets in the presence of limited historical demand data

A. Akcay, B. Biller, S. Tayur

Research output: Contribution to journalArticleAcademicpeer-review

23 Citations (Scopus)
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Abstract

Most of the literature on inventory management assumes that the demand distribution and the values of its parameters are known with certainty. In this paper, we consider a repeated newsvendor setting where this is not the case and study the problem of setting inventory targets when there is a limited amount of historical demand data. Consequently, we achieve the following objectives: (1) to quantify the inaccuracy in the inventory-target estimation as a function of the length of the historical demand data, the critical fractile, and the shape parameters of the demand distribution; and (2) to determine the inventory target that minimizes the expected cost and accounts for the uncertainty around the demand parameters estimated from limited historical data. We achieve these objectives by using the concept of expected total operating cost and representing the demand distribution with the highly flexible Johnson translation system. Our procedures require no restrictive assumptions about the first four moments of the demand random variables, and they can be easily implemented in practical settings with reduced expected total operating costs.
Original languageEnglish
Pages (from-to)297-309
Number of pages14
JournalManufacturing & Service Operations Management
Volume13
Issue number3
DOIs
Publication statusPublished - 18 Feb 2011

Keywords

  • expected total operating cost
  • inventory management
  • Johnson translation system
  • maximum likelihood policy
  • statistical estimation

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