Technical note - Approximation algorithms for perishable inventory systems with setup costs

Huanan Zhang, Cong Shi, Xiuli Chao

Research output: Contribution to journalArticle

16 Scopus citations

Abstract

We develop the first approximation algorithm for periodic-review perishable inventory systems with setup costs. The ordering lead time is zero. The model allows for correlated demand processes that generalize the well-known approaches to model dynamic demand forecast updates. The structure of optimal policies for this fundamental class of problems is not known in the literature. Thus, finding provably near-optimal control policies has been an open challenge. We develop a randomized proportional-balancing policy (RPB) that can be efficiently implemented in an online manner, and we show that it admits a worst-case performance guarantee between 3 and 4. The main challenge in our analysis is to compare the setup costs between RPB and the optimal policy in the presence of inventory perishability, which departs significantly from the previous works in the literature. The numerical results show that the average performance of RPB is good (within 1% of optimality under i.i.d. demands and within 7% under correlated demands).

Original languageEnglish (US)
Pages (from-to)432-440
Number of pages9
JournalOperations Research
Volume64
Issue number2
DOIs
StatePublished - Mar 1 2016

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Management Science and Operations Research

Fingerprint Dive into the research topics of 'Technical note - Approximation algorithms for perishable inventory systems with setup costs'. Together they form a unique fingerprint.

  • Cite this