Optimizing (r, Q) Decisions Considering Misplaced Items: Lost-sales and Backorder Cases

Linda L. Zhang, G. Yazgi Tutuncu, Ceki Franko

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

1 Citation (Scopus)

Abstract

Most available (r, Q) inventory models assume that the actual inventory records are the same as these in the computer systems. With this unrealistic assumption, these models may, thus, distort the inventory decision making in practice. In this study, we develop new (r, Q) models considering the misplaced items to provide inventory managers with realistic decision-making support. In developing the new models, we characterize two cases: backorders and lost-sales. In both cases, we consider stochastic demand and introduce parameters to represent misplaced items. We also propose solution algorithms for model solving. Numerical examples are conducted to demonstrate the applicability and potential of the new (r, Q) models and solution algorithms in making realistic inventory decisions. We further obtain managerial implications.

Original languageEnglish
Title of host publication2018 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2018
PublisherIEEE Computer Society
Pages1598-1602
Number of pages5
ISBN (Electronic)9781538667866
DOIs
Publication statusPublished - 2 Jul 2018
Externally publishedYes
Event2018 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2018 - Bangkok, Thailand
Duration: 16 Dec 201819 Dec 2018

Publication series

NameIEEE International Conference on Industrial Engineering and Engineering Management
Volume2019-December
ISSN (Print)2157-3611
ISSN (Electronic)2157-362X

Conference

Conference2018 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2018
Country/TerritoryThailand
CityBangkok
Period16/12/1819/12/18

Keywords

  • (rQ) policy
  • backorders
  • lost-sales
  • misplaced items

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