Optimizing (r, Q) Decisions Considering Misplaced Items: Lost-Sales and Backorder Cases
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Date
2019
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
IEEE Computer Society
Open Access Color
Green Open Access
No
OpenAIRE Downloads
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Publicly Funded
No
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. © 2018 IEEE.
Description
2018 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2018 -- 16 December 2018 through 19 December 2018 -- 144395
Keywords
(rQ) policy, backorders, lost-sales, misplaced items, Managers, Sales, Stochastic systems, Backorders, Decision making support, Inventory decisions, Inventory managers, Lost sale, Managerial implications, misplaced items, Solution algorithms, Decision making
Fields of Science
0502 economics and business, 05 social sciences, 0211 other engineering and technologies, 02 engineering and technology
Citation
WoS Q
N/A
Scopus Q
Q4

OpenCitations Citation Count
N/A
Source
IEEE International Conference on Industrial Engineering and Engineering Management
Volume
2019-December
Issue
Start Page
1598
End Page
1602
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Scopus : 1
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Mendeley Readers : 2
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1
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1
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1
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