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

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Date

2019

Authors

Tütüncü, Gözde Yazgı
Franko C.

Journal Title

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Volume Title

Publisher

IEEE Computer Society

Open Access Color

Green Open Access

No

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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
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Source

IEEE International Conference on Industrial Engineering and Engineering Management

Volume

2019-December

Issue

Start Page

1598

End Page

1602
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