DocumentCode :
2410200
Title :
Notice of Retraction
Dynamic Inventory Management with Selling the Substitute as Stockout Occurs
Author :
Chunlin Luo ; Jian Liu
Author_Institution :
Sch. of Inf. Technol., Jiangxi Univ. of Finance & Econ., Nanchang, China
fYear :
2010
fDate :
7-9 May 2010
Firstpage :
3221
Lastpage :
3224
Abstract :
Notice of Retraction

After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

A well-known result in Bayesian inventory control is: if lost sales are not observed, the optimal Bayesian inventory level is no less than the corresponding myopic case, that is, the decision-maker should “stock more” to acquire the knowledge of demand. However, we find that when the stockout demand can be satisfied by some substitute product with a probability, the optimal Bayesian inventory level is less than the optimal myopic inventory level. Especially, we use the concept of unnormalized probability to considerably simplify the dynamic programming formulation.
Keywords :
Bayes methods; decision making; dynamic programming; probability; sales management; stock control; Bayesian inventory control; decision-maker; dynamic inventory management; dynamic programming formulation; lost sales; optimal Bayesian inventory level; optimal myopic inventory level; probability; selling; stockout demand; substitute product; unnormalized probability; Bayesian methods; Economics; Equations; Finance; Inventory management; Marketing and sales; Operations research; Bayesian updating; Dynamic inventory management; Stockout; Unnormalized probability;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
E-Business and E-Government (ICEE), 2010 International Conference on
Conference_Location :
Guangzhou
Print_ISBN :
978-0-7695-3997-3
Type :
conf
DOI :
10.1109/ICEE.2010.811
Filename :
5591372
Link To Document :
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