DocumentCode
2796261
Title
An integrated excess stock return model with deteriorating items for vendor-buyer
Author
Chung, Shen Lian ; Wee, Hui Ming
Author_Institution
Dept. of Inf. Manage., St. John´´s Univ., Taipei
Volume
7
fYear
2008
fDate
12-15 July 2008
Firstpage
3915
Lastpage
3920
Abstract
Excess stock is a common phenomenon in a supply chain owing to over ordering and/or incorrect demand predictions. Excess stock is a valueless asset to an organization; it consumes working capital, uses valuable storage space, and decreases the return on investment. Therefore, excessive stock must be dealt with in order to derive an optimal inventory level for minimum total relevant costs. Previous researchers had considered the views of buyers to establish excess stock models to determine the inventory retention level, but the views of the vendors were not consulted. This results in local optimality only and unsatisfied vendors. This study to consider the views of the vendor-buyer and deteriorating items, and to develop an analytical model for the integrated inventory decisions in a supply chain. The results of the model can be a guide to decide the optimal quantity of return units to dispose of under various return purchase prices. A numerical example is provided to illustrate the theory.
Keywords
decision making; stock control; supply chain management; deteriorating items; incorrect demand predictions; integrated excess stock return model; integrated inventory decisions; minimum total relevant costing; optimal inventory level; over ordering; return on investment; supply chain; vendor-buyer views; Analytical models; Cost function; Cybernetics; Inventory management; Investments; Machine learning; Mathematical model; Production systems; Supply chain management; Supply chains; Deteriorating item; Excess stock; Return inventory; Supply chain inventory management;
fLanguage
English
Publisher
ieee
Conference_Titel
Machine Learning and Cybernetics, 2008 International Conference on
Conference_Location
Kunming
Print_ISBN
978-1-4244-2095-7
Electronic_ISBN
978-1-4244-2096-4
Type
conf
DOI
10.1109/ICMLC.2008.4621087
Filename
4621087
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