DocumentCode
1634510
Title
A neural network based method for part demands prediction in auto aftermarket
Author
Yu, Li ; Chen, Yun
Author_Institution
Acad. of Modern Service Ind., Shanghai Univ. of Finance & Econ., Shanghai, China
fYear
2010
Firstpage
648
Lastpage
651
Abstract
In the supply chain management of auto aftermarket, companies strive to manage inventory with low cost while maintaining a reasonable order fulfillment rate. To achieve this objective, a critical issue is to predict the demand for auto parts with high accuracy. Based on the factors relevant to auto aftermarket, this paper proposed an artificial neural network based method to forecast the demands of auto parts. The effectiveness of the proposed method is illustrated with a case study of an auto 4s shop in Shanghai.
Keywords
automotive components; demand forecasting; inventory management; neural nets; supply chain management; Shanghai; auto aftermarket; demand forecasting; inventory management; neural network; part demand prediction; supply chain management; Artificial neural networks; Automotive engineering; Forecasting; Manganese; Marketing and sales; Prediction methods; Supply chain management; demand prediction; neural network; supply chain management;
fLanguage
English
Publisher
ieee
Conference_Titel
Software Engineering and Service Sciences (ICSESS), 2010 IEEE International Conference on
Conference_Location
Beijing
Print_ISBN
978-1-4244-6054-0
Type
conf
DOI
10.1109/ICSESS.2010.5552264
Filename
5552264
Link To Document