Title :
The Product Safety Stock Prediction Method Based on Artificial Neural Network
Author :
Zhao Ping ; Liu Jingjing
Author_Institution :
Wuhan Coll. of Econ., Wuhan, China
Abstract :
When selling products, in order to prevent products stockout due to the uncertainty events, enterprises usually reserves a certain amount of safety stock. The amount of safety stock is directly related to inventory costs. How to calculate the amount of safety stock, the traditional method of using formulas to calculate directly has many limitations. This paper used artificial neural network to predict the amount of safety stock. The experimental result shows high accuracy.
Keywords :
neural nets; prediction theory; production engineering computing; stock control; uncertainty handling; artificial neural network; product safety stock prediction method; product stockout prevention; uncertainty events; Artificial neural networks; Customer service; Fluctuations; Neurons; Safety; Training; artificial neural network; prediction; safety stock; stockout;
Conference_Titel :
Information Science and Management Engineering (ISME), 2010 International Conference of
Conference_Location :
Xi´an
Print_ISBN :
978-1-4244-7669-5
Electronic_ISBN :
978-1-4244-7670-1
DOI :
10.1109/ISME.2010.190
