A Novel Approach for Safety Stock Prediction based on Clustering Artificial Neural Network
نویسنده
چکیده
An accurate safety stock forecasting model has both academic and practical significance to inventory management. Reliable safety stock forecasting can not only help in making right decision but also in decreasing the cost and thereby increasing the profit significantly. Therefore in this paper, Artificial Neural Network (ANN) along with Clustering techniques, have been applied to predict the safety stock and design a new methodology for the problem of low accuracy in presence of outliers as well as high variance in target data of ANN which is safety stock in this study. By experimenting our method implemented in Matlab 7.8.0(R.2009.a) and Weka (3-7-5), it is found to have an optimal accuracy in forecasting the safety stock. Keywords-safety stock; artificial neural network; clustering; prediction; high variance
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