Neural network approach to lumpy demand forecasting for spare parts in process industries

Proceedings of the International Conference on Computer and Communication Engineering 2008, ICCCE08: Global Links for Human Development

Volumn , Issue , 2008, Pages 1378-1382

  Amin Naseri, M R ^a   Rostami Tabar, B ^a  

^a TARBIAT MODARES UNIVERSITY   (Iran)

Author keywords

Forecasting; Lumpy demand; Neural networks; Spare parts

Indexed keywords

FOOD PROCESSING; FORECASTING; IMAGE CLASSIFICATION; PETROCHEMICALS; RECURRENT NEURAL NETWORKS; TECHNOLOGY;

ARTIFICIAL NEURAL NETWORK MODELING; COMMUNICATION ENGINEERING; CONVENTIONAL METHODS; CROSTON'S METHOD; DEMAND FORECASTING; FUTURE CONSUMPTION; GENERALIZED REGRESSION NEURAL NETWORK; HUMAN DEVELOPMENTS; IN-PROCESS; INTERNATIONAL CONFERENCES; INVENTORY MANAGEMENT; LUMPY DEMAND; MULTI-LAYERED; NON-LINEAR PATTERNS; PERCEPTRON NEURAL NETWORKS; PETROCHEMICAL COMPANY; REAL DATA SETS; SPARE PARTS; TIME-SERIES;

NEURAL NETWORKS;

EID: 51849164984     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICCCE.2008.4580831     Document Type: Conference Paper

References (19)

1. Z. S. Hua and B. Zhang "A hybrid support vector machines and logistic regression approach for forecasting intermittent demand of spare parts," Applied Mathematics and Computation , 2006, ARTICLE IN PRESS
2. Z. S. Hua, B.Zhang, J.Yang and D.S Tan "A new approach of forecasting intermittent demand for spare parts inventories in the process industries", Journal of Operational Research Society, 2007, 58, p.52-61
3. A.A. Syntetos and J.E Boylan, "On the bias of intermittent demand estimates" International Journal of Production Economics, 2001, 71, p.457-466.
4. A.A. Syntetos and J.E Boylan, "The accuracy of intermittent demand estimates" International Journal of forecasting, 2005, 21, p.303-314.
5. A. Ghobbar, C. H. Friend, "Evaluation of forecasting methods for intermittent parts demand in the field of aviation: a predictive model, Computers & Operations Research, 2003, 30, p.2097-2114.
6. R.V Bartezzaghi, G.Zotteri, "A simulation framework for forecasting uncertain lumpy demand", International of Journal of Production Economics, 1999, 59, p.499-510.
7. J.D Croston, "Forecasting and Stock Control for Intermittent Demand." Operational Research Quarterly, 1972, 23(3), P. 289-303.
8. F.R Johnston and J.E Boylan, "Forecasting for items with intermittent demand, Journal of the operational Research Society,1996, 47, p.113-121.
9. E. Leve'n, A. Segerstedt, "Inventory control with a modified Croston procedure and Erlan distribution", International Journal of Production Economics, 2004, 90, p.361-367.
10. J.L Carmo, A.J. Rodrigus, "Adaptive forecasting of irregular demand processes." Engineering Applications of Artificial Intelligence,2004, 17, p.137-143.
11. R.S. Gutierrez, A.O. Solis and S.Mukhopadhyay, "Lumpy demand forecasting using neural networks.", International Journal of Production Economic, 111, 2008, p.409-420.
12. th international conference on operations and quantitative management, October 17-20 2007, Bangkok.
13. D.F. Specht, "A general regression neural network.",IEEE Trans Neural Network, 1991, 2(6), p.568-76.
14. J.L Elman, D. Zipser, "Learning the hidden structure of speech. Institute of Cognitive", Science Report 8701, UC San Diego.
15. R.J. Hyndman, "Another Look at Forecast-Accuracy Metrics for Intermittent Demand.", Foresight, International Journal of Applied Forecasting, 2006, 1(4), p.43-46.
16. J. Hoover, "Measuring Forecast Accuracy: Omissions in Today's Forecasting Engines and Demand-Planning Software." Foresight, International Journal of Applied Forecasting, 2006, 1(4), p.32-35.
17. A.A. Syntetos, J.E. Boylan, "On the stock control performance of intermittent demand estimators." International Journal of Production Economics, 103, p.36-47.
18. J.E. Boylan, ""Intermittent and Lumpy Demand: A Forecasting Challenge.", Foresight, International Journal of Applied Forecasting 1(1), p.36-42.
19. J.E Boylan, A. A.Syntetos, G. C Karakostas, "Classification for forecasting and stock control: a case study." Journal of the Operational Research Society,59, 2008, p.473-481.