Authors
Abstract
Keywords
|
Ayers,J.,(2000), HandBook Of chain management, APICS
|
[1]
|
|
Chorpa,S., and Meindl,P.,(2001) supply chain management:strategy,planning and operation, prentice hall,
|
[2]
|
|
Zhao, Xie and Wei,(2002) "The impact of forecast errors on early order commitment in a supply chain.," Decision Sciences, pp. 251-280,
|
[3]
|
|
ARMSTRONG,J.,(2001) Principles of forcasting, Kluwer Academic Publisher,
|
[4]
|
|
Apleydin,E.,(2010) Introduction to machine learning., MIT press,
|
[5]
|
|
Standler,H., and Kilger, C.,(2008) supply chain management and advanced planning concepts model and case studies, springer,
|
[6]
|
|
Henkoff,R.,(1994) "Delivering The Goods," fortune,
|
[7]
|
|
Lee,H., Padmanabhan,v., and Whang, S.,(1997) "The Bullwhip Effect In Supply Chains," Sloan Management Review, pp. 93-102,
|
[8]
|
|
کاظمی, ب., (1381)مدیریت تولید, تهران: دانشگاه پیام نور,
|
[9]
|
|
Anderson, J. A., and Rosenfeld, E.,(1988) Neurocomputing: Foundations of Research, Cambridge: MIT Press,
|
[10]
|
|
Burges,(1998) "Atutorial on support vector machine for pattern recognition," International conference on data mining and knowledge discovery,
|
[11]
|
|
Aburto,L., and Weber, R.,(2007) "Improved supply chain management based on hybrid demand forecasts," Applied Soft Computing, pp. 136-144,
|
[12]
|
|
Gutierreza, S. R., Solis,O. A., and S. Mukhopahyayb, (2008) "Lumpy demand forecasting using neural networks," International Journal of Production Economics, pp. 409-420,
|
[13]
|
|
Niu, Shi and Wu,(2012) "Short-term load forecasting using bayesian neural networks learned by Hybrid Monte Carlo algorithm," Applied Soft Computing, pp. 1822-1827,
|
[14]
|
|
Guanghui,W.,(2012) "Demand Forecasting of Supply Chain Based on Support Vector Regression Method," Procedia Engineering, pp. 280-284,
|
[15]
|
|
شهرابی, ج., وموسوی, س., (1387)“تحلیل تاثیر روش های متداول پیش بینی بر اثرشلاقی و پیشنهاد مدلی برای کنترل آن در زنجیره تامین,” دومین کنفرانس داده کاوی ایران,
|
[16]
|
|
Carbonneau,R., Laframboise, K., and Vahidov, R.,(2007) "Application of machine learning techniques for supply chain demand forecasting," European Journal of Operational Research,
|
[17]
|
|
Mojaveri, Mousavi, Heydar and Aminian,(2009) "Validation and Selection between Machine Learning techniques and traditional methods to reduce bullwhip effect," World Academy of Science, Engineering and Technology,
|
[18]
|
|
Kandananond,K.,(2012) "A Comparison of Various Forecasting Methods for Autocorrelated Time Series," International Journal of Engineering Business Management,
|
[19]
|
|
Hall,S.,(2012) Applied Economic Forecasting techniques, harvester,
|
[20]
|
|
Demuth,H and Beale, M.,(1997) Neural Network Toolbox User's Guide, Version 3.0, The Math Works, Inc,
|
[21]
|
|
Ali, M. M., & Boylan, E. J. (2010). On the effect of non-optimal forecasting methods on supply chain downstream demand. IMA journal of management mathematics , 23, pp. 81-89.
|
[22]
|
)