Document Type : Original Article


1 Ph.D, University of Tehran.

2 Professor, Amirkabir University.


An important issue in supply chain management is the whip effect. This indicates an increase in demand volatility as the chain moves. This paper investigates the effect of several classical and intelligent methods on the forecasting process of turbulent demand on the occurrence of the whip effect. The results show that neural networks have more power to model and predict this behavior than conventional classical methods such as exponential smoothing due to nonlinear, oscillatory and even chaotic demand behavior. At the end of the article, using a numerical example, the use of neural networks to predict turbulent demand, in a successful reduction of the whip effect, is illustrated.


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