Abstract
We consider a series of companies in a supply chain, each of which orders from its immediate upstream collaborators. Usually, the retailer’s order do not coincide with the actual retail sales. The bullwhip effect refers to the phenomenon where orders to the supplier tend to have larger variance than sales to the buyer (i.e. demand distortion), and the distortion propagates upstream in an amplified form (i.e. variance amplification). We show that if the members of the supply chain share information with intelligent support technology, and agree on better and better fuzzy estimates (as time advances) on future sales for the upcoming period, then the bullwhip effect can be significantly reduced.
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© 2002 Springer Science+Business Media New York
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Carlsson, C., Fullér, R. (2002). A Fuzzy Approach to Taming the Bullwhip Effect. In: Zimmermann, HJ., Tselentis, G., van Someren, M., Dounias, G. (eds) Advances in Computational Intelligence and Learning. International Series in Intelligent Technologies, vol 18. Springer, Dordrecht. https://doi.org/10.1007/978-94-010-0324-7_17
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DOI: https://doi.org/10.1007/978-94-010-0324-7_17
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-010-3872-0
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