Fuzzy forecasting applications on supply chains

Demand forecasting; which sound basis for decision making process, is among the key activities that directly affect the supply chain performance. As the demand pattern varies from system to system, determination of the appropriate forecasting model that best fits the demand pattern is a hard decision in management of supply chains. The whiplash effect can be express as the variability of the demand information between stages of the supply chain and the increase of this variability as the information moves upstream through the chain. The usage of proper demand forecasting model that is adequate for the demand pattern is an important step for smoothing this undesirable variability. This paper evaluates the effects of fuzzy linear regression, fuzzy time series and fuzzy grey GM (1,1) forecasting models on supply chain performance quantifying the demand variability (i.e. whiplash) through the stages of a near beer game supply chain simulation model expanded with fuzzy parameters.

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