Model for identification of effects of demand prediction on bullwhip effect using adaptive network-based fuzzy inference system

Model for identification of effects of demand prediction on bullwhip effect using adaptive network-based fuzzy inference system

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Article ID: iaor20162732
Volume: 24
Issue: 4
Start Page Number: 533
End Page Number: 548
Publication Date: Jun 2016
Journal: International Journal of Logistics Systems and Management
Authors:
Keywords: simulation, supply & supply chains, management, statistics: regression
Abstract:

The purpose of supply chain management is to lower the overall cost of chain and this has led to the chain being in need of mutual collaboration of its components. One of the phenomena that expose the coordination of supply chain to challenges is a phenomenon called the bullwhip effect. Following the study of previous research and using the expertise of experts, this research identifies the effective components on the quantity of demand. Then, seeking the opinion of experts in the industry under study (the automotive parts industry), the set of rules for fuzzy inference system were exploited and the model for prediction of single‐level supply change was developed. Furthermore, in order to assess the effect of developed model on bullwhip effect, the results of conducted predictions were compared to each other through the conventional model and technique of company (regression method) and the trend analysis method.

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