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

Authors: Nazanin Pilevari

Addresses: Department of Industrial Management, College of Management and Accounting, Yadegar-e-Imam Khomeini (RAH) Shahre-Rey Branch, Islamic Azad University, Tehran, Iran

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.

Keywords: demand prediction; adaptive neuro fuzzy inference systems; ANFIS; bullwhip effect; modelling; supply chain management; SCM; supply chain collaboration.

DOI: 10.1504/IJLSM.2016.077286

International Journal of Logistics Systems and Management, 2016 Vol.24 No.4, pp.533 - 548

Received: 14 Apr 2015
Accepted: 02 Jun 2015
Published online: 26 Jun 2016 *

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