Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.11851/6080
Title: A fuzzy agent-based model for reduction of bullwhip effect in supply chain systems
Authors: Zarandi, Mohammad Hossein Fazel
Pourakbar, M.
Türkşen, İsmail Burhan
Keywords: supply chain management
agent-based
fuzzy time series
bullwhip effect
simulation
Issue Date: 2008
Publisher: Pergamon-Elsevier Science Ltd
Abstract: This paper addresses the bullwhip effect in a multi-stage supply chain, where all demands, lead times, and ordering quantities are fuzzy. To simulate the bullwhip effect, a modified Hong Fuzzy Time Series is presented by adding a Genetic Algorithm (GA) module for gaining of a window basis. Next, a back propagation neural network is used for defuzzification. The model can forecast the trends in fuzzy data. Then, an agent-based system is developed to minimize the total cost and to reduce the bullwhip effect in supply chains. The system can suggest the reasonable ordering policies. The results show that the propose system is superior than the previous analytical methods in terms of discovering the best available ordering policies. (C) 2007 Elsevier Ltd. All rights reserved.
URI: https://doi.org/10.1016/j.eswa.2007.01.031
https://hdl.handle.net/20.500.11851/6080
ISSN: 0957-4174
Appears in Collections:Endüstri Mühendisliği Bölümü / Department of Industrial Engineering
Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collection

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