Study of Fuzzy Agent-Oriented Model for Bullwhip Effect on Biological Chain Systems

摘要

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 to the previous analytical methods in terms of discovering the best available ordering policies.