A Hybrid Grey & ANFIS Approach to Bullwhip Effect in Supply Chain Networks

Demand forecasting and decision making processes are among the key activities which directly affect the performance of successful supply chain networks. The variability of the demand information between the stages of the supply chains and the increase in this variability as the demand data moves upstream from the customer to consequent stages of the supply chain networks is called Bullwhip Effect. As demand pattern varies due to the field of activity and architecture of supply chains networks, determining the appropriate forecasting and order decision model for system interested in is complicated. This paper analyzes the response of bullwhip effect to a hybrid grey GM (1, 1) forecasting and ANFIS based order decision model under demand with relatively medium variation in a two stage supply chain network simulation. Key-Words: Forecasting, Supply chain network, Bullwhip effect, ANFIS, Grey GM (1, 1).