Impact of Combined Demand Forecasting on the Bullwhip Effect and the Total Cost in a Decentralized Supply Chain

Abstract

In this research, a distributed supply chain model is constructed using a multi-agent system, and the optimal combination of demand forecasting of each company in the supply chain is analyzed. Performance evaluation is evaluated not only in terms of bullwhip effect but also in terms of total cost. The simulation results show that each company can reduce the bullwhip effect and the total cost by determining the demand forecasting method according to its position in the supply chain.