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Fazel Zarandi, M. H., Avazbeigi, M., (2012). A multi-agent solution for reduction of bullwhip effect in fuzzy supply chains Journal of Intelligent and Fuzzy Systems , 23, (5), 259-268

In this paper, we present a new Multi-Agent System for reduction of the bullwhip effect in fuzzy supply chains. First, we show that a supply chain that uses an optimal ordering policy without data sharing among echelons still suffers from the bullwhip effect. Then, we propose the multi-agent solution to manage and reduce the bullwhip effect. The proposed multi-agent system includes four different types of agents in which each agent has its own list of actions. The proposed Multi-agent System applies a new Tabu Search algorithm for fuzzy rule generation, and a new data filtering algorithm for extraction of the bullwhip-free data from supply chain data warehouse. We validate the multi-agent system under different conditions and discuss how the system responds to different factors. The results show that the proposed multi-agent system reduces the bullwhip effect significantly in a rational time.

Keywords: Bullwhip effect, Bullwhip-free data, Decentralized decision making, Fuzzy rule base, Fuzzy supply chain, Fuzzy time series, Multi-agent system, Supply chain management