An Agent-Based Reverse Pricing Model for Reducing Bullwhip Effect in Supply Chains

This paper addresses the problem of increasing order variances in multi-tier supply chains. The majority of current approaches for reducing this problem, namely the bullwhip effect, rely on information sharing and/or cooperative planning in inter-organizational systems. Due to multiple barriers in implementing these approaches, the authors maintain the local autonomy of the participants in the supply chain and provide a multiagent-oriented solution to the problem. In particular, they design an agent-based reverse pricing model for matching supply and demand between independent agents. They adopt reverse pricing for operational procurement decisions and matchmaking that can be automated to a large extent.