Trusted Mediator Agents to Better Manage Complex and Competitive Supply Chains

Competitive markets in supply chains choose not to share their inventory, backlog, and revenue costs and hence global information is not available. In this paper, we propose a new framework for supply chain management based on trusted mediator agents. A mediator agent places an order on behalf of its customer to a corresponding supplier. The agents use local information and apply adaptive heuristic rules in order to enhance the performance of the entire supply chain. We have evaluated our framework through conducting extensive experiments in an agent-based modeling and simulation environment. The results show a consistent improvement in all the cases that were considered in the literature. We show that local information can in fact lead artificial mediator agents to discover effective ordering strategies.