Multi-Agent Consensus Optimization in Large-Scale Supply Networks

Abstract

Multi-agent systems are characterized by decentralized decision-making by the (semi)-autonomous agents and localized communication or information exchange among the neighboring agents. Supply-demand networks form the backbones of both services and manufacturing industries, and need to operate as efficiently as possible to yield optimized returns. In this Master's thesis, we bring the notion of multi-agent systems to clustered supply-demand networks such that each supplier acts as an agent. Consequently, \begin{itemize} \item We adapt consensus-based auction bidding methods to optimize the assignment of demands to the suppliers with known communication pathways and resource constraints. \item Results on moderately large networks are presented, which show promising performance in terms of both assignment quality, as given by the overall demand delivery cost and proportion of assigned demands, and computation time.