Auction Bidding Methods for Multi-Agent Consensus Optimization in Supply-Demand Networks

Abstract

Multiagent 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 letter, we bring the notion of multiagent systems to clustered supply–demand networks such that each supplier acts as an agent. Consequently, we adapt consensus-based auction bidding methods to optimize the assignment of demands to the suppliers with known communication pathways and resource constraints. Results on moderately large networks 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

Publication
IEEE Robotics and Automation Letters 3.4 (2018): 4415-4422