Coordination Of Supply Webs Based On Dispositive Protocols

The focus of this paper is the design of a mechanism to help economic agents either autonomously or cooperatively planning to achieve Pareto-optimal allocation of resources via a completely decentralized coordination of a logistics network. Besides giving a classification and a short review of existing scheduling approaches capable for supply chain management, this article specifies and evaluates protocols employing time-depended price-functions. By performing simulations with the implemented protocol using well-known Job Shop Scheduling Problems as a benchmark we show the efficiency and feasibility of the designed mechanism. The approach enables each agent to exploit the external effects caused by resource constraints of its supply chain contractors by adapting its production planning. Additionally the systems capability to reconfigure itself in case of production resources failure is increased. The evaluation of the protocols concludes with a welfare analysis investigating the payoff distribution along the supply chain. Finally we conclude that future research on this topic should turn to learning agent systems to reduce communication costs.