Decentralization cost in scheduling: A game-theoretic approach

Decentralized organizations may incur inefficiencies because of scheduling issues associated with competition among decision makers (DMs) for limited resources. We analyze the decentralization cost (DC), i.e., the ratio between the Nash equilibrium cost and the cost attained at the centralized optimum. Solution properties of a dispatching–sequencing model are derived and subsequently used to develop bounds on the DC for an arbitrary number of jobs and DMs. A scheduling–based coordinating mechanism is then provided, ensuring that the centralized solution is obtained at equilibrium.