Route Choice Control of Automated Baggage Handling Systems

Abstract

State-of-the-art baggage handling systems transport luggage in an automated way by using destination-coded vehicles (DCVs). These vehicles transport the bags at high speeds on a minirailway network. Currently, the networks are simple, with only a few junctions; otherwise bottlenecks would be created at the junctions. Bottlenecks make the system inefficient. More complex networks were considered. To optimize the performance of the system, centralized and decentralized control methods that could be used to route the DCVs through the track network were developed and compared. The proposed centralized control method is model predictive control (MPC). Because of the large computation effort that centralized MPC required, decentralized MPC and a fast decentralized heuristic approach were also proposed. When the decentralized approaches are implemented, each junction has its own local controller for positioning the switch going into the junction and the switch going out of the junction. To assess the advantages and disadvantages of centralized MPC, decentralized MPC, and the decentralized heuristic approach, a simple benchmark case study was studied. The considered control methods were compared for several scenarios. Centralized MPC becomes intractable when a large stream of bags must be handled, whereas decentralized MPC can still be used to solve the problem suboptimally. Moreover, the decentralized heuristic approach usually gives worse results than those obtained when using decentralized MPC but with very low computation time.