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State-of-the-art baggage handling systems transport luggage in an automated way using destination coded vehicles (DCVs). These vehicles transport the bags at high speeds on a network of tracks. Currently, the DCVs are routed through the system using routing schemes based on preferred routes. These routing schemes respond to the occurrence of predefined events. We do not consider such predefined preferred routes. Instead, we develop advanced control methods to determine the optimal routing in case of dynamic demand. In order to optimize the performance of the system, we first develop and compare efficient centralized, decentralized, and distributed predictive methods. Next, to reduce the computational requirements, we also propose some heuristic methods. Finally, to assess the performance of the proposed control approaches, the methods are compared for several scenarios on a benchmark case study.