Multi-agent based scheduling method for tandem automated guided vehicle

We consider the scheduling method that allows to minimize the traveling time of a AGV (and thus energy consumption) at each of zones, while to minimize the waiting time of the automated guided vehicles (AGVs) and/or containers for pickup and delivery (PD) at the transfer points (TPs) installed between adjacent zones in tandem systems. Scheduling for these tandem AGV systems is often not possible from a single point by a single intelligent agent. Intead, scheduling has to be performed using multiple intelligent agents. We consider the cooperative multi-agent scheduling (CMAS) scheme in which each agent employs a multi-offspring genetic algorithm. Coordination between the agents is used to improve their schedulings. This coordination can be in the form of serial scheme. We propose a novel CMAS method based on Lagrange theory and compare this to a non-cooperative scheduling approach between agents. The proposed method is verified at AGV system for a book printing process in Pyongyang Textbook Print Shop as the real-world experiment and it is shown that the CMAS method for tandem AGV system is effective.