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In between transportation services, trains are parked and maintained atshunting yards. The conflict-free routing of trains to and on these yards andthe scheduling of service and maintenance tasks is known as the train unitshunting and service problem. Efficient use of the capacity of these yards isbecoming increasingly important, because of increasing numbers of trainswithout proportional extensions of the yards. Efficiently schedulingmaintenance activities is extremely challenging: currently only heuristicssucceed in finding solutions to the integrated problem at all. Bounds areneeded to determine the quality of these heuristics, and also to supportinvestment decisions on increasing the yard capacity. For this, a completealgorithm for a possibly relaxed problem model is required. We analyze thepotential of extending the model for multi-agent path finding to be used forsuch a relaxation.

Train Unit Shunting and Servicing: a Real-Life Application of Multi-Agent Path Finding