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Robust Algorithms for Sorting Railway Cars

Büsing, Christina; Maue, Jens

Preprint-Reihe des Instituts für Mathematik, Technische Universität Berlin

We consider a sorting problem from railway optimization called train classification: incoming trains are split up into their single cars and reassembled to form new outgoing trains. Trains are subject to delay, which may turn a prepared sorting schedule infeasible for the disturbed situation. The classification methods applied today deal with this issue by completely disregarding the input order of cars, which provides robustness against any amount of disturbance but also wastes the potential contained in the a priori knowledge about the input.