Abstract
Rearranging cars of an incoming train in a hump yard is a widely discussed topic. Sorting of Rolling Stock Problems can be described in several scenarios and with several constrains. We focus on the train marshalling problem where the incoming cars of a train are distributed to a certain number of sorting tracks. When pulled out again to build the outgoing train, cars sharing the same destination should appear consecutively. The goal is to minimize the number of sorting tracks. We suggest a graph-theoretic approach for this \(\mathcal {NP}\)-complete problem. The idea is to partition an associated directed graph into what we call pseudochains of minimum length. We describe a greedy-type heuristic to solve the partitioning problem which, on random instances, performs better than the known heuristics for the train marshalling problem. In addition we discuss the TMP with b-bounded sorting tracks.
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References
Beygang, K., Dahms, F., Krumke, S.O.: Train Marshalling Problem—Algorithms and Bounds. Technical Report, vol. 132. University of Kaiserslautern (2010)
Hiller, W.: Rangierbahnhöfe. VEB Verlag für Verkehrswesen, Berlin (1983)
Giger, M.: Rangierbahnhof limmattal. In: Swiss Engineering STZ Automate Now!. vol. 1–2, pp. 93–94 (2010)
Hansmann, R.S.: Optimal Sorting of Rolling Stock. Cuvillier, Göttingen (2011)
Zhu, Y., Zhu, R.: Sequence reconstruction under some order-type constraints. Sci. Sin. (A) 26(7), 702–713 (1983)
Dahlhaus, E., Horak, P., Miller, M., Ryan, J.: The train marshalling problem. Discret. Appl. Math. 103(1–3), 41–54. https://doi.org/10.1016/s0166-218x(99)00219-x (2000)
Brueggeman, L., Fellows, M., Fleischer, R., Lackner, M., Komusiewicz, C., Koutis, Y., Pfandler, A., Rosamond, F.: Train marshalling is fixed parameter tractable. In: Kranakis, E., Krizanc, D., Luccio, F. (eds.) Fun with Algorithms, pp. 51–56. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30347-0_8 (2012)
Dahlhaus, E., Manne, F., Miller, M., Ryan, J.: Algorithms for combinatorial problems related to train marshalling. In: Proceedings of AWOCA 2000, pp. 7–16, Hunter Valley (2000)
Beygang, K.: On the Solution of Some Railway Freight Car optimization Problems. Dr. Hut, München (2011)
Rinaldi, F., Rizzi, R.: Solving the train marshalling problem by inclusion—exclusion. Discret. Appl. Math. 217)(Part 3), 685–690 (2017)
Haahr, J.T., Lusby, R.M.: A matheuristic approach to integrate humping and pullout sequencing operations at railroad hump yards. Networks 67(2), 126–138 (2016)
Dörpinghaus, J., Schrader, R.: A graph-theoretic approach to the train marshalling problem. In: Ganzha, M., Maciaszek, L., Paprzycki, M.(eds.) Proceedings of the 2018 Federated Conference on Computer Science and Information Systems, series Annals of Computer Science and Information Systems, vol. 15, pp. 227–231. IEEE. https://doi.org/10.15439/2018F26 (2018)
Dörpinghaus, J.: Pseudostabile Mengen in Graphen. Fraunhofer Verlag. https://kups.ub.uni-koeln.de/8066/ (2018)
Bohlin, M., Hansmann, R., Zimmermann, U.T.: Optimization of railway freight shunting. In: Handbook of Optimization in the Railway Industry, pp. 181–212. Springer (2018)
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Dörpinghaus, J., Schrader, R. (2020). Solving Sorting of Rolling Stock Problems Utilizing Pseudochain Structures in Graphs. In: Fidanova, S. (eds) Recent Advances in Computational Optimization. Studies in Computational Intelligence, vol 838. Springer, Cham. https://doi.org/10.1007/978-3-030-22723-4_4
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