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A greedy approach for a rolling stock management problem using multi-interval constraint propagation

ROADEF/EURO challenge 2014

  • Rolling Stock Unit Management
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Abstract

In this article we present our contribution to the Rolling Stock Unit Management problem proposed for the ROADEF/EURO Challenge 2014. We propose a greedy algorithm to assign trains to departures. Our approach relies on a routing procedure using multi-interval constraint propagation to compute the individual schedules of trains within the railway station. This algorithm allows to build an initial solution, satisfying a significant subset of departures.

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References

  • Benhamou, F., & Granvilliers, L. (2006). Continuous and interval constraints. Foundations of Artificial Intelligence, 2, 571–603.

    Article  Google Scholar 

  • Chabert, G., & Jaulin, L. (2009). Contractor programming. Artificial Intelligence, 173(11), 1079–1100.

    Article  Google Scholar 

  • Floyd, R. W. (1962). Algorithm 97: Shortest path. Communications of the ACM, 5(6), 345.

    Article  Google Scholar 

  • Hudak, P., Hughes, J., Peyton Jones, S. & Wadler, P. (2007). A history of haskell: Being lazy with class. In Proceedings of the Third ACM SIGPLAN Conference on History of Programming Languages (pp. 12-1–12-55). ACM.

  • ILOG, S. (1999). Revising hull and box consistency. In Logic Programming: Proceedings of the 1999 International Conference on Logic Programming, (p. 230). MIT Press.

  • Johnsson, T. (1984). Efficient compilation of lazy evaluation. SIGPLAN Notices, 19(6), 58–69.

    Article  Google Scholar 

  • Knüppel, O. (1994). Profil/biasa fast interval library. Computing, 53(3–4), 277–287.

    Article  Google Scholar 

  • Lerch, M., Tischler, G., Gudenberg, J. W. V., Hofschuster, W., & Krämer, W. (2006). Filib++, a fast interval library supporting containment computations. ACM Transactions on Mathematical Software (TOMS), 32(2), 299–324.

    Article  Google Scholar 

  • Madsen, A. L., & Jensen, F. V. (1999). Lazy propagation: A junction tree inference algorithm based on lazy evaluation. Artificial Intelligence, 113(1), 203–245.

    Article  Google Scholar 

  • Moore, R. E. (1966). Interval analysis., Prentice-Hall series in automatic computation Englewood Cliffs: Prentice-Hall.

    Google Scholar 

  • Ninin, J. (2015). Global optimization based on contractor programming: An overview of the ibex library. In International Conference on Mathematical Aspects of Computer and Information Sciences (pp. 555–559). Springer.

  • Ramond, F., & Marcos, N. (2014). Trains don’t vanish ! ROADEF EURO 2014 challenge problem description. Technical report, SNCF—Innovation & Research Department. https://hal.archives-ouvertes.fr/hal-01057324.

  • Rogers, D. F., Plante, R. D., Wong, R. T., & Evans, J. R. (1991). Aggregation and disaggregation techniques and methodology in optimization. Operations Research, 39(4), 553–582.

    Article  Google Scholar 

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Correspondence to Florence Thiard.

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Joudrier, H., Thiard, F. A greedy approach for a rolling stock management problem using multi-interval constraint propagation. Ann Oper Res 271, 1165–1183 (2018). https://doi.org/10.1007/s10479-017-2543-y

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  • DOI: https://doi.org/10.1007/s10479-017-2543-y

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