Job Order Assignment at Optimal Costs in Railway Maintenance

Franziska Heinicke, Axel Simroth, Roberto Tadei, Mauro M. Baldi

2013

Abstract

Tamping is an important part of railway maintenance. Well tamped ballast reduces track irregularities and increases travel safety and comfort. But if the ballast is in a bad condition, the train speed must be restricted, which leads to delays and penalty costs for the operator. In this paper a novel model for the tamping scheduling problem in a short-term planning horizon is presented. In contrast to other railway maintenance scheduling problems the penalty costs caused by deferring tamping activities are considered in the scheduling process beside the travel costs. Three greedy heuristics are presented and compared in different benchmarks. An outlook discusses issues of interest for further research.

References

  1. Budai, G., Dekker, R., and Kaymak, U. (2009). Genetic and memetic algorithms for scheduling railway maintenance activities. Technical report, Econometric Institute, Erasmus University Rotterdam.
  2. Budai, G., Huisman, D., and Dekker, R. (2004). Scheduling preventive railway maintenance activities. Technical report, Econometric Institute, Erasmus University Rotterdam.
  3. Cong, J., Fang, J., Xie, M., and Zhang, Y. (2005). Mars-a multilevel full-chip gridless routing system. ComputerAided Design of Integrated Circuits and Systems, IEEE Transactions on, 24(3):382 - 394.
  4. Gorman, M. F. and Kanet, J. J. (2010). Formulation and solution approaches to the rail maintenance production gang scheduling problem. Journal of Transportation Engineering, 136:701-708.
  5. Higgins, A. and Ferreira, L. (1999). Scheduling rail track maintenance to minimise overall delays. In Proceedings of the 14th International Symposium on Transportation and Traffic Theory.
  6. Karypis, G. and Kumar, V. (1996). Parallel multilevel graph partitioning. In Parallel Processing Symposium, 1996., Proceedings of IPPS 7896, The 10th International, pages 314 -319.
  7. Meer, K. (2007). Simulated annealing versus metropolis for a TSP instance. Information Processing Letters, 104(6):216 - 219.
  8. Miwa, M. (2002). Mathematical programming model analysis for the optimal track maintenance schedule. QR of RTRI, 43:131-136.
  9. Oyama, T. and Miwa, M. (2006). Mathematical modeling analyses for obtaining an optimal railway track maintenance schedule. Japan J. Indust. Appl. Math., 23:207224.
  10. Peng, F., Kand, S., Li, X., and Ouyang, Y. (2011). A heuristic approach to the railroad track maintenance scheduling problem. Computer-Aided Civil and Infrastructure Engineering, 26:129-145.
  11. Quiroga, L. M. and Schnieder, E. (2010). A heuristic approach to railway track maintenance scheduling. WIT Transactions on The Build Environment, 114:687-699.
  12. Vale, C., Ribeiro, I. M., and Calc¸ada, R. (2012). Integer programming to optimize tamping in railway track as preventive maintenance. Journal of Transportation Engineering, 138:123-131.
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Paper Citation


in Harvard Style

Heinicke F., Simroth A., Tadei R. and M. Baldi M. (2013). Job Order Assignment at Optimal Costs in Railway Maintenance . In Proceedings of the 2nd International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES, ISBN 978-989-8565-40-2, pages 304-309


in Bibtex Style

@conference{icores13,
author={Franziska Heinicke and Axel Simroth and Roberto Tadei and Mauro M. Baldi},
title={Job Order Assignment at Optimal Costs in Railway Maintenance},
booktitle={Proceedings of the 2nd International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,},
year={2013},
pages={304-309},
publisher={SciTePress},
organization={INSTICC},
doi={},
isbn={978-989-8565-40-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Operations Research and Enterprise Systems - Volume 1: ICORES,
TI - Job Order Assignment at Optimal Costs in Railway Maintenance
SN - 978-989-8565-40-2
AU - Heinicke F.
AU - Simroth A.
AU - Tadei R.
AU - M. Baldi M.
PY - 2013
SP - 304
EP - 309
DO -