Optimisation model to schedule railway track renewal operations: a life-cycle cost approach

References

• Andrade, A., & Teixeira, P. (2011a). Biobjective optimization model for maintenance and renewal decisions related to rail track geometry. Transportation Research Record: Journal of the Transportation Research Board, 2261, 163–170. doi:10.3141/2261-19.
   Web of Science ®Google Scholar
• Andrade, A., & Teixeira, P. (2011b). Uncertainty in rail-track geometry degradation: Lisbon–Oporto line case study. Journal of Transportation Engineering, 137, 193–200. doi:10.1061/(ASCE)TE.1943-5436.0000206.
   Web of Science ®Google Scholar
• Andrade, A., & Teixeira, P. (2013). Unplanned-maintenance needs related to rail track geometry. Proceedings of the ICE – Transport, 166, 1–11. doi:10.1680/tran.11.00060.
   Google Scholar
• Budai, G., Huisman, D., & Dekker, R. (2005). Scheduling preventive railway maintenance activities. Journal of the Operational Research Society, 57, 1035–1044. doi:10.1057/palgrave.jors.2602085.
   Web of Science ®Google Scholar
• EN 13848-5 (2008). Railway applications – Track – Track geometry quality. Part 5: Geometric quality levels. European Committee for Standardization (CEN).
   Google Scholar
• Esveld, C. (2001). Modern railway track (2nd ed.). Zaltbommel: MRT Productions.
   Google Scholar
• Famurewa, S., Xin, T., Rantatalo, M., & Kumar, U. (2013). Optimisation of maintenance track possession time: A tamping case study. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 1–11. doi:10.1177/0954409713495667.
   Web of Science ®Google Scholar
• Guler, H. (2013). Prediction of railway track geometry deterioration using artificial neural networks: A case study for Turkish state railways. Structure and Infrastructure Engineering, 10, 614–626. doi:10.1080/15732479.2012.757791.
   Web of Science ®Google Scholar
• Jovanovic, S., Guler, H., & Evren, G. (2011). Modelling railway track geometry deterioration. Proceedings of the ICE – Transport, 164, 65–75. doi:10.1680/tran.2011.164.2.65.
   Google Scholar
• Kalos, M., & Whitlock, P. (2008). Monte Carlo methods (2nd ed.). Weinheim: Wiley-VCH.
   Google Scholar
• Lopez-Pita, A., Teixeira, P., Casas, C., Bachiller, A., & Ferreira, P. (2008). Maintenance costs of high-speed lines in Europe. Transportation Research Record, 2043, 13–19. doi:10.3141/2043-02.
   Web of Science ®Google Scholar
• Lyngby, N., Hokstad, P., & Vatn, J. (2008). RAMS management of railway tracks. In K.B. Misra (Ed.), Handbook of performability engineering (pp. 1123–1145). London: Springer.
   Google Scholar
• Mercier, S., Meier-Hirmer, C., & Roussignol, M. (2012). Bivariate Gamma wear processes for track geometry modelling, with application to intervention scheduling. Structure and Infrastructure Engineering, 8, 357–366. doi:10.1080/15732479.2011.563090.
   Web of Science ®Google Scholar
• Nilsson, R., & Olofsson, U. (2002). Surface cracks and wear of rail: A full-scale test on a commuter train track. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 216, 249–264. doi:10.1243/095440902321029208.
   Web of Science ®Google Scholar
• Patra, A., Söderholm, P., & Kumar, U. (2009). Uncertainty estimation in railway track life-cycle cost: A case study from Swedish National Rail Administration. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 223, 285–293. doi:10.1243/09544097jrrt235.
   Web of Science ®Google Scholar
• Podofillini, L., Zio, E., & Vatn, J. (2006). Risk-informed optimisation of railway tracks inspection and maintenance procedures. Reliability Engineering & System Safety, 91, 20–35. doi:10.1016/J.Ress.2004.11.009.
   Web of Science ®Google Scholar
• Riessberger, K. (2001). Extending maintenance cycles and ballast life. Paper presented at the 7th International Heavy Haul Conference, Brisbane, Australia.
   Google Scholar
• Sadeghi, J., & Askarinejad, H. (2011). Development of track condition assessment model based on visual inspection. Structure and Infrastructure Engineering, 7, 895–905. doi:10.1080/15732470903194676.
   Web of Science ®Google Scholar
• Shyr, F., & Ben-Akiva, M. (1996). Modeling rail fatigue behavior with multiple hazards. Journal of Infrastructure Systems, 2, 73–82. doi:10.1061/(ASCE)1076-0342(1996)2:2(73).
   Google Scholar
• Stirling, A., Roberts, C., Chan, A., & Zhao, J. (2006). Assessing the economic life of rail using a stochastic analysis of failures. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 220, 103–111. doi:10.1243/09544097jrrt30.
   Web of Science ®Google Scholar
• UIC (2008). Best practice guide for optimum track geometry durability. Paris: UIC.
   Google Scholar
• UIC (2009). UIC code 714: Classification of lines for the purpose of track maintenance (4th ed.). Paris: UIC.
   Google Scholar
• Yun, W., & Ferreira, L. (2003). Prediction of the demand of the railway sleepers: A simulation model for replacement strategies. International Journal of Production Economics, 81–82, 589-595.10.1016/S0925-5273(02)00299-2.
   Web of Science ®Google Scholar
• Zhao, J., Chan, A., & Burrow, M. (2007). Reliability analysis and maintenance decision for railway sleepers using track condition information. Journal of the Operational Research Society, 58, 1047–1055. doi:10.1057/palgrave.jors.2602251.
   Web of Science ®Google Scholar
• Zhao, J., Chan, A., & Burrow, M. (2009). A genetic-algorithm-based approach for scheduling the renewal of railway track components. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 223, 533–541. doi:10.1243/09544097jrrt273.
   Web of Science ®Google Scholar
• Zhao, J., Chan, A., Stirling, A., & Madelin, K. (2006). Optimizing policies of railway ballast maintenance and renewal. Transportation Research Record, 1943, 50–56. doi:10.3141/1943-07.
   Google Scholar