Multi-level condition-based maintenance planning for railway infrastructures - A scenario-based chance-constrained approach


Reference:
Z. Su, A. Jamshidi, A. Núñez, S. Baldi, and B. De Schutter, "Multi-level condition-based maintenance planning for railway infrastructures - A scenario-based chance-constrained approach," Transportation Research Part C, vol. 84, pp. 92-123, Nov. 2017.

Abstract:
This paper develops a multi-level decision making approach for the optimal planning of maintenance operations of railway infrastructures, which are composed of multiple components divided into basic units for maintenance. Scenario-based chance-constrained Model Predictive Control (MPC) is used at the high level to determine an optimal long-term component-wise intervention plan for a railway infrastructure, and the Time Instant Optimization (TIO) approach is applied to transform the MPC optimization problem with both continuous and integer decision variables into a nonlinear continuous optimization problem. The middle-level problem determines the allocation of time slots for the maintenance interventions suggested at the high level to optimize the trade-off between traffic disruption and the setup cost of maintenance slots. Based on the high-level intervention plan, the low-level problem determines the optimal clustering of the basic units to be treated by a maintenance agent, subject to the time limit imposed by the maintenance slots. The proposed approach is applied to the optimal treatment of squats, with real data from the Eindhoven-Weert line in the Dutch railway network.


Downloads:
 * Online version of the paper
 * Corresponding technical report: pdf file (1.79 MB)
      Note: More information on the pdf file format mentioned above can be found here.


Bibtex entry:

@article{SuJam:17-014,
        author={Z. Su and A. Jamshidi and A. N{\'{u}}{\~{n}}ez and S. Baldi and B. {D}e Schutter},
        title={Multi-level condition-based maintenance planning for railway infrastructures -- {A} scenario-based chance-constrained approach},
        journal={Transportation Research Part C},
        volume={84},
        pages={92--123},
        month=nov,
        year={2017},
        doi={10.1016/j.trc.2017.08.018}
        }



Go to the publications overview page.


This page is maintained by Bart De Schutter. Last update: June 25, 2018.