Integrated condition-based track maintenance planning and crew scheduling of railway networks

Integrated condition-based track maintenance planning and crew scheduling of railway networks

Su, Z. (TU Delft Team Bart De Schutter)
Jamshidi, A. (TU Delft Railway Engineering)
Nunez, Alfredo (TU Delft Railway Engineering)
Baldi, S. (TU Delft Team Bart De Schutter)
De Schutter, B.H.K. (TU Delft Delft Center for Systems and Control; TU Delft Team Bart De Schutter)

Delft Center for Systems and Control

2019

We develop a multi-level decision making approach for optimal condition-based maintenance planning of a railway network divided into a large number of sections with independent stochastic deterioration dynamics. At higher level, a chance-constrained Model Predictive Control (MPC) controller determines the long-term section-wise maintenance plan, minimizing condition deterioration and maintenance costs for a finite planning horizon, while ensuring that the deterioration level of each section stays below the maintenance threshold with a given probabilistic guarantee in the presence of parameter uncertainty. The resulting large MPC optimization problem containing both continuous and discrete decision variables is solved using Dantzig-Wolfe decomposition to improve the scalability of the proposed approach. At a lower level, the optimal short-term scheduling of the maintenance interventions suggested by the high-level controller and the optimal routing of the corresponding maintenance crew is formulated as a capacitated arc routing problem, which is solved exactly by transforming it into a node routing problem. The proposed approach is illustrated by a numerical case study on the optimal treatment of squats of a regional Dutch railway network. Simulation results show that the proposed approach is robust, non-conservative, and scalable.

Chance-constrained optimization
Condition-based maintenance planning
Distributed optimization
Railway infrastructure

http://resolver.tudelft.nl/uuid:d1ce2230-b625-47ff-b631-ea22df935c15

https://doi.org/10.1016/j.trc.2019.05.045

2019-12-14

0968-090X

Transportation Research. Part C: Emerging Technologies, 105, 359-384

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

journal article

© 2019 Z. Su, A. Jamshidi, Alfredo Nunez, S. Baldi, B.H.K. De Schutter