A Heuristic Approach to Train Maintenance Scheduling Using Simulated Annealing

The optimization of maintenance depot operations is a crucial element in ensuring the quality of railway transportation. Maintenance depots are complex systems with many processes that can be optimized, one of which is the sequencing of individual maintenance activities. These activities can be numerous, and the number of possible sequencing variations is also large. Due to the scale of such an optimization problem, exact methods do not appear to be suitable because of their long computation times. Therefore, our research focuses on the use of the heuristic algorithm Simulated Annealing. In the implementation of this algorithm, several neighborhood transition strategies were proposed, allowing for a more thorough exploration of the solution space. Experiments show that the results are of satisfactory quality compared to exact approaches and require only a fraction of the computation time.