Towards simulation-driven framework for optimising rail depot operations and maintenance scheduling

Efficient and sustainable Train Fleet Maintenance (TFM) is essential for realising the full environmental benefits of rail transport. This paper presents an integrated framework that combines short-term maintenance scheduling optimisation with Discrete Event Simulation (DES) to enhance the adaptability, reliability, and sustainability of depot operations, including maintenance activities. The scheduling tool, underpinned by Mixed Integer Programming and a formal ontological model, generates cost-effective maintenance plans that consider operational constraints. These plans are validated using a detailed DES model built in AnyLogic Software, which replicates depot layouts, rules, and capacities. Simulation enables early conflict detection, proactive adjustments, and reductions in unnecessary movements, energy use, and emissions. A realistic case study demonstrates how the integrated approach supports continuous improvement and improves asset utilisation. The results highlight the potential of combining optimisation and simulation to support greener and more resilient maintenance planning. Future work will focus on formal validation and integration with broader decision-support systems to accelerate the transition to low-carbon rail networks.