Optimizing rake-links independently of timetables in railway operations

Abstract

This study addresses optimal rake-link formation in large-scale timetabled rail operations by modeling the problem as a directed acyclic graph and solving it via the minimum path cover algorithm. It enables efficient rake-to-service assignment while minimizing fleet size. Crucially, it decouples rake-link optimization from the timetable planning process, allowing planners to evaluate feasible rake configurations independently. The model incorporates operational constraints such as deadhead limits, service balance, and slack allowances. Applied to real-world data from Indian Railways, the results reveal clustered Pareto fronts in the decision space, indicating robust and redundant solutions. The approach lays a foundation for resilient, adaptive rail management via digital twin systems.