A network-based method for the EMU train high-level maintenance planning problem

Electric Multiple Unit (EMU) high-level maintenance planning is a typical discrete system. EMU high-level maintenance (HM) planning determines when to undergo HM or execute transportation task for train-sets, based on practical requirements such as passenger transport demand, workshop maintenance capacity, and maintenance regulations. This research constructs a time-state network that can display the transformation processes between different states. On this basis, a path based model and its improvement are developed to minimize the HM costs with consideration of all necessary regulations and practical constraints. To handle the solution space, a path set generation method is presented. A real-world instance from Shanghai Railway, which is the largest affiliate in China Railway Corporation, was conducted to demonstrate the efficiency and effectiveness of the proposed approach, which indicates that the model can be solved to optimum within short computational times by the state-of-the-art solver Gurobi. Moreover, a sensitivity analysis was also performed to evaluate the effects of the variation in average daily operating mileage, HM capacity at the depot and the assumed minimum value of cumulative mileage.