Optimization Model And Algorithm For Rolling Stock Maintenance Scheduling In Metro

The efficiency of metro rolling stock maintenance directly affects the safety and capability of train operation in the main line. Aiming at the optimization problem of rolling stock maintenance scheduling (RSMS) in metro, a multi-objective mixed integer nonlinear bi-level programming model was presented in this paper to improve the efficiency of maintenance as well as the availability of the rolling stock in the planning horizon. In the model, maintenance systems, train operation timetable in the main line and maintenance capacity of the crews are taken into comprehensive consideration. To solve the optimal solutions quickly, the static variable ordering heuristics according to a possible minimum value of the start time of the maintenance, the dynamic value ordering heuristics according to the minimum value and the constraint propagation based on the maintenance cycle are imbedded in the basic backtracking algorithm. Finally, the effectiveness of the model and the algorithm is verified by the instances from Chengdu Metro Line 2 in China.