  It is an important objective pursued in a railway agency or company to reduce
the major maintenance costs of electric multiple unit (EMU). The EMU major
maintenance schedule decides when to undergo major maintenance or undertake
transportation task for train-set, based on practical requirements, such as
passenger transport demand, workshop inspection capacity, and maintenance
requirements. Experienced railway practitioners can generally produce a
feasible major maintenance schedule; however, this manual process is
time-consuming, and an optimal solution is not guaranteed. This research
constructs a time-space network that can display the train-set status
transformation process between available and major maintenance status. On this
basis, a 0-1 integer programming model is developed to reduce the major
maintenance costs with consideration of all necessary regulations and practical
constraints. Compared with the manual process, the genetic algorithm with
simulated annealing survival mechanism is also developed to improve solution
quality and efficiency. It can reduce the complexity of the algorithm
substantially by excluding infeasible solutions when constructing the model.
