In order to effectively judge the geometric state of track and adapt to the maintenance state of highspeed railway, the optimization of track irregularity maintenance strategy is studied. The Markov decision process is selected, the model parameters such as track state level, maintenance action space and maintenance action cost are set, and the value iteration algorithm is used to solve the problem, so as to realize the effective formulation of high-speed railway line maintenance plan. Taking a ballasted high-speed railway line in East China as an example, combined with the characteristics of the track unit at typical deterioration speed, the maintenance decision optimization process of the Markov decision model is analyzed and the effect is verified. At the same time, the optimal maintenance decision of the track unit section at each decision time is explored. Monte Carlo stochastic simulation is used to simulate the total maintenance cost in the planning cycle and compare it with the actual maintenance cost. The results show that the track irregularity maintenance decision based on Markov decision process can fully consider the heterogeneity of track unit section irregularity deterioration, scientifically arrange maintenance activities according to the actual state and deterioration law of track unit section, improve the spatial resolution of maintenance operation, and the optimization effect of maintenance decision in the planning cycle is remarkable, which reduces the maintenance cost while ensuring the high smoothness of the line, and has a guiding role in the maintenance and repair of railway track.