The present work addresses rail traffic rescheduling in case of electric infrastructure failure. The power available for train traction is restricted and the traffic should be reorganized according to this constraint. The system behavior is analyzed by simulation, using a dynamic multi-physics railway simulator that gives physical quantities such as train's speed profiles, voltage along the catenary lines, heating's…The rescheduling problem relies on this black box model, with a large number of input variables, constrained dynamic outputs (typically voltage limits). It involves a complex simulator and a high computation cost. We propose a rescheduling process based on regional sensitivity analysis. Monte Carlo filtering and the two-sample Kolmogorov-Smirnov test statistics are used in order to analyze which rescheduling actions are efficient to obtain an acceptable traffic (respect of operational constraints). Our methodology allows to identify important inputs and reduce the problem's dimension. Non-influential variables are set to a fixed value, and an optimization post treatment can be performed with the remaining influential variables and performance indicator defined by the operator. This analysis allows the decision maker to choose the solution which best fits his objectives. The proposed approach has been tested on a multi-line heterogeneous traffic. The considered incident is a loss of feeding power substation.