Abstract: An algorithm for constructing inflow control plans based on a capability bottleneck feedback-relief strategy was proposed in this work, aiming at programming a regular inflow control scheme for large-scale rail transit networks during peak hours. The core idea of the algorithm is "source tracing", which is to control major stations where inflows travelling through the capacity-bottleneck section, so as to relieve congestion of the bottleneck section. The algorithm based on the intrinsic relationship between the station passenger flow and section flow uses the feedback mechanism to unravel the bottleneck and then determines the target control station, control period and control strength in reverse. In construction processes, the correlation among multiple bottlenecks of the network, the coordination control of stations, and the transitivity of the demand during the control period were fully considered to achieve a scientific and efficient formulation of the inflow control solution. A decision support system based on the proposed algorithm and the Beijing subway network in 2017 was conducted in the empirical study. Results show that the algorithm can efficiently formulate inflow control schemes. Compared to actual section flows between the constructed plan and the real control scheme, it is shown that the proposed scheme can effectively reduce travel delay time of passengers and verify the rationality and accuracy of the algorithm. This study provides theoretical and methodological supports for inflow control organizations and has a nice promotion and application value.