With the ambition of policy makers to encourage a modal shift to rail, an increase in the demand for running trains can be expected. Capacity wise, this increase in demand could be facilitated by applying moving-block signalling. If railway traffic increases however, so does the difficulty of managing it. Rescheduling systems are currently being developed to help traffic managers with this task. An increase in traffic does however increase the computation time needed for solving the conflict resolution optimization problem tackled by these systems. This could pose a problem since traffic management is a task performed in real-time. An often proposed technique to reduce computation time for conflict resolution is decomposing the problem into multiple coordinated sub-problems. Until now, no research has been performed combining moving-block signalling with decomposition of the conflict resolution problem. This research addresses this gap by developing and testing a distributed moving-block conflict resolution model. The effect of the model on computation time and solution quality in comparison to a centralized model is investigated through a case study of the rail network of the Dutch province Noord-Brabant. The results show a clear improvement in computation time for the distributed model while the solution quality improves or remains the same in the majority of tested scenarios.