We address the applicability of a hybrid quantum–classical heuristics for practical railway rescheduling management problems. We build an integer linear programming model and solve it with D-Wave's quantum–classical hybrid solver (CQM) as well as with CPLEX, for comparison. The proposed approach is demonstrated on a real-life heterogeneous urban network in Poland, including both single- and multi-track segments. All the requirements posed by the operator of the network are included in the model. The computational results demonstrate the readiness for application and the benefits of quantum–classical hybrid solvers in a realistic railway scenario: they yield acceptable solutions on time, which is a critical requirement in a rescheduling situation. In particular, CQM as a probabilistic heuristic solver provides a number of feasible, close-to-optimal solutions the dispatcher can choose from.