The impact of delays and disturbances in railway traffic can be mitigated by advanced rail traffic rescheduling models (RTRMs) which make use of mathematical optimization models. In the past several researches have been carried out on the effectiveness of an RTRM in reducing delay and improving punctuality. However, in most of these researches only one case study is used to test the RTRM. Still, it is unclear whether the results found for the application of an RTRM in one particular situation, are also valid for other situations (with different infrastructural and operational characteristics). With this research, the impact of different infrastructure layouts and traffic patterns on the effectiveness of rail traffic rescheduling models is investigated. It provides insight into whether the benefit of an RTRM depends on the infrastructure and timetable in the area where it is applied. For this purpose, an evaluation framework has been developed in which an RTRM can be tested using different infrastructure, operational and disturbance scenarios. In this framework, the RTRM is used to generate a real-time traffic plan for each scenario. These traffic plans are compared with the traffic plans of simple dispatching rules, that can be used in practice by dispatchers. For this comparison, KPIs such as the sum of consecutive delay (amount of delay that propagates within the network) and punctuality are used. This framework is applied to an alternative graph-based RTRM, which is formulated as a MILP (mixed integer linear programming). The results show that the improvement an RTRM can offer over simple dispatching rules, varies per infrastructure layout and traffic pattern. For some infrastructure and operational scenarios, the simple dispatching rules perform as well as the RTRM, which means that for these situations, implementing an advanced RTRM does have much added value. A trend has been observed that the effectiveness of the RTRM increases as more control options are available.