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With increase in the use of railway transport, ensuring robustness in railway timetables has never been this important. In a dense railway timetable even a small disturbance can propagate easily and affect trains' arrival and departure times. In a robust timetable small delays are absorbed and knock-on effects are prevented effectively. The aim of this thesis is to study how optimization tools can support the generation of robust railway traffic timetables. We address two Train Timetabling Problems (TTP) and for both problems we apply Mixed Integer Linear Programming (MILP) to solve them from network management perspectives. The first problem is how robustness in a given timetable can be assessed and ensured. To tackle this problem, a headway-based method is introduced. The proposed method is implemented in real timetables and evaluated from performance perspectives. Furthermore, the impact of the proposed method on capacity utilization, heterogeneity and the speed of trains, is monitored. Results show that the proposed method can improve robustness without imposing major changes in timetables. The second problem addressed in the thesis is how robustness can be assessed and maintained in a given timetable when allocating additional traffic and maintenance slots. Different insertion strategies are studied and their consequences on capacity utilization and on the properties of the timetables are analyzed. Two different insertion strategies are considered: i) simultaneous and ii) stepwise insertion. The results show that inserting the additional trains simultaneously usually results in generating more optimal solutions. However, solving this type of problem is computationally challenging. We also observed that the existing robustness metrics cannot capture the essential properties of having more robust timetables. Therefore we proposed measuring Channel Width, Channel Width Forward, Channel Width Behind and Track Switching. Furthermore, the experimental analysis of the applied MILP model shows that some cases are computationally hard to solve and there is a need to decrease the computation time. Hence several valid inequalities are developed and their effects on the computation time are analyzed. This thesis contains three papers which are appended. The results of this thesis are of special interests for railway traffic planners and it would support their working process. However, railway traffic operators and passengers also benefit from this study

Optimization-Based Methods for Revising Train Timetables with Focus on Robustness