In the CAPMO-Train project, we aimed to illuminated the possibilities of automated, optimized train-dispatcher shifts that take all legal and operational restrictions into account and integrate train-dispatcher workload. To this end, we developed an optimization frame-work for shift scheduling. We exemplified our framework with results for Malmo¨ dispatching center, but the framework itself is flexible and can be applied for other dispatching centers. We derived the number of train movements in a dispatching area during a time period as an approximation for the objective task load (which is correlated to the subjective dispatcher workload) and inferred an upper bound for this approximation based on discussion with operational experts. Together with legal and operational requirements for train-dispatcher shifts, this task-load measure build the basis for the optimization framework. For the framework, we designed several mathematical optimization models: - We designed an integer programming (IP) model to compute optimal one-day tac-tical shift plans, taking legal and operational requirements and the current knowledge on the current timetable (and possibly a maintenance plan) in the form of the task-load approximation into account. With this first IP, we minimized the number of dispatchers. That is, we established a lower bound on how many dispatchers can be scheduled. We showcased that we can automate the scheduling problem with experimental studies on real-world-sized instances (and in presentations to Trafikverket also on real-world instances), computing the optimum solutions within a few minutes. With an improved model, we could achieve runtimes of a few seconds. - To improve the quality of the shifts, we designed an IP model to compute optimal one-day tactical shift plans, minimizing the number of area-dispatcher-assignment switches (handover), while also forbidding undesired start times for shifts and too short shifts. Here, we compared four different approaches to track these handovers. We showcased that it is possible to compute one-day shift plans with the minimum number of handovers using the minimum number of dispatchers from the first models with experimental studies on real-world-sized instances (and in presentations to Trafikverket also on real-world instances) within less than two hours. - We expanded the first model (for minimizing the number of dispatchers) to enforce the scheduling of breaks to compare schedules with and without breaks for different maximum shift lengths. Here, we aimed to highlight trade-offs between the number and length of breaks, the length of shifts and the number of dispatchers needed, to show the operational planers what an introduction of scheduled breaks (today no breaks are scheduled in the shift plans) would yield. - We designed an IP model for weekly tactical shift plans, taking the output of the handover-minimization model as building blocks to create shift plans that take a large variety of additional legal requirements into account. That is, here we compute the optimum weekly plans with respect to the input shifts. With this we cannot guarantee (and will likely not achieve) the global optimum, but because of the large number and intricacy of the additional requirements from the union agreement, we do not deem the computation of the global optimum feasible within reasonable time bounds. The runtime of our approach in some first experiments reach nearly 20 minutes in experimental studies on real-world-sized instances. Hence, we showcase that it is possible to automate this task. The overall goal of the CAPMO-Train project was to enable Trafikverket to automatically find cost-effective and safe train dispatcher shifts. The development of a tool for tactical shift planning based on the optimization framework was out of the scope of this project. That is, within this project we developed methods and programs that can be used by researchers/experts and which we used to produce solutions for exemplary problems. However, we did not develop a tool that Trafikverket can use in its current planning (which would require data bases, a well-developed graphical user interface etc.). But we discussed the optimal tactical shift plans with operational experts to include as many real-world conditions as possible. With this we laid out a possible way ahead for an implementation. Some slight deviation from the original project specification was necessary, and we detail that in Subsection 4.3 of this report.