This master thesis considers a new type of personnel planning problem. Besides the usual assignment of personal to tasks and time-windows with the usual side constraints, it also addresses structured qualifications. These qualifications are characterized by the combination of different categorical and hierarchical skills with the multi-tasking capability and the experience of the staff members. This master thesis provides an integer optimization model (ILP-model) to assign tasks to staff members. Each task has to be fulfilled by a worker with a suitable qualification. Tasks also differ in their level of intensity; several of them could be performed simultaneously by one person. The possibility of combining temporal overlapping tasks not only depends on the task itself but also on the qualifications of the assigned person. To model the complicated covering of several tasks by individual workers a worker-dependent and a task-dependent conflict matrix was employed.The developed model was applied to a real-world personnel planning problem encountered at Grazer Spielstätten (a subsidiary of Bühnen Graz), a company operating event locations in Graz. For each day of the planning horizon several events are given, each of them with a long list of tasks. Besides the usual legal regulations and union rules concerning e.g. working time, split shifts, breaks, days off and weekends, the planning scenario has very different tasks to be executed on each working day, namely different in duration, required skill and intensity. The necessary duties have to be fulfilled by a highly heterogenous workforce. Moreover, it is possible for one worker to fulfill several tasks at the same time, but this ability depends again on the particular task, the required intensity and on the individual worker. The extended model was implemented in Python PuLP and combined with an open-source solver to be included in a real-world planning system.