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Timetabling the courses offered at the Computer Science Department of the University of Munich requires the processing of hard and soft constraints. Hard constraints are conditions that must be satisfied, soft constraints, however, may be violated, but should be satisfied as much as possible. This paper shows how to model our timetabling problem as a partial constraint satisfaction problem and gives a concise finite domain solver implemented with Constraint Handling Rules that, by performing soft constraint propagation, allows for making soft constraints an active part of the problem solving process. Furthermore, we improve efficiency by reusing parts of the timetable of the previous year. Our prototype needs only a few minutes to create a timetable while manual timetabling usually takes a few days. It was presented at the Systems’98 computer fair in Munich and several universities have enquired for it.