  The paper presents a study of local search heuristics in general and variable
neighborhood search in particular for the resolution of an assignment problem
studied in the practical work of universities. Here, students have to be
assigned to scientific topics which are proposed and supported by members of
staff. The problem involves the optimization under given preferences of
students which may be expressed when applying for certain topics.
  It is possible to observe that variable neighborhood search leads to superior
results for the tested problem instances. One instance is taken from an actual
case, while others have been generated based on the real world data to support
the analysis with a deeper analysis.
  An extension of the problem has been formulated by integrating a second
objective function that simultaneously balances the workload of the members of
staff while maximizing utility of the students. The algorithmic approach has
been prototypically implemented in a computer system. One important aspect in
this context is the application of the research work to problems of other
scientific institutions, and therefore the provision of decision support
functionalities.
