Our main focus is research in the field of applied stochastic processes, where issues of queuing theory are in the foreground. Due to the variety of tasks various mathematical methods are used. For the treatment of queueing networks we use techniques of diffusion approximation and decomposition. The analysis of condition-based operating systems, such as occur in telecommunication and manufacturing systems, we were able to reduce the calculation of special subdominanter solutions of linear difference and differential equations. Here especially generalizations of continued fractions play an important role. If there is no analytical solution available for some problem, we use heuristics which are mostly based on limit theorems or put an event simulation.

In the context of industrial projects, we are often confronted with optimization problems under uncertainty. We solve the predominantly nonlinear problems using genetic algorithms.