The doctoral programme VIENNA GRADUATE SCHOOL ON COMPUTATIONAL OPTIMIZATION is funded by
Modern optimization methods are a key issue in successful decision making in many areas such as energy production and trading, financial and insurance management, transportation and communication, network design and bioinformatics.
The short time goal of the research and training program of this Graduate School is to give the PhD candidates a comprehensive training in optimization with special emphasis on algorithmic and computational aspects as well as to prepare them for a scientific career by introducing them into the scientific networks of the participating scientists. The structure of the DK+ program also allows to study the relations between different areas of optimization. In long term we will foster collaboration between the members and their respective institutions in order to make Vienna a place of excellence in Computational Optimization.
The different areas of optimization covered by the faculty members of the program are:
- Combinatorial Optimization (Henzinger, Raidl),
- Global Optimization (Bomze, Bot, Neumaier, Schichl),
- Heuristic Optimization (Neumaier, Schichl, Raidl),
- Nonlinear Optimization (Bomze, Bot, Neumaier, Uhler),
- Stochastic Optimization (Pflug, Uhler),
- Dynamic Optimization (Pflug, Uhler),
- Algorithmic Game Theory (Bomze, Henzinger),
- Optimization for intelligent Data Analysis (Bomze, Henzinger, Uhler)
- Nonsmooth Optimization (Bot, Pflug, Neumaier, Schichl)
Each field is represented by more than one member, enabling productive cooperation and co-supervision of the PhD students. A special emphasis is put on the algorithmic aspect. It is intended to encourage the collegiates to work on theoretical topics as well as to implement and compare algorithms on a practical basis. Most of the research topics are related to concrete practical problems and the planned work should contribute to the solution of these problems.
University of Vienna
1090 Vienna, Austria
T: +43-1-4277-386 31