The research and teaching activities at the Chair of Numerical Optimization focus on the design, analysis, and application of efficient numerical methods for several classes of optimization problems. They include smooth nonlinear constrained optimization, complementarity problems and variational inequalities, related nonsmooth and degenerate problems, problems in discrete optimization, in particular problems of cutting and packing, optimization tasks in machine learning, and diverse applications.

• Nonlinear Optimization and Applications
• Complementarity Problems and Variational Inequalities
• Nonsmooth and Degenerate Problems
• Machine Learning and Applications