Workshop

Semi-infinite optimization, i.e., the solution of optimization problems with infinitely many constraints (SIP), has been intensively studied over the last decades. The progress of computer technology has enhanced SIP methodology significantly. On the one hand, solution methods for this problem class have been increasingly developed and refined. On the other hand, high-dimensional problems, as they often occur in practice, have become numerically tractable. As a result, the range of possible applications has evolved considerably and semi-infinite optimization has been increasingly applied to practical problems in recent years.

In addition to the standard applications of semi-infinite optimization such as model approximation, design centering, robust optimization, and optimal control, SIP techniques have been recently used in machine learning, design of experiments, coverage issues and mixed stochastic-robust optimization. Thereby, SIP methods have been applied in application areas such as product portfolio optimization and process engineering.

The one and a half day workshop provides the opportunity to discuss and promote the use of semi-infinite optimization in practice with outstanding international scientists and application experts.

Confirmed invited talks are

• Süreyya Aküz (Bahçeşehir University Istanbul): Semi-infinite Optimization in Machine Learning
  
• René Henrion (WIAS Berlin): Dealing with Probust Constraints in Stochastic Optimization
• Alexander Mitsos (RWTH Aachen): Contingency Screening for Power Grids Using Existence-Constrained Semi-Infinite Programs
• Gerhard-Wilhelm Weber (Poznan University of Technology): A Stochastic Maximum Principle for a Markov Regime-Switching Jump-Diffusion Model with Delay and an Application to Finance
• Ralf Werner (University of Augsburg): Non, je ne regrette rien