Workshop

Robust optimization deals with uncertainties in parameters describing optimization problems and their impact to proposed solutions.

Wald’s classical determistic maximin approach for robust optimization delivering the best outcome under worst assumed parameter setting is often too conservative for practical purposes as it typically comes with a highcost for security. On the other hand, probabilistic settings for robust optimization quantifying uncertainties by probability distributions of parameters and using stochastic optimization to compute moments or distributions of outcomes is often time consuming or even intractable.

The workshop with six invited talks and contributed practical applications will discuss recent approaches and results around deterministic and probabilistic robust optimization from different point of views and will encourage interdisciplinary dialogue and cooperation between mathematicians and practitioners.

Everybody interested in the subjects is cordially invited. Registration is not required.