Ivo Nowak, HAW-Hamburg
We present new decomposition methods for globally solving complex optimization and machine learning problems based on a generate-refine-and-solve (GRS) approach using inner and outer approximations. The methods are implemented in the open-source frameworks Decogo and Decolearn. Numerical results for complex nonconvex MINLPs are presented. Furthermore, we discuss possible extensions, like PDE-constrained optimization and bi-objective ensemble learning.