The conference series aims at bringing together researchers and practitioners working in the interdisciplinary field of machine learning and optimization to present and discuss recent developments.
Our research assistant and doctoral student Söhnke Maecker participated in this event and presented “An Efficient Data Structure for Unrelated Parallel Machine Scheduling in Distributed Manufacturing Systems”. The contribution features a technique to conduct computationally highly-efficient local search for a parallel machine scheduling problem that considers job delivery.
With more than 50 presentations, the well-organized event offered an excellent platform for the participants to exchange ideas on how to apply machine learning methods to optimization problems and how optimization can be used to improve machine learning techniques. This was facilitated by an accompanying social program featuring a collective dinner in the beautiful historic city of Cádiz.