The keynote talk “A Survey of Model-Based Methods for Global Optimization” is available on videolectures.net.
This lecture introduces model-based methods for global optimization. Fundamental aspects of and recent advances in surrogate-model based optimization are discussed. Strategies for selecting and evaluating surrogates are presented. The lecture concludes with a description of key features of two state-of-the-art surrogate model based algorithms, namely the evolvability learning of surrogates (EvoLS) algorithm and the sequential parameter optimization (SPO).
This lecture is part of a project that has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No 692286.
It was recorded during the 7th International Conference on Bioinspired Optimization Methods And Their Applications (BIOMA), Bled 2016.