Model-based methods for continuous and discrete global optimization

Thomas Bartz-Beielstein, Martin Zaefferer

Abstract: Highlights•Up-to-date survey and comprehensive taxonomy of surrogate model based optimization algorithms.•Covers continuous and discrete/combinatorial search spaces.•Presents six strategies for dealing with discrete data structures.•New strategy for model selection and combination in surrogate model-based optimization.•Outlook on important challenges (model selection, dimensionality, benchmarks, definiteness) and research directions.