Model-based Methods for Continuous and Discrete Global Optimization

The article “Model-based Methods for Continuous and Discrete Global Optimization” by Thomas Bartz-Beielstein and Martin Zaefferer  will be published in Applied Soft Computing Journal. It will be available soon.

The first part of this article presents a survey of model-based methods, focusing on continuous optimization. It introduces a taxonomy, which is useful as a guideline for selecting adequate model-based optimization tools. The second part provides details for the case of discrete optimization problems. Here, six strategies for dealing with discrete data structures are introduced. A new approach for combining surrogate information via stacking is proposed in the third part.