In simulation-based engineering, design choices are often obtained following the optimization of complex blackbox models. These models frequently involve mi...

Benchmarking new optimization methods on test problems is essential for assessing their performance and tuning their parameters. Yet, few problems are avail...

Solving optimization problems in which functions are blackboxes and variables involve different types poses significant theoretical and algorithmic challeng...

Heterogeneous datasets emerge in various machine learning or optimization applications that feature different data sources, various data types and complex re...

A mathematical framework for modelling constrained mixed-variable optimization problems is presented in a blackbox optimization context. The framework intr...