Abstract Machine learning (ML) has been increasingly used to aid aerodynamic shape
optimization (ASO), thanks to the availability of aerodynamic data and continued …

As climate change is exacerbated and existing resources are depleted, the need for
sustainable industries becomes ever so important. Aviation is not an exception. Despite the …

Abstract The Surrogate Modeling Toolbox (SMT) is an open-source Python package that
offers a collection of surrogate modeling methods, sampling techniques, and a set of sample …

In recent years, the research community has witnessed an explosion of literature dealing
with the mimicking of behavioral patterns and social phenomena observed in nature towards …

The surrogate modeling toolbox (SMT) is an open-source Python package that contains a
collection of surrogate modeling methods, sampling techniques, and benchmarking …

The expected improvement (EI) algorithm is a very popular method for expensive
optimization problems. In the past twenty years, the EI criterion has been extended to deal …

Many industrial applications require time-consuming and resource-intensive evaluations of
suitable solutions within very limited time frames. Therefore, many surrogate-assisted …

The global optimization of a high-dimensional black-box function under black-box
constraints is a pervasive task in machine learning, control, and engineering. These …

Engineering optimization problems usually involve computationally expensive simulations
and many design variables. Solving such problems in an efficient manner is still a major …

Surrogate models provide an affordable alternative to the evaluation of expensive
deterministic functions. However, the construction of accurate surrogate models with many …