Most real-world problems involve some type of optimization problems that are often
constrained. Numerous researchers have investigated several techniques to deal with …

Coronary artery disease (CAD) is the most common cardiovascular disease (CVD) and often
leads to a heart attack. It annually causes millions of deaths and billions of dollars in …

Context. Complex organic molecules (COMs) are ubiquitously detected in the gas phase
and thought to be mostly formed on icy grains. Nevertheless, there have not been any …

Automated machine learning (AutoML) is a young research area aiming at making high-
performance machine learning techniques accessible to a broad set of users. This is …

The last few years have witnessed a surge in methods for symbolic regression, from
advances in traditional evolutionary approaches to novel deep learning-based systems …

Job shop scheduling (JSS) is a process of optimizing the use of limited resources to improve
the production efficiency. JSS has a wide range of applications, such as order picking in the …

Deep neural operators can learn operators map** between infinite-dimensional function
spaces via deep neural networks and have become an emerging paradigm of scientific …

The recent years have witnessed the rise of accurate but obscure decision systems which
hide the logic of their internal decision processes to the users. The lack of explanations for …

The rise of sophisticated machine learning models has brought accurate but obscure
decision systems, which hide their logic, thus undermining transparency, trust, and the …

The development of electric vehicles (EVs) depends on several factors: the EV's acquisition
price, autonomy, the charging process and the charging infrastructure. This paper is focused …