It is well-documented how artificial intelligence can have (and already is having) a big
impact on chemical engineering. But classical machine learning approaches may be weak …

The optimization and machine learning toolkit (OMLT) is an open-source software package
incorporating neural network and gradient-boosted tree surrogate models, which have been …

With the continuous progress and development in biomedicine, metallic biomedical
materials have attracted significant attention from researchers. Due to the low compatibility …

Recent developments in data science and machine learning have inspired a new wave of
research into data-driven modeling for mathematical optimization of process applications …

Bayesian Optimization is a useful tool for experiment design. Unfortunately, the classical,
sequential setting of Bayesian Optimization does not translate well into laboratory …

High-speed railway pantograph-catenary system is the only energy transfer pathway to drive
a train operation. Energy transfer quality deteriorates with the increasing train speed and …

Towards the low-carbon goal, a smart grid features remote connection, data sharing, and
cyber–physical integration to increase the flexibility of energy supplies, to reduce electricity …

Some real-world design optimization problems can be formulated as expensive mixed-
variable optimization problems (EMVOPs), which involve both continuous and discrete …

Tree ensembles can be well-suited for black-box optimization tasks such as algorithm tuning
and neural architecture search, as they achieve good predictive performance with little or no …

When assessing demand response to solve optimal scheduling problems, the optimization
algorithm needs to be coupled with the process model in order to quantify the behavior of …