Uncertainties are widespread in the optimization of process systems, such as uncertainties
in process technologies, prices, and customer demands. In this paper, we review the basic …

The importance of data science and big data analytics is growing very fast as organizations
are gearing up to leverage their information assets to gain competitive advantage. The …

State-of-the-art decision tree methods apply heuristics recursively to create each split in
isolation, which may not capture well the underlying characteristics of the dataset. The …

JuMP is an open-source modeling language that allows users to express a wide range of
optimization problems (linear, mixed-integer, quadratic, conic-quadratic, semidefinite, and …

Bridging cultures that have often been distant, Julia combines expertise from the diverse
fields of computer science and computational science to create a new approach to …

Electrochemical energy storage (ES) units (eg, batteries) have been field-validated as an
efficient back-up resource that enhances resilience of distribution systems. However, using …

With declining costs of battery storage, there is growing interest to deploy them in power
systems to provide multiple grid services that directly support integration of variable …

About a year into the pandemic, COVID-19 accumulates more than two million deaths
worldwide. Despite non-pharmaceutical interventions such as social distance, mask …

The increasing penetration of distributed energy resources in the distribution grid is
producing an ever-heightening interest in the use of the flexibility on offer by said distributed …

Optimal Power Flow (OPF) dispatches controllable generation at minimum cost subject to
operational constraints on generation and transmission assets. The uncertainty and …