Abstract Process Systems Engineering (PSE) is the scientific discipline of integrating scales
and components describing the behavior of a physicochemical system, via mathematical …

This paper reviews recent advances in the field of optimization under uncertainty via a
modern data lens, highlights key research challenges and promise of data-driven …

Manufacturing is continuously evolving from concept development to methods and tools
available for the production of goods for use or sale. Traditionally, manufacturing refers to an …

This paper gives a review on existing scheduling methodologies developed for process
industries. Above all, the aim of the paper is to focus on the industrial aspects of scheduling …

This work examines applying deep reinforcement learning to a chemical production
scheduling process to account for uncertainty and achieve online, dynamic scheduling, and …

Energy is a key driver of the modern economy, therefore modeling and simulation of energy
systems has received significant research attention. We review the major developments in …

Supply chain management and optimisation is a critical aspect of modern enterprises and a
flourishing research area. This paper presents a critical review of methodologies for …

Robust counterpart optimization techniques for linear optimization and mixed integer linear
optimization problems are studied in this paper. Different uncertainty sets, including those …

Optimization under uncertainty has been an active area of research for many years.
However, its application in Process Systems Engineering has faced a number of important …

To ensure the autonomous power supply in microgrids (MGs) in stand-alone mode while
also maintaining stability, energy storage systems (ESSs) and demand-side flexibility can be …