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 …

While methods for optimization under uncertainty have been studied intensely over the past
decades, the explicit consideration of the interplay between uncertainty and time has gained …

In the large-scale industries, optimization of multi-type energy systems to minimize the total
energy cost is of great importance and has received worldwide attentions. In the real …

In this paper, we present a brief overview of enterprise-wide optimization and challenges in
multiscale temporal modeling and integration of different models for the levels of planning …

In this work, we address the modeling and solution of mixed-integer linear multistage
stochastic programming problems involving both endogenous and exogenous uncertain …

A novel data‐driven approach for optimization under uncertainty based on multistage
adaptive robust optimization (ARO) and nonparametric kernel density M‐estimation is …

We address the long-term planning of electric power infrastructure under uncertainty. We
propose a Multistage Stochastic Mixed-integer Programming formulation that optimizes the …

To addresses the design and operations of resilient supply chains under uncertain
disruptions, a general framework is proposed for resilient supply chain optimization …

Biorefineries are designed to utilize a combination of various technologies to transform
biomass derived raw materials into different value-added products. This strategy has been …

Energy systems analysis supports in designing and operating reliable and cost-effective
energy solutions to a range of sectors, including power, heating, mobility, and industry …