Uncertainty or error occurs as a result of a lack or misuse of knowledge about specific topics
or situations. In this review, we recall the differences between error and uncertainty briefly …

A near-global optimization approach is proposed to design blending recipes for refinery
products under uncertainties. In the refining industry, the most valuable products, such as …

This article presents a study on the optimal design and operation of a pilot-scale absorber
column in post-combustion CO 2 capture in the presence of uncertainty. A mechanistic …

Dynamic experiments that yield as much information as possible are highly valuable for
estimating parameters in nonlinear dynamic processes. Techniques for model-based …

Nonlinear model predictive control (NMPC) has become an important tool for optimization
based control of many (bio) chemical systems. A requirement for a well-performing NMPC …

We present a scalable computing framework for the solution stochastic multiobjective
optimization problems. The proposed framework uses a nested conditional value-at-risk …

Practical chemical process is usually a dynamic process including uncertainty. Stochastic
constraints can be used to chemical process modeling, where constraints cannot be strictly …

An approach for the optimal design of chemical processes in the presence of uncertainty
was presented. The key idea in this work is to approximate the process constraint functions …

Generally, chemical processes are designed with the use of inaccurate mathematical
models. Therefore, it is important to create a chemical process that guarantees the …

Model-based design principles have received considerable attention in biotechnology and
the chemical industry over the last two decades. However, parameter uncertainties of first …