Dynamic optimization problems in chemical processes are often quite challenging because
these problems often involve multiple and conflicting objectives. To solve the multi-objective …

Simultaneous optimization of multiple objective functions results in a set of trade-off, or
Pareto, solutions. Choosing a, in some sense, best solution in this set is in general a …

Abstract Nonlinear Model Predictive Control (NMPC) is a powerful technique that can be
used to control many industrial processes. Different and often conflicting control objectives …

A numerical method is proposed for constructing an approximation of the Pareto front of
nonconvex multi-objective optimal control problems. First, a suitable scalarization technique …

Dynamic optimization techniques for complex nonlinear systems can provide the process
industry with sustainable and efficient operating regimes. The problem with these regimes is …

In chemical engineering applications, process design and operation need to be optimized
for criteria such as profit, capital cost, conversion, yield and emissions simultaneously …

The manufacturing industry is faced with the challenge to constantly improve its processes,
eg, due to lower profit margins, more strict environmental policies and increased societal …

Dynamic optimization solutions largely rely on the accuracy of the underlying mathematical
models. However, these models only represent an approximation of the real dynamic …

In recent decades, the study and development of numerical strategies for cancer treatment
have become increasingly feasible, thanks to the advancement of numerical techniques and …

Building complexes have demands of electricity, cooling capacity for air conditioning, and
sanitary hot water. These demands can be met efficiently using multigeneration systems …