The development of pharmaceutical manufacturing processes has been facilitated by recent
advances in the process simulation area. However, since the simulations are usually …

Surrogate‐based optimization approaches have been widely adopted in industrial problems
due to their potential to reduce the number of simulation runs required in the optimization …

Simulation optimization (SO) problems can be difficult to solve because of the lack of
knowledge of the algebraic model equations and the unknown structure of the noise …

With the increasing trend of solving more complex and integrated optimization problems,
there is a need for developing process models that are sufficiently accurate as well as …

Simulation-based optimization using surrogate models enables decision-making through
the exchange of data from high-fidelity models and development of approximations. Many …

The problem of integrated design and control optimization of process plants is discussed in
this paper. We consider it as a nonlinear programming problem subject to differential …

An effective strategy for the sampling, modeling, and optimization of black-box problems with
constraints is proposed. Black-box systems are often approximated and solved using …

An enhanced surrogate assisted framework, based on Probability of Improvement (PI)
method, is proposed in this paper. We made some modifications to the original PI approach …

Surrogate based modeling has been commonly used as a simplification of computationally
complex simulations and processes where the underlying equations are unknown (black …

Surrogate modelling aims to reduce computational costs by avoiding the solution of rigorous
models for complex physicochemical systems. However, it requires extensive sampling to …