The idea of using a simpler surrogate to represent a complex phenomenon has gained
increasing popularity over past three decades. Due to their ability to exploit the black-box …

The ability to accurately model and simulate chemical processes has been paramount to the
growing success and efficiency in process design and operation. These improvements …

Surrogate models are used to map input data to output data when the actual relationship
between the two is unknown or computationally expensive to evaluate for several …

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

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 …

Contemporary engineering design is heavily based on computer simulations. Accurate, high-
fidelity simulations are used not only for design verification but, most importantly, to adjust …

Objective functions that appear in engineering practice may come from measurements of
physical systems and, more often, from computer simulations. In many cases, optimization of …

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

Surrogate-based optimization (Queipo et al. 2005, Simpson et al. 2008) represents a class
of optimization methodologies that make use of surrogate modeling techniques to quickly …

Surrogate models–simple functional approximations of complex models–can facilitate
engineering analysis of complicated systems by greatly reducing computational expense …