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 …

This manuscript reviews recent advances in deterministic global optimization for Mixed-
Integer Nonlinear Programming (MINLP), as well as Constrained Derivative-Free …

Smart manufacturing (SM) is a new paradigm that allows manufacturing to enter its fourth
revolution by exploiting state-of-the art sensing, communication and computation as the …

Most optimization problems in engineering can be formulated as 'expensive'black box
problems whose solutions are limited by the number of function evaluations. Frequently …

The algorithmic framework ARGONAUT is presented for the global optimization of general
constrained grey-box problems. ARGONAUT incorporates variable selection, bounds …

This paper introduces a novel methodology for the global optimization of general
constrained grey-box problems. A grey-box problem may contain a combination of black-box …

Feasibility analysis is used to determine the feasible region of a multivariate process. This
can be difficult when the process models include black‐box constraints or the simulation is …

In numerous applications across all science and engineering areas, there are optimization
problems where both the objective function and the constraints have no closed-form …

Tree ensembles can be well-suited for black-box optimization tasks such as algorithm tuning
and neural architecture search, as they achieve good predictive performance with little or no …