Due to the wide use and key importance of mathematical models in process engineering,
experiment design is becoming an essential tool for the rapid building and validation of …

I have enjoyed very much writing this book. This is very important from a personal point of
view, but I believe this is the key of writing something interesting for the readers. One of the …

A fast new algorithm is proposed for numerical computation of (approximate) D-optimal
designs. This cocktail algorithm extends the well-known vertex direction method (VDM; …

Nature-inspired metaheuristic algorithms, like Particle Swarm Optimization (PSO), are
powerful general-purpose optimization tools but they invariably do not come with rigorous …

Model-based optimal designs for regression problems with multiple objectives are common
in practice. The traditional approach is to construct an optimal design for the most important …

This paper links the chemical kinetic models that obey the framework of nonlinear statistical
models with optimal design theory. We provide the appropriate optimal designs for them, so …

We extend the approach in [Ann. Statist. 38 (2010) 2499–2524] for identifying locally optimal
designs for nonlinear models. Conceptually the extension is relatively simple, but the …

Several common general purpose optimization algorithms are compared for finding A-and D-
optimal designs for different types of statistical models of varying complexity, including high …

CVX‐based numerical algorithms are widely and freely available for solving convex
optimization problems but their applications to solve optimal design problems are limited …

The Arrhenius equation is widely used to describe the relationship between the rate of a
chemical reaction and the temperature. However, in some cases more precision is needed …