The class of nature‐inspired metaheuristic algorithms is increasingly used to tackle all kinds
of optimization problems across disciplines. It also plays an important component in artificial …

When optimizing an experimental design for good prediction performance based on an
assumed second order response surface model, it is common to focus on a single optimality …

G-optimal designs are those which minimize the worst-case prediction variance. Thus, such
designs are of interest if prediction is a primary component of the post-experiment analysis …

Over recent decades, optimal experimental design has surged in popularity due to
affordable computing and efficient algorithms. However, some researchers highlight that this …

In this study we address existing deficiencies in the literature on applications of Particle
Swarm Optimization (PSO) to generate optimal designs. We present the results of a large …

Due to the special fields of aerospace, explosion impact, weapon penetration, and other
high-g value acceleration test, the sensor test range and antioverload capability have great …

In order to establish the projection properties of computer uniform designs of experiments on
Sobol's sequences, an empirical comparative statistical analysis of the homogeneity of 2D …

In modern pharmaceutical studies, treatments may include several drugs added
sequentially, and the drugs' order-of-addition can have significant impacts on their efficacy …

Constraints widely exist in the structural optimization problems, including not only expensive
constraints but also inexpensive constraints with explicit or implicit analytical expressions …

Space-filling experimental design techniques are commonly used in many computer
modeling and simulation studies to explore the effects of inputs on outputs. This research …