This paper presents a comprehensive review of the design of experiments used in the
surrogate models. In particular, this study demonstrates the necessity of the design of …

The idea for this book came from the time the authors spent at the Statistics and Applied
Mathematical Sciences Institute (SAMSI) in Research Triangle Park in North Carolina …

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

Sampling techniques are used in many fields, including design of experiments, image
processing, and graphics. The techniques in each field are designed to meet the constraints …

Abstract Artificial Neural Networks (ANNs) are well known for their credible ability to capture
non-linear trends in scientific data. However, the heuristic nature of estimation of parameters …

Global optimization of complex and high-dimensional functions remains a central challenge
with broad applications in science and engineering. This study introduces a new …

While multi-robot cells are being used more often in industry, the problem of work-piece
position optimization is still solved using heuristics and the human experience and, in most …

Halton sequences have always been quite popular with practitioners, in part because of
their intuitive definition and ease of implementation. However, in their original form, these …

Through numerical experiments, we examine the condition numbers of the interpolation
matrix for many species of radial basis functions (RBFs), mostly on uniform grids. For most …

Generating the low-discrepancy point sets in high-dimensional space is an optimization
problem which involves two issues: how to define the objective function of optimization, and …