Sequential design for response surface model fit in computer experiments using derivative information

ABSTRACT

This article considers the problem of response surface model fit in computer experiment. We propose a new sequential adaptive design through the “maximum expected improvement” approach. The new method defines the improvement by the first order approximation from the known design points using derivative information and sequentially seeks point in area with large curvature and variance. A version with distance penalty is also considered. We demonstrate their superiority over some existing methods by simulation.

KEYWORDS:

• Computer experiments
• Gaussian process
• Global prediction
• Sequential design

MATHEMATICS SUBJECT CLASSIFICATION:

• 60G15
• 62K20
• 62L05

Acknowledgments

The research is supported by the National Natural Science Foundation of China (grant 11271134) and the innovation fund from East China Normal University.