To read the full version of this content please select one of the options below:

Alternative Kriging-HDMR optimization method with expected improvement sampling strategy

Enying Li (Central South University of Forestry and Teleology, Changsha, China)
Fan Ye (State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha, China)
Hu Wang (State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha, China)

Engineering Computations

ISSN: 0264-4401

Article publication date: 7 August 2017

Abstract

Purpose

The purpose of study is to overcome the error estimation of standard deviation derived from Expected improvement (EI) criterion. Compared with other popular methods, a quantitative model assessment and analysis tool, termed high-dimensional model representation (HDMR), is suggested to be integrated with an EI-assisted sampling strategy.

Design/methodology/approach

To predict standard deviation directly, Kriging is imported. Furthermore, to compensate for the underestimation of error in the Kriging predictor, a Pareto frontier (PF)-EI (PFEI) criterion is also suggested. Compared with other surrogate-assisted optimization methods, the distinctive characteristic of HDMR is to disclose the correlations among component functions. If only low correlation terms are considered, the number of function evaluations for HDMR grows only polynomially with the number of input variables and correlative terms.

Findings

To validate the suggested method, various nonlinear and high-dimensional mathematical functions are tested. The results show the suggested method is potential for solving complicated real engineering problems.

Originality/value

In this study, the authors hope to integrate superiorities of PFEI and HDMR to improve optimization performance.

Keywords

Acknowledgements

This work has been supported by a project of the National Natural Science Foundation of China (grant number 11572120, grant number 11172097, grant number 11302266, grant number 61232014).

Citation

Li, E., Ye, F. and Wang, H. (2017), "Alternative Kriging-HDMR optimization method with expected improvement sampling strategy", Engineering Computations, Vol. 34 No. 6, pp. 1807-1828. https://doi.org/10.1108/EC-06-2016-0208

Publisher

:

Emerald Publishing Limited

Copyright © 2017, Emerald Publishing Limited