Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4959513 | European Journal of Operational Research | 2017 | 11 Pages |
Abstract
Stochastic kriging (SK) methodology has been known as an effective metamodeling tool for approximating a mean response surface implied by a stochastic simulation. In this paper we provide some theoretical results on the predictive performance of SK, in light of which novel integrated mean squared error-based sequential design strategies are proposed to apply SK for mean response surface metamodeling with a fixed simulation budget. Through numerical examples of different features, we show that SK with the proposed strategies applied holds great promise for achieving high predictive accuracy by striking a good balance between exploration and exploitation.
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Science (General)
Authors
Xi Chen, Qiang Zhou,