A review on design, modeling and applications of computer experiments

Victoria C.P. Chen, Kwok Leung Tsui, Russell R. Barton, Martin Meckesheimer

Research output: Contribution to journalReview articlepeer-review

235 Scopus citations

Abstract

In this paper, we provide a review of statistical methods that are useful in conducting computer experiments. Our focus is on the task of metamodeling, which is driven by the goal of optimizing a complex system via a deterministic simulation model. However, we also mention the case of a stochastic simulation, and examples of both cases are discussed. The organization of our review first presents several engineering applications, it then describes approaches for the two primary tasks of metamodeling: (i) selecting an experimental design; and (ii) fitting a statistical model. Seven statistical modeling methods are included. Both classical and newer experimental designs are discussed. Finally, our own computational study tests the various metamodeling options on two two-dimensional response surfaces and one ten-dimensional surface.

Original languageEnglish (US)
Pages (from-to)273-291
Number of pages19
JournalIIE Transactions (Institute of Industrial Engineers)
Volume38
Issue number4
DOIs
StatePublished - Apr 2006

All Science Journal Classification (ASJC) codes

  • Industrial and Manufacturing Engineering

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