SIMULATION OPTIMIZATION FOR COMPUTER MODELS WITH MULTIVARIATE OUTPUT

被引：0

作者：

Kontar, Raed ^{[1
]}

Zhou, Shiyu ^{[1
]}

Horst, John ^{[2
]}

机构：

[1] Univ Wisconsin Madison, Dept Ind & Syst Engn, Madison, WI 53706 USA

[2] NIST, Gaithersburg, MD 20899 USA

来源：

PROCEEDINGS OF THE ASME 12TH INTERNATIONAL MANUFACTURING SCIENCE AND ENGINEERING CONFERENCE - 2017, VOL 4 | 2017年

关键词：

Metamodeling; Simulation optimization; Separable covariance; non-Separable covariance; DESIGNS;

D O I：

暂无

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

This paper explores the potential of Gaussian process based Metamodels for simulation optimization with multivariate outputs. Specifically we focus on Multivariate Gaussian process models established through separable and non-separable covariance structures. We discuss the advantages and drawbacks of each approach and their potential applicability in manufacturing systems. The advantageous features of the Multivariate Gaussian process models are then demonstrated in a case study for the optimization of manufacturing performance metrics.

引用

页数：8

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