Quantile-Based Optimization of Noisy Computer Experiments with Tunable Precision

Picheny, Victor; Ginsbourger, David; Richet, Yann; Caplin, Gregory (2013). Quantile-Based Optimization of Noisy Computer Experiments with Tunable Precision. Technometrics, 55(1), pp. 2-13. Taylor & Francis 10.1080/00401706.2012.707580

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This article addresses the issue of kriging-based optimization of stochastic simulators. Many of these simulators depend on factors that tune the level of precision of the response, the gain in accuracy being at a price of computational time. The contribution of this work is two-fold: first, we propose a quantile-based criterion for the sequential design of experiments, in the fashion of the classical expected improvement criterion, which allows an elegant treatment of heterogeneous response precisions. Second, we present a procedure for the allocation of the computational time given to each measurement, allowing a better distribution of the computational effort and increased efficiency. Finally, the optimization method is applied to an original application in nuclear criticality safety. This article has supplementary material available online. The proposed criterion is available in the R package DiceOptim.

Item Type:

Journal Article (Original Article)

Division/Institute:

08 Faculty of Science > Department of Mathematics and Statistics > Institute of Mathematical Statistics and Actuarial Science

UniBE Contributor:

Ginsbourger, David

Subjects:

500 Science > 510 Mathematics

ISSN:

0040-1706

Publisher:

Taylor & Francis

Language:

English

Submitter:

Lutz Dümbgen

Date Deposited:

12 Mar 2014 09:22

Last Modified:

12 Jan 2016 11:06

Publisher DOI:

10.1080/00401706.2012.707580

BORIS DOI:

10.7892/boris.41520

URI:

https://boris.unibe.ch/id/eprint/41520

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