Quantile-Based Optimization of Noisy Computer Experiments With Tunable Precision
- 11 July 2012
- journal article
- research article
- Published by Informa UK Limited in Technometrics
- Vol. 55 (1), 2-13
- https://doi.org/10.1080/00401706.2012.707580
Abstract
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.Keywords
Other Versions
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