optimization_of_noisy_computer_experiments_with_tunable_precision_technometrics_2011 [Promethee]

Optimization of Noisy Computer Experiments with Tunable Precision (Technometrics 2011)

by V. Picheny, D. Ginsbourger, Y. Richet, G. Caplin


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: firstly, we propose a quantile-based criterion for the sequential choice of experiments, in the fashion of the classical Expected Improvement criterion, which allows an elegant treatment of heterogeneous response precisions. Secondly, we present a procedure that allocates on-line 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.


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