hal-00578550, version 3
Quantile-based optimization of Noisy Computer Experiments with Tunable Precision
Résumé : 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 design 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 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.
- 1 :
- CERFACS
- 2 :
- University of Bern
- 3 :
- Ministère de l'écologie de l'Energie, du Développement durable et de l'Aménagement du territoire – Ministère de l'économie, de l'industrie et de l'emploi – Ministère de l'Enseignement Supérieur et de la Recherche Scientifique – Ministère de la Défense – Ministère de la santé
- Domaine : Mathématiques/Optimisation et contrôle
- Mots-clés : Kriging – Expected Improvement – Stochastic simulators
- Versions disponibles : v1 (25-03-2011) v2 (17-08-2011) v3 (19-03-2012)
- hal-00578550, version 3
- http://hal.archives-ouvertes.fr/hal-00578550
- oai:hal.archives-ouvertes.fr:hal-00578550
- Contributeur :
- Soumis le : Lundi 19 Mars 2012, 19:21:51
- Dernière modification le : Lundi 19 Mars 2012, 19:25:27




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