Noisy Expected Improvement and On-line Computation Time Allocation for the Optimization of Simulators with Tunable Fidelity
2nd International Conference on Engineering Optimization, EngOpt 2010
September 6-9, 2010, Lisbon, Portugal
This article addresses the issue of kriging-based optimization of stochastic simulators. Many of these simulators depends 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 a rigorous 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.