Robust minimax design from costly simulations.

Abstract

Design of complex physical systems most often relies on numerical simulations that may be extremely costly. In this paper, design is formalized as the optimization of a performance index with respect to control variables. Uncertainty is modeled via a vector of environmental variables that can take any value in a known compact set and may have an adverse effect on performance. In this context, the determination of a robust design requires the continuous minimax optimization of black-box functions. An algorithm combining Kriging-based optimization with relaxation is presented, which makes it possible to find approximate solutions to such problems on a limited computational budget. The design of a vibration absorber is presented as an illustrative example