Metamodeling techniques are commonly used to replace expensive computer simulations in robust
design problems. Due to the discrepancy between the simulation model and metamodel, a robust solution in
the infeasible region can be found according to the prediction error in constraint responses. In deterministic
optimizations, balancing the predicted constraint and metamodeling uncertainty, expected violation (EV) criterion
can be used to explore the design space and add samples to adaptively improve the fitting accuracy of the
constraint boundary. However in robust design problems, the predicted error of a robust design constraint cannot
be represented by the metamodel prediction uncertainty directly. The conventional EV-based sequential sampling
method cannot be used in robust design problems. In this paper, by investigating the effect of metamodeling
uncertainty on the robust design responses, an extended robust expected violation (REV) function is proposed to
improve the prediction accuracy of the robust design constraints. To validate the benefits of the proposed method,
a crashworthiness-based lightweight design example, i.e. a highly nonlinear constrained robust design problem, is
given. Results show that the proposed method can mitigate the prediction error in robust constraints and ensure
the feasibility of the robust solution.
ZHANG Si-liang1 (章斯亮), ZHU Ping1* (朱 平), CHEN Wei1,2 (陈 卫)
. Robust Expected Violation Criterion for Constrained Robust Design Problems and Its Application in Automotive Lightweight Design[J]. Journal of Shanghai Jiaotong University(Science), 2013
, 18(3)
: 257
-263
.
DOI: 10.1007/s12204-013-1391-4
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