%0 Book Section
%A Dellino, Gabriella
%A Meloni, Carlo
%B WSC '12 Proceedings of the Winter Simulation Conference 
%D 2012
%F eprints:1444
%I ACM
%T Metamodel variability analysis combining bootstrapping and validation techniques
%U http://eprints.imtlucca.it/1444/
%X Research on metamodel-based optimization has received considerably increasing interest in recent years, and has found successful applications in solving computationally expensive problems. The joint use of computer simulation experiments and metamodels introduces a source of uncertainty that we refer to as metamodel variability. To analyze and quantify this variability, we apply bootstrapping to residuals derived as prediction errors computed from cross-validation. The proposed method can be used with different types of metamodels, especially when limited knowledge on parameters’ distribution is available or when a limited computational budget is allowed. Our preliminary experiments based on the robust version of  the EOQ model show encouraging results.
%Z Article No.: 334