metamodel that preserves this known shape, this article uses bootstrapping (or resampling). Parametric bootstrapping assuming …-event simulation) using distribution-free bootstrapping. In stochastic simulation, the analysts should simulate each input combination … variation, so the Kriging metamodel does not need to interpolate the average outputs. Bootstrapping provides a simple method for …

are binding; it applies bootstrapping (resampling) to test the estimated gradients in the KKT conditions. The new …

acceptable confidence intervals and estimates of the optimal input combination. This conclusion is based on bootstrapping and …

Distribution-free bootstrapping of the replicated responses of a given discreteevent simulation model gives … analysis than classic Kriging; i.e., bootstrapping gives lower MSE and confidence intervals with higher coverage and the same …

estimator uses parametric bootstrapping. Classic EI and bootstrapped EI are compared through four popular test functions …