@techreport{d3b15c4627c4493e8c539df60be8ff0b,
title = "Expected Improvement in Efficient Global Optimization Through Bootstrapped Kriging - Replaces CentER DP 2010-62",
abstract = "This article uses a sequentialized experimental design to select simulation input com- binations for global optimization, based on Kriging (also called Gaussian process or spatial correlation modeling); this Kriging is used to analyze the input/output data of the simulation model (computer code). This design and analysis adapt the clas- sic {"}expected improvement{"} (EI) in {"}efficient global optimization{"} (EGO) through the introduction of an unbiased estimator of the Kriging predictor variance; this estimator uses parametric bootstrapping. Classic EI and bootstrapped EI are com- pared through various test functions, including the six-hump camel-back and several Hartmann functions. These empirical results demonstrate that in some applications bootstrapped EI finds the global optimum faster than classic EI does; in general, however, the classic EI may be considered to be a robust global optimizer.",
keywords = "Simulation, Optimization, Kriging, Bootstrap",
author = "Kleijnen, {Jack P.C.} and {van Beers}, W.C.M. and {van Nieuwenhuyse}, I.",
note = "Subsequently published in the Journal of Global Optimization (2012)",
year = "2011",
language = "English",
volume = "2011-015",
series = "CentER Discussion Paper",
publisher = "Information Management",
type = "WorkingPaper",
institution = "Information Management",
}