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» Stochastic kriging for simulation metamodeling
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WSC
2007
13 years 9 months ago
Kriging metamodeling in constrained simulation optimization: an explorative study
This paper describes two experiments exploring the potential of the Kriging methodology for constrained simulation optimization. Both experiments study an (s, S) inventory system ...
William E. Biles, Jack P. C. Kleijnen, Wim C. M. V...
WSC
2008
13 years 9 months ago
Stochastic kriging for simulation metamodeling
We extend the basic theory of kriging, as applied to the design and analysis of deterministic computer experiments, to the stochastic simulation setting. Our goal is to provide fl...
Bruce E. Ankenman, Barry L. Nelson, Jeremy Staum
QRE
2008
140views more  QRE 2008»
13 years 6 months ago
Discrete mixtures of kernels for Kriging-based optimization
: Kriging-based exploration strategies often rely on a single Ordinary Kriging model which parametric covariance kernel is selected a priori or on the basis of an initial data set....
David Ginsbourger, Céline Helbert, Laurent ...
CCE
2010
13 years 4 months ago
Multi-scale methods and complex processes: A survey and look ahead
AbstrAct A comprehensive overview of numerical methodologies currently available for analyzing and building understanding of complex processes is presented. Both equation-free and ...
Angelo Lucia
CORR
2010
Springer
182views Education» more  CORR 2010»
13 years 7 months ago
SPOT: An R Package For Automatic and Interactive Tuning of Optimization Algorithms by Sequential Parameter Optimization
The sequential parameter optimization (spot) package for R (R Development Core Team, 2008) is a toolbox for tuning and understanding simulation and optimization algorithms. Model-...
Thomas Bartz-Beielstein