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Kriging metamodeling in simulation: A review

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  • Kleijnen, Jack P.C.

Abstract

This article reviews Kriging (also called spatial correlation modeling). It presents the basic Kriging assumptions and formulas--contrasting Kriging and classic linear regression metamodels. Furthermore, it extends Kriging to random simulation, and discusses bootstrapping to estimate the variance of the Kriging predictor. Besides classic one-shot statistical designs such as Latin Hypercube Sampling, it reviews sequentialized and customized designs for sensitivity analysis and optimization. It ends with topics for future research.

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File URL: http://www.sciencedirect.com/science/article/B6VCT-4PXDM37-1/2/3fe509cf3c77ae78470ea4b9f88d4ca0
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Bibliographic Info

Article provided by Elsevier in its journal European Journal of Operational Research.

Volume (Year): 192 (2009)
Issue (Month): 3 (February)
Pages: 707-716

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Handle: RePEc:eee:ejores:v:192:y:2009:i:3:p:707-716

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Web page: http://www.elsevier.com/locate/eor

Related research

Keywords: Kriging Metamodel Response surface Interpolation Optimization Design;

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References

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  1. Kleijnen, Jack P. C. & van Beers, Wim C. M., 2005. "Robustness of Kriging when interpolating in random simulation with heterogeneous variances: Some experiments," European Journal of Operational Research, Elsevier, vol. 165(3), pages 826-834, September.
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Citations

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Cited by:
  1. Didier Rullière & Alaeddine Faleh & Frédéric Planchet & Wassim Youssef, 2013. "Exploring or reducing noise? A global optimization algorithm in the presence of noise," Post-Print hal-00759677, HAL.
  2. repec:hal:wpaper:hal-00759677 is not listed on IDEAS
  3. Kleijnen, Jack P.C. & Beers, W.C.M. van & Nieuwenhuyse, I. van, 2010. "Constrained optimization in simulation: A novel approach," Open Access publications from Tilburg University urn:nbn:nl:ui:12-3583585, Tilburg University.
  4. Kleijnen, Jack P.C., 2013. "Simulation-Optimization via Kriging and Bootstrapping: A Survey (Revision of CentER DP 2011-064)," Discussion Paper 2013-064, Tilburg University, Center for Economic Research.
  5. Plischke, Elmar & Borgonovo, Emanuele & Smith, Curtis L., 2013. "Global sensitivity measures from given data," European Journal of Operational Research, Elsevier, vol. 226(3), pages 536-550.
  6. Kabirian, Alireza & Ólafsson, Sigurdur, 2011. "Continuous optimization via simulation using Golden Region search," European Journal of Operational Research, Elsevier, vol. 208(1), pages 19-27, January.
  7. Bettonvil, B.W.M. & Castillo, E. del & Kleijnen, J.P.C., 2007. "Statistical Testing of Optimality Conditions in Multiresponse Simulation-based Optimization (Revision of 2005-81)," Discussion Paper 2007-45, Tilburg University, Center for Economic Research.
  8. Strang, Kenneth David, 2012. "Importance of verifying queue model assumptions before planning with simulation software," European Journal of Operational Research, Elsevier, vol. 218(2), pages 493-504.
  9. Rommel Regis & Christine Shoemaker, 2013. "A quasi-multistart framework for global optimization of expensive functions using response surface models," Journal of Global Optimization, Springer, vol. 56(4), pages 1719-1753, August.
  10. Mehdad, E. & Kleijnen, Jack P.C., 2013. "Bootstrapping and Conditional Simulation in Kriging: Better Confidence Intervals and Optimization," Discussion Paper 2013-038, Tilburg University, Center for Economic Research.

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