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Global Optimization for Black-box Simulation via Sequential Intrinsic Kriging

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  • Mehdad, E.

    (Tilburg University, Center For Economic Research)

  • Kleijnen, Jack P.C.

    (Tilburg University, Center For Economic Research)

Abstract

No abstract is available for this item.

Suggested Citation

  • Mehdad, E. & Kleijnen, Jack P.C., 2014. "Global Optimization for Black-box Simulation via Sequential Intrinsic Kriging," Discussion Paper 2014-063, Tilburg University, Center for Economic Research.
    • Handle: RePEc:tiu:tiucen:8fa8d96f-a086-4c4b-88ab-9c8b523beb64
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    References listed on IDEAS

    as
    1. Ehsan Mehdad & Jack P.C. Kleijnen, 2018. "Stochastic intrinsic Kriging for simulation metamodeling," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 34(3), pages 322-337, May.
    2. Ivo Couckuyt & Dirk Deschrijver & Tom Dhaene, 2014. "Fast calculation of multiobjective probability of improvement and expected improvement criteria for Pareto optimization," Journal of Global Optimization, Springer, vol. 60(3), pages 575-594, November.
    3. Bruce Ankenman & Barry L. Nelson & Jeremy Staum, 2010. "Stochastic Kriging for Simulation Metamodeling," Operations Research, INFORMS, vol. 58(2), pages 371-382, April.
    4. D. Huang & T. Allen & W. Notz & N. Zeng, 2006. "Global Optimization of Stochastic Black-Box Systems via Sequential Kriging Meta-Models," Journal of Global Optimization, Springer, vol. 34(3), pages 441-466, March.
    5. Juliane Müller & Christine Shoemaker, 2014. "Influence of ensemble surrogate models and sampling strategy on the solution quality of algorithms for computationally expensive black-box global optimization problems," Journal of Global Optimization, Springer, vol. 60(2), pages 123-144, October.
    6. Roustant, Olivier & Ginsbourger, David & Deville, Yves, 2012. "DiceKriging, DiceOptim: Two R Packages for the Analysis of Computer Experiments by Kriging-Based Metamodeling and Optimization," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 51(i01).
    7. J. D. Opsomer & D. Ruppert & M. P. Wand & U. Holst & O. Hössjer, 1999. "Kriging with Nonparametric Variance Function Estimation," Biometrics, The International Biometric Society, vol. 55(3), pages 704-710, September.
    8. Ning Quan & Jun Yin & Szu Ng & Loo Lee, 2013. "Simulation optimization via kriging: a sequential search using expected improvement with computing budget constraints," IISE Transactions, Taylor & Francis Journals, vol. 45(7), pages 763-780.
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    Keywords

    global optimization; Gaussian process; Kriging; intrinsic Kriging; metamodel; computer experiment; Simulation;
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