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Small response surface designs for metamodel estimation

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  • Batmaz, Inci
  • Tunali, Semra

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  • Batmaz, Inci & Tunali, Semra, 2003. "Small response surface designs for metamodel estimation," European Journal of Operational Research, Elsevier, vol. 145(2), pages 455-470, March.
    • Handle: RePEc:eee:ejores:v:145:y:2003:i:2:p:455-470
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    References listed on IDEAS

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    1. Kleijnen, Jack P. C., 1995. "Verification and validation of simulation models," European Journal of Operational Research, Elsevier, vol. 82(1), pages 145-162, April.
    2. R D Hurrion & S Birgil, 1999. "A comparison of factorial and random experimental design methods for the development of regression and neural network simulation metamodels," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 50(10), pages 1018-1033, October.
    3. Kleijnen, Jack P. C. & Sargent, Robert G., 2000. "A methodology for fitting and validating metamodels in simulation," European Journal of Operational Research, Elsevier, vol. 120(1), pages 14-29, January.
    4. Kleijnen, Jack P. C. & Standridge, Charles R., 1988. "Experimental design and regression analysis in simulation: An FMS case study," European Journal of Operational Research, Elsevier, vol. 33(3), pages 257-261, February.
    5. J. S. Hunter & T. H. Naylor, 1970. "Experimental Designs for Computer Simulation Experiments," Management Science, INFORMS, vol. 16(7), pages 422-434, March.
    6. Joan M. Donohue & Ernest C. Houck & Raymond H. Myers, 1995. "Simulation Designs for the Estimation of Quadratic Response Surface Gradients in the Presence of Model Misspecification," Management Science, INFORMS, vol. 41(2), pages 244-262, February.
    7. Joan M. Donohue & Ernest C. Houck & Raymond H. Myers, 1993. "Simulation Designs and Correlation Induction for Reducing Second-Order Bias in First-Order Response Surfaces," Operations Research, INFORMS, vol. 41(5), pages 880-902, October.
    8. Kleijnen, J.P.C. & Bettonvil, B.W.M., 1997. "Searching for important factors in simulation models with many factors : Sequential bifurcation," Other publications TiSEM be826993-22f9-4cb3-89df-3, Tilburg University, School of Economics and Management.
    9. Bettonvil, Bert & Kleijnen, Jack P. C., 1997. "Searching for important factors in simulation models with many factors: Sequential bifurcation," European Journal of Operational Research, Elsevier, vol. 96(1), pages 180-194, January.
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    Cited by:

    1. Crombecq, K. & Laermans, E. & Dhaene, T., 2011. "Efficient space-filling and non-collapsing sequential design strategies for simulation-based modeling," European Journal of Operational Research, Elsevier, vol. 214(3), pages 683-696, November.
    2. Vinícius Resende Domingues & Luan Carlos de Sena Monteiro Ozelim & André Pacheco de Assis & André Luís Brasil Cavalcante, 2022. "Combining Numerical Simulations, Artificial Intelligence and Intelligent Sampling Algorithms to Build Surrogate Models and Calculate the Probability of Failure of Urban Tunnels," Sustainability, MDPI, vol. 14(11), pages 1-29, May.
    3. Jack P. C. Kleijnen & Susan M. Sanchez & Thomas W. Lucas & Thomas M. Cioppa, 2005. "State-of-the-Art Review: A User’s Guide to the Brave New World of Designing Simulation Experiments," INFORMS Journal on Computing, INFORMS, vol. 17(3), pages 263-289, August.
    4. Bozağaç, Doruk & Batmaz, İnci & Oğuztüzün, Halit, 2016. "Dynamic simulation metamodeling using MARS: A case of radar simulation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 124(C), pages 69-86.

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