Screening Experiments for Simulation: A Review
AbstractThis article reviews so-called screening in simulation; i.e., it examines the search for the really important factors in experiments with simulation models that have very many factors (or inputs). The article focuses on a most efficient and effec- tive screening method, namely Sequential Bifurcation. It ends with a discussion of possible topics for future research, and forty references for further study.
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Bibliographic InfoPaper provided by Tilburg University, Center for Economic Research in its series Discussion Paper with number 2007-21.
Date of creation: 2007
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Screening; Metamodel; Response Surface; Design;
Find related papers by JEL classification:
- C0 - Mathematical and Quantitative Methods - - General
- C1 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General
- C9 - Mathematical and Quantitative Methods - - Design of Experiments
This paper has been announced in the following NEP Reports:
- NEP-ALL-2007-04-09 (All new papers)
- NEP-CBE-2007-04-09 (Cognitive & Behavioural Economics)
- NEP-CMP-2007-04-09 (Computational Economics)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Kleijnen, J.P.C. & Bettonvil, B.W.M., 1997.
"Searching for important factors in simulation models with many factors: Sequential bifurcation,"
Open Access publications from Tilburg University
urn:nbn:nl:ui:12-73905, Tilburg University.
- 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.
- Persson, Fredrik & Olhager, Jan, 2002. "Performance simulation of supply chain designs," International Journal of Production Economics, Elsevier, vol. 77(3), pages 231-245, June.
- S. M. Lewis & A. M. Dean, 2001. "Detection of interactions in experiments on large numbers of factors," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(4), pages 633-672.
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