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An overview of the design and analysis of simulation experiments for sensitivity analysis

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  • Kleijnen, Jack P. C.

Abstract

Sensitivity analysis may serve validation, optimization, and risk analysis of simulation models.This review surveys classic and modern designs for experiments with simulation models.Classic designs were developed for real, non-simulated systems in agriculture, engineering, etc.These designs assume a few factors (no more than ten factors) with only a few values per factor (no more than five values).These designs are mostly incomplete factorials (e.g., fractionals).The resulting input/output (I/O) data are analyzed through polynomial metamodels, which are a type of linear regression models.Modern designs were developed for simulated systems in engineering, management science, etc.These designs allow many factors (more than 100), each with either a few or many (more than 100) values.These designs include group screening, Latin Hypercube Sampling (LHS), and other space filling designs.Their I/O data are analyzed through second-order polynomials for group screening, and through Kriging models for LHS.
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Suggested Citation

  • Kleijnen, Jack P. C., 2005. "An overview of the design and analysis of simulation experiments for sensitivity analysis," European Journal of Operational Research, Elsevier, vol. 164(2), pages 287-300, July.
    • Handle: RePEc:eee:ejores:v:164:y:2005:i:2:p:287-300
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    1. Shu Yamada & Dennis Lin, 2002. "Construction of mixed-level supersaturated design," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 56(3), pages 205-214, December.
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    7. Russell C. H. Cheng & Jack P. C. Kleijnen, 1999. "Improved Design of Queueing Simulation Experiments with Highly Heteroscedastic Responses," Operations Research, INFORMS, vol. 47(5), pages 762-777, October.
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    9. J P C Kleijnen & M T Smits, 2003. "Performance metrics in supply chain management," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(5), pages 507-514, May.
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    11. Angun, M.E. & Gürkan, G. & den Hertog, D. & Kleijnen, J.P.C., 2002. "Response surface methodology revisited," Other publications TiSEM 32c35a04-3de9-4dee-a242-6, Tilburg University, School of Economics and Management.
    12. Russell C. H. Cheng & Jack P. C. Kleijnen, 1999. "Improved Design of Queueing Simulation Experiments with Highly Heteroscedastic Responses," Operations Research, INFORMS, vol. 47(5), pages 762-777, October.
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