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Experimental Design for Sensitivity Analysis, Optimization and Validation of Simulation Models

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Author Info

  • Kleijnen, J.P.C.

    (Tilburg University, Center for Economic Research)

Abstract

This chapter gives a survey on the use of statistical designs for what-if analysis in simula- tion, including sensitivity analysis, optimization, and validation/verification. Sensitivity analysis is divided into two phases. The first phase is a pilot stage, which consists of screening or searching for the important factors among (say) hundreds of potentially important factors. A novel screening technique is presented, namely sequential bifurcation. The second phase uses regression analysis to approximate the input/output transformation that is implied by the simulation model; the resulting regression model is also known as a metamodel or a response surface. Regression analysis gives better results when the simu- lation experiment is well designed, using either classical statistical designs (such as frac- tional factorials) or optimal designs (such as pioneered by Fedorov, Kiefer, and Wolfo- witz). To optimize the simulated system, the analysts may apply Response Surface Metho- dology (RSM); RSM combines regression analysis, statistical designs, and steepest-ascent hill-climbing. To validate a simulation model, again regression analysis and statistical designs may be applied. Several numerical examples and case-studies illustrate how statisti- cal techniques can reduce the ad hoc character of simulation; that is, these statistical techniques can make simulation studies give more general results, in less time. Appendix 1 summarizes confidence intervals for expected values, proportions, and quantiles, in termi- nating and steady-state simulations. Appendix 2 gives details on four variance reduction techniques, namely common pseudorandom numbers, antithetic numbers, control variates or regression sampling, and importance sampling. Appendix 3 describes jackknifing, which may give robust confidence intervals.

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Bibliographic Info

Paper provided by Tilburg University, Center for Economic Research in its series Discussion Paper with number 1997-52.

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Date of creation: 1997
Date of revision:
Handle: RePEc:dgr:kubcen:199752

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Web page: http://center.uvt.nl

Related research

Keywords: least squares; distribution-free; non-parametric; stopping rule; run-length; Von Neumann; median; seed; likelihood ratio;

References

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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.:
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  1. 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.
  2. 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.
  3. Sherif, Yosef S. & Boice, Bruce A., 1994. "Optimization by pattern search," European Journal of Operational Research, Elsevier, vol. 78(3), pages 277-303, November.
  4. Kleijnen, J.P.C., 1975. "A comment on Blanning's metamodel for sensitivity analysis: The regression metamodel in simulation," Open Access publications from Tilburg University urn:nbn:nl:ui:12-369888, Tilburg University.
  5. Kleijnen, J.P.C., 1995. "Case study: Statistical validation of simulation models," Open Access publications from Tilburg University urn:nbn:nl:ui:12-369796, Tilburg University.
  6. Jack P. C. Kleijnen & Bert Bettonvil & Willem Van Groenendaal, 1998. "Validation of Trace-Driven Simulation Models: A Novel Regression Test," Management Science, INFORMS, vol. 44(6), pages 812-819, June.
  7. Kleijnen, J.P.C. & Groenendaal, W.J.H. van, 1995. "Two-stage versus sequential sample-size determination in regression analysis of simulation experiments," Open Access publications from Tilburg University urn:nbn:nl:ui:12-80492, Tilburg University.
  8. Dagenais, M.G. & Dufour, J.M., 1993. "Pitfalls of Rescalling Regression Models with Box-Cox Transformations," Cahiers de recherche 9333a, Centre interuniversitaire de recherche en économie quantitative, CIREQ.
  9. Kleijnen, J.P.C. & Karremans, P.C.A. & Oortwijn , W.K. & Groenendaal, W.J.H. van, 1987. "Jackknifing estimated weighted least squares: JEWLS," Open Access publications from Tilburg University urn:nbn:nl:ui:12-365635, Tilburg University.
  10. Kleijnen, J.P.C., 1995. "Verification and validation of simulation models," Open Access publications from Tilburg University urn:nbn:nl:ui:12-369797, Tilburg University.
  11. Standridge, C. & Kleijnen, J.P.C., 1988. "Experimental design and regression analysis: An FMS case study," Open Access publications from Tilburg University urn:nbn:nl:ui:12-369815, Tilburg University.
  12. Kleijnen, J.P.C. & Kloppenburg, G. & Meeuwsen, F., 1985. "Testing the mean of an asymmetric population: Johnson's modified t test revisited," Research Memorandum 183, Tilburg University, Faculty of Economics and Business Administration.
  13. Jack P. C. Kleijnen, 1992. "Regression Metamodels for Simulation with Common Random Numbers: Comparison of Validation Tests and Confidence Intervals," Management Science, INFORMS, vol. 38(8), pages 1164-1185, August.
  14. Kleijnen, J.P.C. & Groenendaal, W.J.H. van, 1992. "Simulation: A statistical perspective," Open Access publications from Tilburg University urn:nbn:nl:ui:12-388278, Tilburg University.
  15. Kleijnen, Jack P. C., 1995. "Statistical validation of simulation models," European Journal of Operational Research, Elsevier, vol. 87(1), pages 21-34, November.
  16. Kleijnen, J.P.C., 2009. "Sensitivity Analysis of Simulation Models," Discussion Paper 2009-11, Tilburg University, Center for Economic Research.
  17. Kleijnen, J.P.C., 1993. "Simulation and optimization in production planning: a case study," Open Access publications from Tilburg University urn:nbn:nl:ui:12-369798, Tilburg University.
  18. Kleijnen , J.P.C., 1995. "Sensitivity analysis and optimization of system dynamics models: Regression analysis and statistical design of experiments," Open Access publications from Tilburg University urn:nbn:nl:ui:12-365599, Tilburg University.
  19. Saltelli, A. & Andres, T. H. & Homma, T., 1995. "Sensitivity analysis of model output. Performance of the iterated fractional factorial design method," Computational Statistics & Data Analysis, Elsevier, vol. 20(4), pages 387-407, October.
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Citations

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Cited by:
  1. Grazia Vicario & Daniele Romano, 2001. "Factorial experiments for sequential process," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1-2), pages 191-204.
  2. Kleijnen, J.P.C., 2004. "An Overview of the Design and Analysis of Simulation Experiments for Sensitivity Analysis," Discussion Paper 2004-16, Tilburg University, Center for Economic Research.
  3. Matteo Richiardi, 2004. "The Promises and Perils of Agent-Based Computational Economics," Computational Economics 0401001, EconWPA.
  4. Kleijnen, J.P.C., 2001. "Experimental Design for Sensitivity Analysis of Simulation Models," Discussion Paper 2001-15, Tilburg University, Center for Economic Research.
  5. Giorgio Fagiolo & Paul Windrum & Alessio Moneta, 2006. "Empirical Validation of Agent Based Models: A Critical Survey," LEM Papers Series 2006/14, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
  6. Gaury, E.G.A. & Kleijnen, J.P.C. & Pierreval, H., 1997. "Configuring a pull production control strategy through a generic model," Discussion Paper 1997-101, Tilburg University, Center for Economic Research.
  7. Gaury, E.G.A. & Kleijnen, J.P.C. & Pierreval, H., 1998. "Customized Pull Systems for Single-Product Flow Lines," Discussion Paper 1998-117, Tilburg University, Center for Economic Research.
  8. Kurt DeMaagd & Scott Moore, 2007. "Computational modeling of city formation," Computational Economics, Society for Computational Economics, vol. 30(1), pages 41-56, August.
  9. Beers, W.C.M. van & Kleijnen, J.P.C., 2001. "Kriging for Interpolation in Random Simulation," Discussion Paper 2001-74, Tilburg University, Center for Economic Research.
  10. Pasquale Cirillo & Carlo Bianchi & Mauro Gallegati & Pietro Vagliasindi, 2006. "Validating and Calibrating Agent-based Models: a Case Study," Computing in Economics and Finance 2006 277, Society for Computational Economics.
  11. Kleijnen, J.P.C., 2006. "Generalized Response Surface Methodology: A New Metaheuristic," Discussion Paper 2006-77, Tilburg University, Center for Economic Research.

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