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Sensitivity Analysis and Optimization of System Dynamics Models : Regression Analysis and Statistical Design of Experiments

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Author Info
Kleijnen, J.P.C. (Tilburg University, Center for Economic Research)

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Abstract

This tutorial discusses what-if analysis and optimization of System Dynamics models. These problems are solved, using the statistical techniques of regression analysis and design of experiments (DOE). These issues are illustrated by applying the statistical techniques to a System Dynamics model for coal transportation, taken from Wolstenholme's book "System Enquiry: a System Dynamics Approach" (1990). The regression analysis uses the least squares algorithm. DOE uses classic designs, namely, fractional factorials and central composite designs. Compared with intuitive approaches, DOE is more efficient: DOE gives more accurate estimators of input effects. Moreover DOE is more effective: interactions are estimable too. The System Dynamics model is also optimized. A heuristic is derived, inspired by Response Surface Methodology (RSM) but accounting for constraints. Some remaining pertinent problems are briefly discussed, namely DOE for cases with many factors, and DOE for random System Dynamics models. Conclusions are presented for the case study, and general principles are derived. Finally 23 references are given for further study.

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Paper provided by Tilburg University, Center for Economic Research in its series Discussion Paper with number 4.

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Date of creation: 1995
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Handle: RePEc:dgr:kubcen:19954

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

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Related research
Keywords: System Dynamics Models;

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References listed on IDEAS
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.:
  1. Bettonvil, B. & Kleijnen, J.P.C., 1994. "Identifying the Important Factors in Simulation Models with Many Factors," Discussion Paper 114, Tilburg University, Center for Economic Research. [Downloadable!]
  2. 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. [Downloadable!] (restricted)
  3. Kleijnen, Jack P. C., 1995. "Verification and validation of simulation models," European Journal of Operational Research, Elsevier, vol. 82(1), pages 145-162, April. [Downloadable!] (restricted)
  4. Kleijnen, J.P.C., 2009. "Sensitivity Analysis of Simulation Models," Discussion Paper 2009-11, Tilburg University, Center for Economic Research. [Downloadable!]
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Cited by:
(explanations, 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.)

  1. Roberto Leombruni & Matteo Richiardi & Nicole J. Saam & Michele Sonnessa, 2005. "A Common Protocol for Agent-Based Social Simulation," LABORatorio R. Revelli Working Papers Series 47, LABORatorio R. Revelli, Centre for Employment Studies. [Downloadable!]
    Other versions:
  2. Kleijnen, J.P.C., 1997. "Experimental design for sensitivity analysis, optimization, and validation of simulation models," Discussion Paper 52, Tilburg University, Center for Economic Research. [Downloadable!]
  3. Kleijnen, Jack P.C., 2006. "White noise assumptions revisited : regression models and statistical designs for simulation practice," Discussion Paper 50, Tilburg University, Center for Economic Research. [Downloadable!]
  4. Kleijnen, J.P.C., 1995. "Sensitivity analysis and related analysis : a survey of statistical techniques," Research Memorandum 706, Tilburg University, Faculty of Economics and Business Administration. [Downloadable!]
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