Design and Analysis of simulation experiments: Tutorial

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Abstract

This tutorial reviews the design and analysis of simulation experiments. These experiments may have various goals: validation, prediction, sensitivity analysis, optimization (possibly robust), and risk or uncertainty analysis. These goals may be realized through metamodels. Two types of metamodels are the focus of this tutorial: (i) low-order polynomial regression, and (ii) Kriging or Gaussian processes). The type of metamodel guides the design of the experiment; this design .…xes the input combinations of the simulation model. However, before a regression or Kriging metamodel is applied, the many inputs of the underlying realistic simulation model should be screened; the tutorial focuses on sequential bifurcation. Optimization of the simulated system may use either a sequence
of low-order polynomials— known as response surface methodology— or Kriging models .…tted through sequential designs. Finally, "robust" optimization should account for uncertainty in simulation inputs. The tutorial includes references to earlier WSC papers.
Original languageEnglish
Place of PublicationTilburg
PublisherCentER, Center for Economic Research
Number of pages25
Volume2017-018
Publication statusPublished - 27 Mar 2017

Publication series

NameCentER Discussion Paper
Volume2017-018

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Keywords

  • regression
  • Kriging
  • Gaussian process
  • factor screening
  • optimization
  • risk analysis

Cite this

Kleijnen, J. P. C. (2017). Design and Analysis of simulation experiments: Tutorial. (CentER Discussion Paper; Vol. 2017-018). Tilburg: CentER, Center for Economic Research.