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Adaptive extensions of the Nelder and Mead Simplex Method for optimization of stochastic simulation models

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Author Info
Neddermeijer, H.G.
Oortmarssen, G.J. van
Piersma, N.
Dekker, R.
Habbe, J.D.F. (Erasmus Econometric Institute)

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Abstract

We consider the Nelder and Mead Simplex Method for the optimization of stochastic simulation models. Existing and new adaptive extensions of the Nelder and Mead simplex method designed to improve the accuracy and consistency of the observed best point are studied. We compare the performance of the extensions on a small microsimulation model, as well as on five test functions. We found that gradually decreasing the noise during an optimization run is the most preferred approach for stochastic objective functions. The amount of computation effort needed for successful optimization is very sensitive to the timing of noise reduction and to the rate of decrease of the noise. Restarting the algorithm during the optimization run, in the sense that the algorithm applies a fresh simplex at certain iterations during an optimization run, has adverse effects in our tests for the microsimulation model and for most test functions.

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File URL: http://hdl.handle.net/1765/1655
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Publisher Info
Paper provided by Erasmus University Rotterdam, Econometric Institute in its series Econometric Institute Report with number EI 2000-22/A Revision_Date: 2009-07-29.

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Date of creation: 25 May 2000
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Handle: RePEc:dgr:eureir:1765001655

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Related research
Keywords: simulation; programming; health care; Nelder and Mead Simplex Method;

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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. 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!]
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Cited by:
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  1. S.Y.G.L. Tan & G.J. Oortmarssen van & N. Piersma, 2000. "Estimting parameters of a microsimulation model for breast cancer screening using the score function method," Econometric Institute Report 208, Erasmus University Rotterdam, Econometric Institute. [Downloadable!]
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