In this study we tried to estimate unknown parameters in a System Dynamics Model by optimization technique instead of trial and error. As the number of unknown parameters increases, it is difficult to estimate them by trial and error because the number of combinations of them increases rapidly. It follows that model builder are often forced to identify them subjectively. That's a weak point of Systems Dynamics Models- lack of model validation. We had tried to optimize controllable parameters on the basis of some objective functions. (2) (3) We applied this parameter optimization techniques to parameter estimation. The unknown parameters were estimated by using observational data as econometricians usually do in especially simultaneous decision models. A simplified Inventory Control Model which included two unknown parameters is used in this study.

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Date created

• 1996

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• Document

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• Processing documentation available at: https://wiki.albany.edu/display/SCA/Processing+Ingested+Digital+Files

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• Creative Commons BY-NC-ND Attribution-NonCommercial-NoDerivs 4.0 International

  
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System Dynamic Society Records

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• This collection is part of the University Archives