System Dynamics like other simulation methodologies is basically descriptive, in that it does not search for optimized set of policy variables. To render it an optimization capability one may augment it with a Genetic Algorithm (GA) input machine with a multi criteria objective function evaluator such as TOPSIS. Starting from a random population of policy variables, different simulation run will be performed one for every member of the population. Using GA operators and the evaluation motor a new population of policy variables will be constructed. The procedure is automatically repeated until the best combination of policy variables is formed. This paper presents this as an idea and gives an example of how this can be performed in practice.

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Date created

• 2008 July 20-2008 July 24

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• Document

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System Dynamic Society Records

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• This collection is part of the University Archives