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System Dynamics Models, Optimization of

Encyclopedia of Complexity and Systems Science

Definition of the Subject

The term “optimization” when related to system dynamics (SD) models has a special significance. It relates to the mechanism used to improve the model vis-à-vis a criterion. This collapses into two fundamentally different intentions. Firstly one may wish to improve the model in terms of its performance. For instance, it may be desired to minimize overall costs of inventory while still offering a satisfactory level of service to the downstream customer. So the criterion here is cost, and this would be minimized after searching the parameter space related to service level. The direction of need may be reversed, and maximization may be desired as, for instance, if one had a model of a firm and wished to maximize profit subject to an acceptable level of payroll and advertising costs. Here the parameter space being explored would involve both payroll and advertising parameters. This type of optimization might be described generically as policy optimization.

Optimizat...

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Abbreviations

Econometrics:

A statistical approach to economic modeling in which all the parameters in the structural equations are estimated according to a “best fit” to historical data.

Maximum likelihood:

A statistical concept which underpins calibration optimization and which generates the most likely parameter values; it is equivalent to the parameter set which minimizes the chi-square value.

Objective function:

See Payoff below.

Optimization:

The process of improving a model’s results in terms of either an aspect of its performance or by calibrating it to fit reported time series data.

Payoff:

A formula which expresses the objective, say, maximization of profits, minimization of costs, or minimization of the differences between a model variable and historical data on that variable.

Zero-one parameter:

A parameter which is used as a multiplier in a policy equation and serves the effect of bringing in or removing a particular influence in determining the optimal policy.

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Authors and Affiliations

  1. Centre for OR & Applied Statistics, Salford Business School, Faculty of Business, Law & The Built Environment, University of Salford, M5 4WT, Salford, Greater Manchester, UK

    Brian Dangerfield

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  1. Brian Dangerfield
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Correspondence to Brian Dangerfield .

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  1. Ramtech Ltd., Larkspur, California, USA

    Robert A. Meyers

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Dangerfield, B. (2013). System Dynamics Models, Optimization of. In: Meyers, R. (eds) Encyclopedia of Complexity and Systems Science. Springer, New York, NY. https://doi.org/10.1007/978-3-642-27737-5_542-4

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  1. Latest

    System Dynamics Models, Optimization of
    Published:
    09 April 2019

    DOI: https://doi.org/10.1007/978-3-642-27737-5_542-5

  2. Original

    System Dynamics Models, Optimization of
    Published:
    25 April 2014

    DOI: https://doi.org/10.1007/978-3-642-27737-5_542-4

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