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Modelling and Simulation pp 323–342Cite as

Optimization

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Part of the book series: Simulation Foundations, Methods and Applications ((SFMA))

Abstract

The goal of a simulation project is often formulated in terms of an optimization task, and this chapter explores this topic within the CTDS context. A key facet of this task is the identification of a criterion function that measures some aspect of the SUI’s behaviour that is related to the project goal(s). The criterion function is dependent on some set of parameters embedded within the SUI. The optimization task corresponds to finding a ‘best value’ for this set of parameters as indicated by an extreme value (either maximum or minimum) for the selected criterion function. This problem of extremizing the value of a criterion function by locating a best value for a set of parameters has been widely studied in the optimization literature. In the modelling and simulation context, the problem is distinctive inasmuch as the evaluation of the criterion function is linked to a simulation model. Several well-established numerical procedures that can be directly applied when the simulation model falls in the CTDS category are outlined in this chapter. Included here are both a gradient-independent method (the Nelder–Mead Simplex method) and a gradient-dependent method (the conjugate gradient method). Associated issues of gradient evaluation and the linear search problem are discussed.

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Notes

  1. 1.

    Figure 10.1 has been taken from Pinter [23] with the permission of the author.

  2. 2.

    Within the present context, this implies that while α is in Î, J(α) always increases as α moves to the right from α *, and likewise, J(α) always increases as α moves to the left from α *.

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Authors and Affiliations

  1. School of Electrical Engineering and Computer Science, University of Ottawa, Ottawa, ON, Canada

    Louis G. Birta & Gilbert Arbez

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  1. Louis G. Birta
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  2. Gilbert Arbez
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Birta, L.G., Arbez, G. (2013). Optimization. In: Modelling and Simulation. Simulation Foundations, Methods and Applications. Springer, London. https://doi.org/10.1007/978-1-4471-2783-3_10

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  • DOI: https://doi.org/10.1007/978-1-4471-2783-3_10

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