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Robust Optimal Policy Methods for Nonlinear Models

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Part of the book series: Operations Research Proceedings ((ORP,volume 1990))

Abstract

We discuss two types of robust policy. The first is due to uncertainty in the parameters or exogenous variables in the model. We present a method that is based on sensitivity analysis and reduces to a mean- variance optimization in the linear model case. The second type of uncertainty is that due to the multiplicity of models purporting to represent the same economic system. We present a min-max algorithm to solve this problem.

Zusammenfassung

Zwei Arten von robuster Strategie werden betrachtet. Die erste basiert auf der Unbestimmtheit der Parameter oder der exogenen Variablen im Model. Wir stellen eine Methode vor, die auf Sensitivitätsanalyse beruht und die sich in ein Durchschnitts-Varianz Optimierungsproblem im linearen Model zurückführen läßt. Die zweite Art von Unbestimmtheit ensteht in Folge der Vielfalt von Modellen, die alle ein und dasselbe ökonomische System beschreiben können. Zur Lösung dieses Falles wird ein Min-Max Algorithmus dargestellt.

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© 1992 Springer-Verlag Berlin · Heidelberg

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Berc, R. (1992). Robust Optimal Policy Methods for Nonlinear Models. In: Bühler, W., Feichtinger, G., Hartl, R.F., Radermacher, F.J., Stähly, P. (eds) Papers of the 19th Annual Meeting / Vorträge der 19. Jahrestagung. Operations Research Proceedings, vol 1990. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-77254-2_29

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  • DOI: https://doi.org/10.1007/978-3-642-77254-2_29

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-55081-5

  • Online ISBN: 978-3-642-77254-2

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