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Optimal Engineering Design by Means of Stochastic Optimization Methods

  • Conference paper
Emerging Methods for Multidisciplinary Optimization

Part of the book series: International Centre for Mechanical Sciences ((CISM,volume 425))

Abstract

The optimization problems arising in engineering design contain many model parameters (material, loading, costs, tolerances, etc.) which are not given, fixed quantities, but must be considered as random variables with a given probability distribution. Evaluating the performance of the system by expected cost functions or taking into account the reliability of designs, the basic optimization problem under stochastic uncertainty is replaced by a certain deterministic substitute problem taking into account random parameter variations. The mathematical properties of the substitute problems are examined and (approximate) solution techniques are provided by applying stochastic optimization methods.

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Author information

Authors and Affiliations

  1. Aero—Space Engineering and Technology, Federal Armed Forces University Munich, Neubiberg/München, Germany

    K. Marti

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  1. K. Marti
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Editor information

Editors and Affiliations

  1. The University of Liverpool, UK

    Jan Blachut

  2. University of Siegen, Germany

    Hans A. Eschenauer

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© 2001 Springer-Verlag Wien

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Marti, K. (2001). Optimal Engineering Design by Means of Stochastic Optimization Methods. In: Blachut, J., Eschenauer, H.A. (eds) Emerging Methods for Multidisciplinary Optimization. International Centre for Mechanical Sciences, vol 425. Springer, Vienna. https://doi.org/10.1007/978-3-7091-2756-8_3

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  • DOI: https://doi.org/10.1007/978-3-7091-2756-8_3

  • Publisher Name: Springer, Vienna

  • Print ISBN: 978-3-211-83335-3

  • Online ISBN: 978-3-7091-2756-8

  • eBook Packages: Springer Book Archive

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