Risk measures in the context of robust and reliability based optimization

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Event details

Date 17.01.2017
Hour 15:1516:30
Speaker Dr. Domenico Quagliarella Head of
Multidisciplinary Analysis and Design
Fluid Mechanics Department
C.I.R.A. - Italian Aerospace Research Centre
Location
Category Conferences - Seminars
Many industrial optimization processes must take account of the stochastic nature of the system and processes to be designed or re-designed and have to consider the random variability of some of the parameters that describe them. Thus it is necessary to characterize the system that is being studied from various points of view related to the treatment of uncertainty. This talk is related to the use of various risk measures in the context of robust and reliability based optimization. We start from the definition of risk measure and its formal setting and then we show how different risk functional definitions can lead to different approaches to the problem of optimization under uncertainty. In particular, the application of value-at-risk (VaR) and conditional value-at-risk (CVaR) is here illustrated. These risk measures originated in the area of financial engineering, but they are very well and naturally suited to reliability-based design optimization problems and they represent a viable alternative to more traditional robust design approaches. We will then discuss the implementation of an efficient risk-measure based optimization algorithm based on the introduction of the Weighted Empirical Cumulative Distribution Function (WECDF) and on the use of methods for changing the probability measure. Finally we will discuss the problems related to the error in the estimation of the risk function and we will illustrate the “bootstrap” computational statistics technique to get an estimate of the standard error on VaR and CVaR. Finally, we will report some application examples of this approach to robust and reliability based optimization, with particular reference to the robust design optimization of a natural laminar flow wing for a supersonic business jet.
 
 

Practical information

  • Informed public
  • Free
  • This event is internal

Contact

  • Pénélope Leyland, Fabio Nobile, Michele Pisaroni

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