Surrogate-based Constrained Multi-Objective Optimization

author: Alexander Forrester, School of Engineering Sciences, University of Southampton
published: July 20, 2009,   recorded: July 2009,   views: 8150


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Aerospace design is synonymous with the use of long running and computationally intensive simulations, which are employed in the search for optimal designs in the presence of multiple, competing objectives and constraints. The difficulty of this search is often exacerbated by numerical `noise' and inaccuracies in simulation data and the frailties of complex simulations, that is they often fail to return a result. Surrogate-based optimization methods can be employed to solve, mitigate, or circumvent problems associated with such searches. This presentation gives an overview of constrained multi-objective optimization using Gaussian process based surrogates, with an emphasis on dealing with real-world problems.

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Comment1 Lionel Juillen, May 25, 2019 at 11:09 a.m.:

I tried without success to display the video...
and also I got an error when I wanted to download the slides/ppt file.... The link looks broken.. :-(

Could you fix these issues ?
Best regards

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