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A multiobjective optimization based approach for RBDO
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Poirion, Fabrice | - |
dc.contributor.author | Mercier, Quentin | - |
dc.date.accessioned | 2019-05-14T03:00:18Z | - |
dc.date.available | 2019-05-14T03:00:18Z | - |
dc.date.issued | 2019-05-26 | - |
dc.identifier.citation | 13th International Conference on Applications of Statistics and Probability in Civil Engineering(ICASP13), Seoul, South Korea, May 26-30, 2019 | - |
dc.identifier.isbn | 979-11-967125-0-1 | - |
dc.identifier.other | ICASP13-027 | - |
dc.identifier.uri | https://hdl.handle.net/10371/153260 | - |
dc.description.abstract | In this paper we present a novel algorithm in order to solve multiobjective design optimization problems of a sandwich plate when the objective functions are not smooth and when uncertainty is introduced into the material properties. The algorithm is based on the existence of a common descent vector for each sample of the random objective functions and on an extension of the stochastic gradient algorithm. It will be shown that a chance constraint optimization problem such as a RBDO problem can be written as a multiobjective optimization problem. Chance constraint optimization problems yields optimal designs for a fixed given level of probability for the constraint. However in real life problem it is not realistic to introduce a given probability because it is not known. It is more efficient to solve the problem for a whole range of probability in order to obtain an overview of the probability level appearing in the constraint effect on the solution. We show in this paper how to transform a chance constraint optimization problem into a multiobjective optimization problem and we give an illustration on simple examples. | - |
dc.language.iso | en | - |
dc.title | A multiobjective optimization based approach for RBDO | - |
dc.type | Conference Paper | - |
dc.identifier.doi | 10.22725/ICASP13.027 | - |
dc.sortNo | 973 | - |
dc.citation.pages | 65-71 | - |
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