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Surrogates and Classification Approaches for Efficient Global Optimization (EGO) with Inequality Constraints

hal.structure.identifierInstitut de Recherche de l'Ecole Navale [IRENAV]
dc.contributor.authorSACHER, Matthieu
hal.structure.identifierAnalysis and Control of Unsteady Models for Engineering Sciences [ACUMES]
dc.contributor.authorDUVIGNEAU, Régis
hal.structure.identifierLaboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur [LIMSI]
dc.contributor.authorLE MAITRE, Olivier
hal.structure.identifierBio-Indicateurs Actuels et Fossiles [BIAF]
dc.contributor.authorDURAND, Matthieu
hal.structure.identifierAlgebRe, geOmetrie, Modelisation et AlgoriTHmes [AROMATH]
hal.structure.identifierMyCFD
dc.contributor.authorBERRINI, Elisa
hal.structure.identifierInstitut de Recherche de l'Ecole Navale [IRENAV]
dc.contributor.authorHAUVILLE, Frédéric
hal.structure.identifierInstitut de Recherche de l'Ecole Navale [IRENAV]
dc.contributor.authorASTOLFI, Jacques André
dc.date.accessioned2021-05-14T09:50:29Z
dc.date.available2021-05-14T09:50:29Z
dc.date.conference2017-05
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/77288
dc.description.abstractEnIn this work, we compare the use of Gaussian Process (GP) models for the constraints with a classification approach relying on a Least-Squares Support Vector Machine (LS-SVM). We propose several adaptations of the classification approach in order to improve the efficiency of the EGO procedure, in particular an extension of the binary LS-SVM classifier to come-up with a probabilistic estimation of the feasible domain. The efficiencies of the GP models and classification methods are compared in term of computational complexities, distinguishing the construction of the GPmodels or LS-SVM classifier from the resolution of the optimization problem. The effect of the number of design parameters on the numerical costs is also investigated.The approaches are tested on the optimization of a complex non-linear Fluid-Structure Interaction system modeling a two dimensional flexible hydrofoil. Multi-design variables, defining the unloaded geometry of the foil and the characteristics of its elastic trailing edge, are used in the minimization of the foil’s drag, under constraints set to ensure minimal lift force and prevent cavitation at selected boat-speeds.
dc.language.isoen
dc.title.enSurrogates and Classification Approaches for Efficient Global Optimization (EGO) with Inequality Constraints
dc.typeCommunication dans un congrès avec actes
dc.subject.halInformatique [cs]/Analyse numérique [cs.NA]
dc.subject.halMathématiques [math]/Equations aux dérivées partielles [math.AP]
dc.subject.halMathématiques [math]/Optimisation et contrôle [math.OC]
dc.subject.halSciences de l'ingénieur [physics]/Mécanique [physics.med-ph]/Mécanique des fluides [physics.class-ph]
bordeaux.hal.laboratoriesInstitut de Mécanique et d’Ingénierie de Bordeaux (I2M) - UMR 5295*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.institutionINRAE
bordeaux.institutionArts et Métiers
bordeaux.countryCA
bordeaux.title.proceedingSIAM Optimization
bordeaux.conference.cityVancouver
bordeaux.peerReviewedoui
hal.identifierhal-01589262
hal.version1
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-01589262v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.au=SACHER,%20Matthieu&DUVIGNEAU,%20R%C3%A9gis&LE%20MAITRE,%20Olivier&DURAND,%20Matthieu&BERRINI,%20Elisa&rft.genre=proceeding


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