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dc.contributor.authorZadeh, Parviz M.*
dc.contributor.authorToropov, V.V.*
dc.contributor.authorWood, Alastair S.*
dc.date.accessioned2014-04-28T11:28:15Z
dc.date.available2014-04-28T11:28:15Z
dc.date.issued2009
dc.identifier.citationZadeh, P. M., Toropov, V. V., Wood, A. S. (2009) Metamodel-based collaborative optimization framework. Structural and Multidisciplinary Optimization, 38 (2), 103-115.
dc.identifier.urihttp://hdl.handle.net/10454/6248
dc.description.abstractThis paper focuses on the metamodel-based collaborative optimization (CO). The objective is to improve the computational efficiency of CO in order to handle multidisciplinary design optimization problems utilising high fidelity models. To address these issues, two levels of metamodel building techniques are proposed: metamodels in the disciplinary optimization are based on multi-fidelity modelling (the interaction of low and high fidelity models) and for the system level optimization a combination of a global metamodel based on the moving least squares method and trust region strategy is introduced. The proposed method is demonstrated on a continuous fiber-reinforced composite beam test problem. Results show that methods introduced in this paper provide an effective way of improving computational efficiency of CO based on high fidelity simulation models.en
dc.subjectREF 2014; Multidisciplinary design optimization; Collaborative optimization; Metamodel; Moving least squares method; Multi-fidelity modelling
dc.titleMetamodel-based collaborative optimization framework
dc.typeArticle
dc.identifier.doihttps://doi.org/10.1007/s00158-008-0286-8


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