Print Email Facebook Twitter Adaptive efficient global optimization of systems with independent components Title Adaptive efficient global optimization of systems with independent components Author Rehman, S.U. (TU Delft Computational Design and Mechanics) Langelaar, Matthijs (TU Delft Computational Design and Mechanics) Date 2017 Abstract We present a novel approach for efficient optimization of systems consisting of expensive to simulate components and relatively inexpensive system-level simulations. We consider the types of problem in which the components of the system problem are independent in the sense that they do not exchange coupling variables, however, design variables can be shared across components. Component metamodels are constructed using Kriging. The metamodels are adaptively sampled based on a system level infill sampling criterion using Efficient Global Optimization. The effectiveness of the technique is demonstrated by applying it on numerical examples and an engineering case study. Results show steady and fast converge to the global deterministic optimum of the problems. Subject Efficient global optimizationExpected improvementGaussian processesInfill samplingKrigingSystem optimization To reference this document use: http://resolver.tudelft.nl/uuid:060d9f3e-561c-4806-87fb-dd378cfaf3b0 DOI https://doi.org/10.1007/s00158-017-1663-y ISSN 1615-147X Source Structural and Multidisciplinary Optimization, 55 (4), 1143-1157 Part of collection Institutional Repository Document type journal article Rights © 2017 S.U. Rehman, Matthijs Langelaar Files PDF art_10.1007_s00158_017_1663_y.pdf 989.8 KB Close viewer /islandora/object/uuid:060d9f3e-561c-4806-87fb-dd378cfaf3b0/datastream/OBJ/view