Sequential optimization of strip bending process using multiquadric radial basis function surrogate models

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Surrogate models are used within the sequential optimization strategy for forming processes. A sequential improvement (SI) scheme is used to refine the surrogate model in the optimal region. One of the popular surrogate modeling methods for SI is Kriging. However, the global response of Kriging models deteriorates in some cases due to local model refinement within SI. This may be problematic for multimodal optimization problems and for other applications where correct prediction of the global response is needed. In this paper the deteriorating global behavior of the Kriging surrogate modeling technique is shown for a model of a strip bending process. It is shown that a Radial Basis Function (RBF) surrogate model with Multiquadric (MQ) basis functions performs equally well in terms of optimization efficiency and better in terms of global predictive accuracy. The local point density is taken into account in the model formulation
Original languageEnglish
Title of host publicationThe current state-of-the-art on materials forming, numerical and experimental approaches at different length-scales: ESAFORM 2013
PublisherTrans Tech Publications Ltd
ISBN (Print)9783037857199
Publication statusPublished - 22 Apr 2013
Event16th International ESAFORM Conference on Material Forming, ESAFORM 2013 - Aveiro, Portugal
Duration: 22 Apr 201324 Apr 2013
Conference number: 16

Publication series

PublisherTrans Tech Publications


Conference16th International ESAFORM Conference on Material Forming, ESAFORM 2013
Abbreviated titleESAFORM 2013


  • METIS-310402
  • IR-85982

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