Adaptive efficient global optimization of systems with independent components

Samee Rehman, Matthijs Langelaar*

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

1 Citation (Scopus)
61 Downloads (Pure)


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.

Original languageEnglish
Pages (from-to)1143-1157
JournalStructural and Multidisciplinary Optimization
Issue number4
Publication statusPublished - 2017


  • Efficient global optimization
  • Expected improvement
  • Gaussian processes
  • Infill sampling
  • Kriging
  • System optimization


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