Multi-point objective-oriented sequential sampling strategy for constrained robust design

Ping Zhu*, Siliang Zhang, Wei Chen

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

21 Scopus citations


Metamodelling techniques are widely used to approximate system responses of expensive simulation models. In association with the use of metamodels, objective-oriented sequential sampling methods have been demonstrated to be effective in balancing the need for searching an optimal solution versus reducing the metamodelling uncertainty. However, existing infilling criteria are developed for deterministic problems and restricted to one sampling point in one iteration. To exploit the use of multiple samples and identify the true robust solution in fewer iterations, a multi-point objective-oriented sequential sampling strategy is proposed for constrained robust design problems. In this article, earlier development of objective-oriented sequential sampling strategy for unconstrained robust design is first extended to constrained problems. Next, a double-loop multi-point sequential sampling strategy is developed. The proposed methods are validated using two mathematical examples followed by a highly nonlinear automotive crashworthiness design example. The results show that the proposed method can mitigate the effect of both metamodelling uncertainty and design uncertainty, and identify the robust design solution more efficiently than the single-point sequential sampling approach.

Original languageEnglish (US)
Pages (from-to)287-307
Number of pages21
JournalEngineering Optimization
Issue number3
StatePublished - Mar 4 2015


  • constrained robust design
  • crashworthiness design
  • multiple-point sampling
  • objective-oriented sequential sampling method

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Optimization
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering
  • Applied Mathematics


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