A generalized "max-min" sample for surrogate update

Sylvain Lacaze, Samy Missoum

Research output: Contribution to journalArticlepeer-review

29 Scopus citations


This brief note describes the generalization of the "max-min" sample that was originally used in the update of approximated feasible or failure domains. The generalization stems from the use of the random variables joint distribution in the sampling scheme. In addition, this note proposes a numerical improvement of the max-min optimization problem through the use of the Chebychev norm.

Original languageEnglish (US)
Pages (from-to)683-687
Number of pages5
JournalStructural and Multidisciplinary Optimization
Issue number4
StatePublished - Apr 2014


  • Adaptive sampling
  • Chebychev norm
  • Max-min sample
  • Reliability

ASJC Scopus subject areas

  • Software
  • Control and Systems Engineering
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design
  • Control and Optimization


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