Using adaptive multi-accurate function evaluations in a surrogate-assisted method for computer experiments

Weichung Wang, Ray Bing Chen, Chia Lung Hsu

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

In many computer experiments, surrogates are used to assist in searching for certain target points. If the surrogates are defined by response function values evaluated by costly iterative processes, the computational burdens may impede the efficiency of regular surrogate-assisted methods. Instead of computing the fully convergent response function values, we propose to control the function evaluation iterations dynamically to save time on function evaluations without degrading the overall performance. Our new algorithms adaptively determine whether each of the function evaluation iterations should be paused, kept running, or restarted; we then use the approximate function values with various levels of accuracy to construct the surrogates. The numerical results show that the proposed algorithms achieve significant savings when solving super-level set searching problems that involve identifying positive Lyapunov exponents of a dynamical system.

Original languageEnglish
Pages (from-to)3151-3162
Number of pages12
JournalJournal of Computational and Applied Mathematics
Volume235
Issue number10
DOIs
Publication statusPublished - 2011 Mar 15

All Science Journal Classification (ASJC) codes

  • Computational Mathematics
  • Applied Mathematics

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