Multi-fidelity optimization via surrogate modelling

  title={Multi-fidelity optimization via surrogate modelling},
  author={Alexander I. J. Forrester and Andras Sobester and Andy J. Keane},
This paper demonstrates the application of correlated Gaussian process based approximations to optimization where multiple levels of analysis are available, using an extension to the geostatistical method of co-kriging. An exchange algorithm is used to choose which points of the search space to sample within each level of analysis. The derivation of the co-kriging equations is presented in an intuitive manner, along with a new variance estimator to account for varying degrees of computational… CONTINUE READING
Highly Influential
This paper has highly influenced 13 other papers. REVIEW HIGHLY INFLUENTIAL CITATIONS


Publications citing this paper.
Showing 1-10 of 102 extracted citations


Publications referenced by this paper.
Showing 1-10 of 20 references

The BAE Ltd. transport aircraft synthesis and optimization program

  • J. Cousin, M. Metcalf
  • AHS, and ASEE, Aircraft Design, Systems and…
  • 1990
Highly Influential
9 Excerpts

Wing optimization using design of experiment, response surface, and data fusion methods

  • A. J. Keane
  • Journal of Aircraft,
  • 2003

A taxonomy of global optimization methods based on response surfaces

  • D. R. Jones
  • Journal of Global Optimization,
  • 2001
2 Excerpts

Predicting the output from complex computer code when fast approximations are available

  • M. C. Kennedy, A. O’Hagan
  • Biometrika
  • 2000

Predicting the output from copmlex computer code when fast approximations are available

  • M. C. Kennedy, A. O’Hagan
  • 2000
2 Excerpts

Similar Papers

Loading similar papers…