Why Not Run the Efficient Global Optimization Algorithm with Multiple Surrogates?
Felipe A. C. Viana
Here it is a reference on how can we improve the EGO (efficient global
optimization) algorithm with multiple surrogates:
Viana FAC, Haftka RT, and Watson LT, "Why Not Run the Efficient Global
Optimization Algorithm with Multiple Surrogates?," 51th AIAA/ASME/ASCE/
AHS/ASC Structures, Structural Dynamics, and Materials Conference,
Orlando, USA, April 12 - 15, 2010. AIAA 2010-3090.
Surrogate-based optimization has become popular in the design of
complex engineering systems. Each optimization cycle consists of
analyzing a number of designs, fitting a surrogate, performing
optimization based on the surrogate, and finally performing exact
simulation at the design obtained by the optimization. Adaptive
sampling algorithms that add one point per cycle are readily available
in the literature. They use uncertainty estimators to guide the
selection of the next sampling point(s). The addition of one point at
a time may not be efficient when it is possible to run simulations in
parallel. So we propose an algorithm for adding several points per
optimization cycle based on the simultaneous use of multiple
surrogates. The need for uncertainty estimates usually limits adaptive
sampling algorithms to surrogates such as kriging and polynomial
response surface because of the lack of uncertainty estimates in the
implementation of other surrogates. We import uncertainty estimates
from surrogates having such estimates to use with other surrogates
such as support vector regression models. The approach was tested on
two analytic examples for nine basic surrogates including kriging,
radial basis neural networks, linear Shepard and support vector
regression. For these examples we compare our approach with
traditional sequential optimization based on kriging. We found that
our approach was able to deliver better results in a fraction of the
optimization cycles needed by the traditional kriging implementation.
You can find more about it online:
http://sites.google.com/site/fchegury/publications
All the best,
Felipe A. C. Viana