On the Design of Optimization Strategies Based on Global Response Surface Approximation Models

Striking the correct balance between global exploration of search spaces and local exploitation of promising basins of attraction is one of the principal concerns in the design of global optimization algorithms. This is true in the case of techniques based on global response surface approximation mo...

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Bibliographic Details
Published in:Journal of global optimization 2005-09, Vol.33 (1), p.31-59
Main Authors: Sóbester, András, Leary, Stephen J., Keane, Andy J.
Format: Article
Language:English
Subjects:
Approximation
Design of experiments
Design optimization
Engineering schools
Exploitation
Heuristic
Operations research
Optimization algorithms
Optimization techniques
Physics
Studies
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Summary:Striking the correct balance between global exploration of search spaces and local exploitation of promising basins of attraction is one of the principal concerns in the design of global optimization algorithms. This is true in the case of techniques based on global response surface approximation models as well. After constructing such a model using some initial database of designs it is far from obvious how to select further points to examine so that the appropriate mix of exploration and exploitation is achieved. In this paper we propose a selection criterion based on the expected improvement measure, which allows relatively precise control of the scope of the search. We investigate its behavior through a set of artificial test functions and two structural optimization problems. We also look at another aspect of setting up search heuristics of this type: the choice of the size of the database that the initial approximation is built upon. [PUBLICATION ABSTRACT]
ISSN:0925-5001
1573-2916
DOI:10.1007/s10898-004-6733-1