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Recent advances in surrogate-based optimization
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DOI：10.1016/j.paerosci.2008.11.001.png)
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Abstract
En 中文
The evaluation of aerospace designs is synonymous with the use of long running and computationally intensive simulations. This fuels the desire to harness the efficiency of surrogate-based methods in aerospace design optimization. Recent advances in surrogate-based design methodology bring the promise of efficient global optimization closer to reality. We review the present state of the art of constructing surrogate models and their use in optimization strategies. We make extensive use of pictorial examples and, since no method is truly universal, give guidance as to each method's strengths and weaknesses. (C) 2008 Elsevier Ltd. All rights reserved.
Keywords:
RESPONSE-SURFACE
GLOBAL OPTIMIZATION
DESIGN
APPROXIMATION
REGULARIZATION
IMPROVEMENT
ALGORITHMS
VARIABLES
MODELS
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