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Surrogate-based methods for black-box optimization
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DOI：10.1111/itor.12292.png)
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Abstract
En 中文
In this paper, we survey methods that are currently used in black-box optimization, that is, the kind of problems whose objective functions are very expensive to evaluate and no analytical or derivative information is available. We concentrate on a particular family of methods, in which surrogate (or meta) models are iteratively constructed and used to search for global solutions.
Keywords:
simulation optimization
black-box functions
heuristics
optimal control
nonlinear programming
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2.9
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1.8K
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3.7K