Space-Mapping Optimization With Adaptive Surrogate Model
Space-Mapping Optimization With Adaptive Surrogate Model
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DOI：
10.1109/tmtt.2006.890524
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发表时间：
2007-03
影响因子：
4.3
通讯作者：
S. Koziel;J. Bandler
中科院分区：
文献类型：
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作者：
S. Koziel;J. Bandler
在空间映射优化算法中使用的映射的适当选择通常是问题相关的。空间映射代理模型的参数数目必须调整，使得模型足够灵活以反映精细模型的特征，但同时又不过度灵活。其外推能力应允许预测当前迭代点附近的精细模型响应。空间映射类型的错误选择可能导致空间映射优化算法的性能不佳。在本文中，我们考虑一个空间映射优化算法与自适应代理模型。这使我们能够根据模型的近似/外推能力调整给定迭代中使用的空间映射代理模型的类型。该技术不需要任何额外的精细模型评估
The proper choice of mapping used in space-mapping optimization algorithms is typically problem dependent. The number of parameters of the space-mapping surrogate model must be adjusted so that the model is flexible enough to reflect the features of the fine model, but at the same time is not over flexible. Its extrapolation capability should allow the prediction of the fine model response in the neighborhood of the current iteration point. A wrong choice of space-mapping type may lead to poor performance of the space-mapping optimization algorithm. In this paper, we consider a space-mapping optimization algorithm with an adaptive surrogate model. This allows us to adjust the type of space-mapping surrogate model used in a given iteration based on the approximation/extrapolation capability of the model. The technique does not require any additional fine model evaluations