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Correlation matrices in kriging assisted optimisation of electromagnetic devices

机译：克里金法辅助电磁设备优化中的相关矩阵

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摘要

Kriging surrogate modelling facilitates efficient decision making regarding where to place the next point for evaluation during optimisation. This is particularly helpful in the design of electromagnetic devices where computationally expensive numerical field modelling needs to be used. The disadvantage, however, is that correlation matrices are required which, for problems with many design variables and multiple objectives, may grow in size leading to the need for page swapping and thus slowing down of what in principle should be a very fast process. In this study several methodologies to reduce the computational resources required in such problems are proposed. The efficiency of the proposed approach is demonstrated using an example of a large multi-parameter optimisation problem where kriging coupled with the average gradient value method is employed.
机译：克里格代理模型有助于优化过程中有关将下一个评估点放置在何处的有效决策。这在需要使用计算量大的数值场建模的电磁设备的设计中特别有用。但是，缺点是需要相关矩阵，对于具有许多设计变量和多个目标的问题，可能会增大尺寸，从而导致需要页面交换，因此减慢了原则上应该是非常快速的过程。在这项研究中，提出了几种减少此类问题所需的计算资源的方法。以大型多参数优化问题为例演示了所提出方法的效率，该问题采用了克里金法和平均梯度值方法。

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