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Electromagnetics optimization using an evolutionary algorithm with a mixed-parameter self-adaptive mutation operator

机译:使用带有混合参数自适应突变算子的进化算法进行电磁优化

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Applications of evolutionary programming (EP) in electromagnetics to date have been mainly in continuous parameter optimizations. EP, however, can directly work with continuous or discrete parameters. We present an implementation of EP with a mixed continuous-discrete parameter representation. In our approach the mutation operator consists of a hybrid combination of Gaussian mutation, for the continuous parameters, and Poisson mutation, for the discrete parameters. The implementation uses self-adaptive schemes for updating the standard deviation of the Gaussian distribution and the mean of the Poisson distribution during the evolution. As an example, the mixed-parameter EP algorithm is applied to the design of a multi-layer filter structure.
机译:迄今为止,进化编程(EP)在电磁学中的应用主要集中在连续参数优化中。但是,EP可以直接使用连续或离散的参数。我们提出了一个带有混合连续离散参数表示形式的EP的实现。在我们的方法中,突变算子由高斯突变(对于连续参数)和泊松突变(对于离散参数)的混合组合组成。该实现使用自适应方案在演化过程中更新高斯分布的标准偏差和泊松分布的均值。例如,将混合参数EP算法应用于多层滤波器结构的设计。

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