论文信息 - Comparison between genetic and gradient-based optimization algorithms for solving electromagnetics problems

Comparison between genetic and gradient-based optimization algorithms for solving electromagnetics problems

This paper compares the application of genetic algorithms and traditional gradient-based algorithms to various optimization problems in electromagnetics. Gradient algorithms work well for a small number of continuous parameters. Genetic algorithms are best for a large number of quantized parameters. Both antenna array and scattering optimization examples are shown. >

Randy L. Haupt | R. Haupt

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