Optimization Design of Metamaterial Absorbers Based on an Improved Adaptive Genetic Algorithm
Keywords:Absorber, adaptive genetic algorithm, metamaterial, optimization
Most reported metamaterials are designed empirically by parameter sweep, which is time-consuming and ineffective. We propose an optimization method of designing metamaterial absorbers based on an improved adaptive genetic algorithm (IAGA), with the aim to get wideband absorption. Firstly, an IAGA optimization model is presented, of which the crossover probability is adaptively adjusted by introducing a nonlinear function, and the mutation probability is adaptively adjusted using complementary idea. Then, a wideband triple-layer metamaterial absorber in THz region is designed and optimized using IAGA, getting about 40.4% increasing of relative bandwidth compared with the results of reference . A further comparison between IAGA and standard genetic algorithm (SGA) indicates that the IAGA is an effective method in improving convergence speed and stability, and can be used to optimize structure parameters of metamaterial absorbers with desired characteristics.
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