Optimizing 1D Dielectric Electromagnetic Bandgap (D-EBG) Structures Using Multistage Genetic Algorithm (MS-GA) and Considering Parameter Variations
An optimization method utilizing a multistage genetic algorithm (MS-GA) and considering parameter variations has been proposed to obtain optimal design of one-dimensional dielectric bandgap(1D D-EBG) structures with a few periods in small packaging power distribution networks. One-dimensional finite method (1D FEM) is used to improve computational efficiency and iteration speed. MS-GA consists of 3 stages: In stage 1, the population was initialized by Hamming distance, and the fitness was calculated to determine the number of EBG period. In stage 2, genetic manipulation and sensitivity analysis were used to improve local search ability and obtain preliminary results. In stage 3, cubic spline interpolation and local integral were used to reconstruct the fitness evaluation function considering parameter deviation, adjust the results and obtain the optimal parameters. Three optimized target frequency bands with center frequencies of 2.4 GHz, 3.5 GHz and 28 GHz were optimized, and Pearson coefficient was used to analyze the correlation between the parameters to better understand the influence of parameter deviation on the optimization results. The achieved results meet the optimization object within the allowable range of parameter errors, and the parameter constraints were successfully met for all three designs, with their final dimensions below 20 mm. Three-dimensional full-wave simulation software was used to simulate and analyze the stopband bands, and the simulation results were consistent with the calculation results.