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A parallelization method of genetic algorithms for optimal design of microwave filter

机译:遗传算法的并行化方法用于微波滤波器的优化设计

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The evolutional computing including generic algorithms (GAs) is applied to automatic design optimization in many practical problems. Using the method, we can find an optimum or a quasi optimum solution automatically, and may reduce the computational complexity about several to ten percent compared with the full searching in the parameter space. In general, an evaluation of fitness takes much time to be calculated. So it is necessary to speed up calculations by a parallel processing technique. In this paper, we discuss to employ two kinds of genetic algorithm (GA), parameter-free GA and micro-GA, for an automatic design optimization of dichroic band pass filter operating in the millimeter to terahertz frequency band. And their parallelization methods are proposed and compared with each other on the degree of acceleration. Electromagnetic simulations of dichroic filter are carried out using the FDTD technique.
机译:在许多实际问题中,包括通用算法(GA)在内的进化计算已应用于自动设计优化。使用该方法,我们可以自动找到最优解或准最优解,并且与在参数空间中进行全面搜索相比,可以将计算复杂度降低约百分之几至百分之十。通常,适应性评估需要大量时间才能计算出来。因此,有必要通过并行处理技术来加快计算速度。在本文中,我们讨论了采用两种遗传算法(无参数遗传算法和微遗传算法)对在毫米至太赫兹频段工作的二向色带通滤波器进行自动设计优化。并提出了它们的并行化方法,并在加速程度上进行了比较。使用FDTD技术对二向色性滤波器进行电磁仿真。

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