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Multi-Objective Optimization of Wire Antennas: Genetic Algorithms Versus Particle Swarm Optimization

机译:线天线的多目标优化:遗传算法与粒子群优化

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摘要

The paper is aimed to the multi-objective optimization of wire multi-band antennas. Antennas are numerically modeled using time-domain integral-equation method. That way, the designed antennas can be characterized in a wide band of frequencies within a single run of the analysis. Antennas are optimized to reach the prescribed matching, to exhibit the omni-directional constant gain and to have the satisfactory polarization purity. Results of the design are experimentally verified. The multi-objective cost function is minimized by the genetic algorithm and by the particle swarm optimization. Results of the optimization by both the multi-objective methods are in detail compared. The combination of the time domain analysis and global optimization methods for the broadband antenna design and the detailed comparison of the multi-objective particle swarm optimization with the multi-objective genetic algorithm are the original contributions of the paper.
机译:本文旨在对有线多频带天线进行多目标优化。使用时域积分方程法对天线进行数值建模。这样,可以在一次分析中在宽频带内表征设计的天线。天线经过优化以达到规定的匹配度,以表现出全向恒定增益并具有令人满意的极化纯度。设计结果经过实验验证。遗传算法和粒子群算法可将多目标成本函数最小化。详细比较了两种多目标方法的优化结果。本文将宽带天线设计的时域分析与全局优化方法相结合,并将多目标粒子群优化与多目标遗传算法进行详细的比较是本文的主要贡献。

著录项

  • 作者

    Lukes Z.; Raida Zbyněk;

  • 作者单位
  • 年度 2005
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  • 原文格式 PDF
  • 正文语种 en
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