Particle Swarm Optimization Algorithms with Applications to Wave Scattering Problems

Alkmini Michaloglou, N. Tsitsas
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引用次数: 3

Abstract

Particle Swarm Optimization (PSO) algorithms are widely used in a plethora of optimization problems. In this chapter, we focus on applications of PSO algorithms to optimization problems arising in the theory of wave scattering by inhomogeneous media. More precisely, we consider scattering problems concerning the excitation of a layered spherical medium by an external dipole. The goal is to optimize the physical and geometrical parameters of the medium’s internal composition for varying numbers of layers (spherical shells) so that the core of the medium is substantially cloaked. For the solution of the associated optimization problem, PSO algorithms have been specifically applied to effectively search for optimal solutions corresponding to realizable parameters values. We performed rounds of simulations for the the basic version of the original PSO algorithm, as well as a newer variant of the Accelerated PSO (known as “Chaos Enhanced APSO”/ “Chaotic APSO”). Feasible solutions were found leading to significantly reduced values of the employed objective function, which is the normalized total scattering cross section of the layered medium. Remarks regarding the differences and particularities among the different PSO algorithms as well as the fine-tuning of their parameters are also pointed out.
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粒子群优化算法及其在波散射问题中的应用
粒子群优化算法(PSO)广泛应用于各种优化问题中。本章重点讨论了粒子群算法在非均匀介质波散射理论中优化问题的应用。更确切地说,我们考虑了层状球形介质受外部偶极子激发的散射问题。目标是优化介质内部组成的物理和几何参数,以适应不同层数(球壳),从而使介质的核心基本上被掩盖。针对关联优化问题的求解,具体应用粒子群算法有效地搜索可实现参数值对应的最优解。我们对原始PSO算法的基本版本以及加速PSO的新版本(称为“混沌增强APSO”/“混沌APSO”)进行了几轮模拟。找到了可行的解,使得所采用的目标函数(层状介质的归一化总散射截面)的值显著减小。指出了不同粒子群算法之间的差异和特殊性,并对其参数进行了微调。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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