2008
DOI: 10.2528/pier07101702
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Modified Multi-Objective Particle Swarm Optimization for Electromagnetic Absorber Design

Abstract: Abstract-Use of Multi-Objective Particle Swarm Optimization for designing of planar multilayered electromagnetic absorbers and finding optimal Pareto front is described. The achieved Pareto presents optimal possible trade-offs between thickness and reflection coefficient of absorbers. Particle swarm optimization method in comparison with most of optimization algorithms such as genetic algorithms is simple and fast. But the basic form of Multi-objective Particle Swarm Optimization may not obtain the best Pareto… Show more

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Cited by 54 publications
(26 citation statements)
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“…Table 7. Model parameters obtained after minimization of RCS of a conducting cylinder (a = 50 mm) with one layer coating made of dispersive metamaterial in the frequency band [1][2][3][4][5][6][7][8][9][10] GHz for TE polarization. Table 8 and drawn in Fig.…”
Section: Numerical Examplesmentioning
confidence: 99%
See 1 more Smart Citation
“…Table 7. Model parameters obtained after minimization of RCS of a conducting cylinder (a = 50 mm) with one layer coating made of dispersive metamaterial in the frequency band [1][2][3][4][5][6][7][8][9][10] GHz for TE polarization. Table 8 and drawn in Fig.…”
Section: Numerical Examplesmentioning
confidence: 99%
“…Minimization or even maximization of radar cross section (RCS) [1][2][3] of objects is of particular interest, which can be achieved by different techniques such as application of Radar Absorbing Materials (RAM) [4,6]. Other applications of RAM have been developed, such as anechoic chambers, antenna designs with low side lobes, protection from electromagnetic interference in high speed circuits, etc.…”
Section: Introductionmentioning
confidence: 99%
“…New modified PSO-based schemes are continuously emerging in the literature in an attempt to improve the overall performance of classical schemes in one direction: to speed up convergence preserving diversity and increasing exploration abilities. Different modified versions of the classical PSO algorithm can be found applied to array synthesis [10,11], patch antenna design [12] or planar multilayered absorbers design [13]. In fact, there are some schemes that mix up heuristic GA and PSO optimization algorithms [14,15].…”
Section: Introductionmentioning
confidence: 99%
“…One of the powerful algorithms that can be employed for optimization of the multidimensional problems of this kind, especially in the domain of computational electromagnetism, is the particle swarm optimization (PSO) method [37][38][39][40][41][42][43][44][45][46][47]. Recently, some different PC structures have been optimized by using the PSO algorithm to evaluate a fitness function [48,49].…”
Section: Introductionmentioning
confidence: 99%