A Hybrid Genetic-Algorithm Space-Mapping Method for the Optimization of Broadband Aperture-Coupled Asymmetrical U-Shaped Slot Antennas

Zhang, Y.-J.; Gong, Shuxi; Wang, X.; Wang, W.-T.

doi:10.1163/156939310793699118

Cited by 8 publications

(6 citation statements)

References 20 publications

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“…In [16,17] such metaheuristic methods have been employed to study electromagnetic radiation problems. A main advantage of metaheuristic search techniques is the fact that they do not depend on a correct assumption of a starting point.…”

Section: Introductionmentioning

confidence: 99%

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A Method of Predicting Composite Magnetic Sources Employing Particle Swarm Optimization

Spantideas¹,

Kapsalis²,

Kakarakis³

et al. 2014

PIER M

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Abstract-In this paper, the problem of predicting the parameters (positions and magnetic moments) of an Equipment Under Test (EUT) composed of a magnetic dipole and quadrupole is studied. Firstly, a multiple magnetic dipole and quadrupole model (MDQM) is developed to simulate the magnetic behavior of the EUT. The parameters of the model are calculated using the values of the near field measurements applying the Particle Swarm Optimization (PSO) algorithm. For the evaluation of the method, extended simulations were conducted, producing theoretical values and distorting them with noise, and then the developed algorithm was used to create the proper MDQM. As an evaluation criterion, the relative difference between the theoretical and the MDQM's magnetic field is considered.

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Section: Introductionmentioning

confidence: 99%

“…One of the most recently developed stochastic methods, imitating natural phenomena, i.e., the movement of bees inside a field, is Particle Swarm Optimization (PSO) [18]. PSO has been used in a variety of problems, such as antenna design ( [16,17]) and resource allocation [19].…”

Section: Introductionmentioning

confidence: 99%

A Method of Predicting Composite Magnetic Sources Employing Particle Swarm Optimization

Spantideas¹,

Kapsalis²,

Kakarakis³

et al. 2014

PIER M

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show abstract

“…The GA has been widely used for solving complex electromagnetic (EM) problems [14][15][16][17]. Varied antennas, such as monopole antennas [18,19], Yagi antennas [20,21], patch antennas [22][23][24][25] and array antennas [26][27][28][29] are designed for certain kinds of radiating target by GA optimization.…”

Section: Introductionmentioning

confidence: 99%

Design and Optimization of Low RCS Patch Antennas Based on a Genetic Algorithm

Zhu¹,

Shao²,

Li³

et al. 2012

PIER

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Abstract-In this article, a genetic algorithm (GA) is employed to the design of low radar cross section (RCS) patch antennas. Combined with the high frequency simulation software (HFSS) for antenna simulations, the GA performs the optimization of geometric parameters.In order to reduce the RCS while holding the satisfying radiation performance of antennas, the radiation model and scattering model are respectively calculated. The combination of proportionate selection and elitist model for the selection strategy is used to speed up the convergence of the GA. Two-point crossover is adopted to accelerate the converging speed and results in more fit individuals. Moreover, the whole design procedure is auto-controlled by programming the VBScript in the HFSS. Two examples of low RCS slot antennas are provided to verify the accuracy and efficiency of the proposed method.

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“…In [10,11] metaheuristic methods have been employed to study electromagnetic radiation problems. Stochastic search techniques start to be widely used with their main advantage that they do not need assumption on objective function's properties and do not need identification of a starting point.…”

Section: Introductionmentioning

confidence: 99%

Prediction of Multiple Magnetic Dipole Model Parameters From Near Field Measurements Employing Stochastic Algorithms

Kapsalis¹,

Kakarakis²,

Capsalis³

2012

PIER Letters

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Abstract-In this paper, the problem of predicting far field magnitude from near field measurements of an equipment under test (EUT) is studied. Firstly, a multiple magnetic dipole model is developed to simulate the magnetic behavior of the EUT. The parameters of the model (dipoles positions and magnetic moments) are calculated using the values of the near field applying the Particle Swarm Optimization (PSO) algorithm. For the evaluation of the method, extended simulations were conducted, producing theoretical values and distorting them with noise, and then the developed algorithm was used to create the proper model. Finally, the theoretical results are compared to the field assessments the proper models produced.

show abstract

A Hybrid Genetic-Algorithm Space-Mapping Method for the Optimization of Broadband Aperture-Coupled Asymmetrical U-Shaped Slot Antennas

Cited by 8 publications

References 20 publications

A Method of Predicting Composite Magnetic Sources Employing Particle Swarm Optimization

A Method of Predicting Composite Magnetic Sources Employing Particle Swarm Optimization

Design and Optimization of Low RCS Patch Antennas Based on a Genetic Algorithm

Prediction of Multiple Magnetic Dipole Model Parameters From Near Field Measurements Employing Stochastic Algorithms

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