Genetical Swarm Optimization: Self-Adaptive Hybrid Evolutionary Algorithm for Electromagnetics

Grimaccia, Francesco; Mussetta, Marco; Zich, R.E.

doi:10.1109/tap.2007.891561

Cited by 108 publications

(45 citation statements)

References 13 publications

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“…PSO has been shown to be very effective in optimizing challenging multidimensional, nonlinear and multimodal problems in a variety of fields such as signal processing [20][21][22][23], communication networks [24], biomedical [25,26], control [27,28], robotics [29], power systems [30], electromagnetics [31], image and video analysis [32,33]. It was inspired by the social behavior of animals, specifically the ability of groups of animals to work collectively in finding the desirable positions in a given area.…”

Section: Particle Swarm Optimizationmentioning

confidence: 99%

Multipath channel identification by using global optimization in ambiguity function domain

Güldoǧan

Arıkan

2011

Signal Processing

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a b s t r a c tA new transform domain array signal processing technique is proposed for identification of multipath communication channels. The received array element outputs are transformed to delay-Doppler domain by using the cross-ambiguity function (CAF) for efficient exploitation of the delay-Doppler diversity of the multipath components. Clusters of multipath components can be identified by using a simple amplitude thresholding in the delay-Doppler domain. Particle swarm optimization (PSO) can be used to identify parameters of the multipath components in each cluster. The performance of the proposed PSO-CAF technique is compared with the space alternating generalized expectation maximization (SAGE) technique and with a recently proposed PSO based technique at various SNR levels. Simulation results clearly quantify the superior performance of the PSO-CAF technique over the alternative techniques at all practically significant SNR levels.

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Section: Particle Swarm Optimizationmentioning

confidence: 99%

Multipath channel identification by using global optimization in ambiguity function domain

Güldoǧan

Arıkan

2011

Signal Processing

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“…The design of complex electromagnetic (EM) structures for real life applications often requires exploiting the features of evolutionary computation techniques such as the classic Genetic Algorithms (GA) [1], Particle Swarm Optimization (PSO) [2], Ant Colony Optimization (ACO) [3] as well as more recent developed population based approaches such as MetaPSO [4], Memetic Algorithm [5], Invasive Weed Optimization (IWO) [6], Biogeography-Based Optimization [7] and other hybrid techniques [8][9][10]. All these population based techniques share the same basic idea, i.e., they attempt to reach the optimum solution acting at each step of the iterative process on the current population, i.e., on a considered set of candidate solutions, through general, problem-independent operators.…”

Section: Introductionmentioning

confidence: 99%

Modified Bayesian Optimization Algorithm for Sparse Linear Antenna Design

Ha¹,

Pirinoli²,

Zich³

et al. 2013

PIER B

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Abstract-In this paper, a modified Bayesian Optimization Algorithm (BOA), named M-BOA, is proposed to introduce a suitable mutation scheme for the traditional procedure in order to speed up the convergence of the algorithm and to avoid it to be trapped in local minima or to stagnate in suboptimal solutions. The proposed algorithm has been applied both to a specific mathematical test function and to sparse linear antenna arrays design, showing outperforming capabilities not only with respect to the standard BOA, but also with respect to other assessed global optimization methods.

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“…In order to solve these problems efficiently, Evolutionary Algorithms (EAs) [9][10][11] have been considered and successfully applied to such problems [12][13][14][15][16][17][18][19][20][21][22]. Differential Evolution (DE) [9,10,23,24] has emerged as one of the most powerful real parameter optimizers of current interest.…”

Section: Introductionmentioning

confidence: 99%

Design of Dual Pattern Concentric Ring Array Antenna Using Differential Evolution Algorithm With Novel Evolutionary Operators

Mandal¹,

Das²

2012

PIER M

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Abstract-Concentric ring antenna arrays with the ability to produce dual pattern have many applications in communications and radar engineering. In this paper, we represent a new method for design of an optimized reconfigurable concentric ring array with dual pattern of desired specifications. Here, our goal is to find a suitable common element excitation amplitude distribution and two different element excitation phase distributions for two desired radiation patterns. For this purpose, we have proposed a novel objective function which is completely different from the traditional objective functions usually used in antenna design problems. For the optimization procedure, we have developed a modified Differential Evolution (DE) algorithm, denoted as DE rBM 2SX, which employs new kinds of crossover and mutation operators to overcome some drawbacks of the classical DE on single-objective fitness landscapes. We consider three types of dual pattern -pencil beam+pencil beam, pencil beam+flat-top beam, flat-top beam+flat-top beam. The simulation results obtained by applying our proposed method clearly indicate that our method is very convenient to obtain radiation patterns of desired specifications. We compare results of the modified DE algorithm with those of another state-of-the-art improved variant of DE, called JADE and a state-ofthe-art variant of the Particle Swarm Optimization (PSO) algorithm called Comprehensive Learning Particle Swarm Optimizer (CLPSO). Such comparisons reflect that the proposed algorithm is more efficient than JADE or CLPSO in finding optimum configuration of the dual pattern concentric ring array antenna.

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Genetical Swarm Optimization: Self-Adaptive Hybrid Evolutionary Algorithm for Electromagnetics

Cited by 108 publications

References 13 publications

Multipath channel identification by using global optimization in ambiguity function domain

Multipath channel identification by using global optimization in ambiguity function domain

Modified Bayesian Optimization Algorithm for Sparse Linear Antenna Design

Design of Dual Pattern Concentric Ring Array Antenna Using Differential Evolution Algorithm With Novel Evolutionary Operators

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