Efficiency-constrained particle swarm optimization of a modified bernstein polynomial for conformal array excitation amplitude synthesis

Boeringer, D.W.; Werner, Douglas H.

doi:10.1109/tap.2005.851783

Cited by 90 publications

(46 citation statements)

References 61 publications

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“…Genetic algorithms (GAs), particle swarm optimization (PSO), differential evolution (DE) and related techniques dominate as the mainstream evolutionary strategies (ES), mostly due to widespread availability, understanding and user confidence [1]- [11]. These optimization techniques have enjoyed a great deal of success and have been applied in a wide variety of electromagnetic device design problems including antennas [12]- [19], antenna arrays [20]- [29], frequency selective surfaces [30]- [36], filters [37] and [38] and many others. The utility of the algorithms allows application to any EM design problem that can be reduced to a simple set of defining parameters.…”

Section: Introductionmentioning

confidence: 99%

Fast Optimization of Electromagnetic Design Problems Using the Covariance Matrix Adaptation Evolutionary Strategy

Gregory

Bayraktar

Werner

2011

IEEE Trans. Antennas Propagat.

185

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A new method of optimization recently made popular in the evolutionary computation (EC) community is introduced and applied to several electromagnetics design problems. First, a functional overview of the covariance matrix adaptation evolutionary strategy (CMA-ES) is provided. Then, CMA-ES is critiqued alongside a conventional particle swarm optimization (PSO) algorithm via the design of a wideband stacked-patch antenna. Finally, the two algorithms are employed for the design of small to moderate size aperiodic ultrawideband antenna array layouts (up to 100 elements). The results of the two electromagnetics design problems illustrate the ability of CMA-ES to provide a robust, fast and user-friendly alternative to more conventional optimization strategies such as PSO. Moreover, the ultrawideband array designs that were created using CMA-ES are seen to exhibit performances surpassing the best examples that have been reported in recent literature.Index Terms-Covariance matrix adaptation, evolutionary strategy, microstrip antennas, optimization algorithm, particle swarm optimization, self-adaptive, stacked patch antenna.

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Section: Introductionmentioning

confidence: 99%

Fast Optimization of Electromagnetic Design Problems Using the Covariance Matrix Adaptation Evolutionary Strategy

Gregory

Bayraktar

Werner

2011

IEEE Trans. Antennas Propagat.

185

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“…Considering that the optimization for excitation amplitude of each element on this cylindrical array may be a formidable task in engineering practice, a modified Bernstein polynomial for arc arrays is extended here to reduce the number of optimization parameters. The modified Bernstein polynomial [25] is defined as follows:…”

Section: Pattern Synthesismentioning

confidence: 99%

Modified Differential Evolution Algorithm for Pattern Synthesis of Antenna Arrays

Li¹,

Li²,

Shi³

et al. 2013

PIER

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Abstract-A modified differential evolution algorithm (MDE) for pattern synthesis of antenna arrays is proposed in this paper. By employing the novel strategies of best of random mutation and randomized local search, the convergence of standard differential evolution algorithm (SDE) is significantly accelerated. Five standard benchmark functions are optimized to testify the proposed algorithm by comparison with several other optimization algorithms. The numerical results verify the superior performance of the proposed MDE. Furthermore, the MDE is applied to two pattern synthesis examples, including a linear array and a cylindrical conformal array. Experiment results demonstrate that the proposed MDE has better performance than the other optimization methods in both of these two examples, which indicate the proposed algorithm is a competitive optimization algorithm in pattern synthesis.

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“…In recent years, the evolutionary algorithms (EAs) for array synthesis have been extensively studied [1,[3][4][5][6][7][8][9][10][11][12][13][14][15][16][17]. Several global optimization algorithms such as differential evolution (DE) [3][4][5], genetic algorithm (GA) [6][7][8], ant colony optimization (ACO) [9], and particle swarm optimization (PSO) [10][11][12][13][14][15] are used in antenna array pattern. However, these methods appear certain drawbacks to the possibility of premature convergence to a local optimum when achieving the global optimum.…”

Section: Introductionmentioning

confidence: 99%

Synthesis of Unequally Spaced Antenna Arrays by Using Inheritance Learning Particle Swarm Optimization

Liu

Feng²,

Wang³

et al. 2011

PIER

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Abstract-In this paper, synthesis of unequally spaced linear antenna arrays based on an inheritance learning particle swarm optimization (ILPSO) is presented. In order to improve the optimization efficiency of the PSO algorithm, we propose an inheritance learning strategy that can be applied to different topology of different PSO algorithms. In ILPSO algorithm, each cycle contains several PSO optimization processes, and uniform initial particle positions, part of which inherited from the good results in pre-cycles, are adopted in post-cycles. ILPSO enhances the exploration ability of PSO algorithm significantly, and can escape from the trap of local optimum areas with greater probability. The results demonstrate good performance of the ILPSO in solving a set of eight 30-D benchmark functions when compared to nine other variants of the PSO. The novel proposed algorithm has been applied in 32-element position-only array synthesis with three different constraints, simulation results show that ILPSO obtains better synthesis results reliably and efficiently.

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Efficiency-constrained particle swarm optimization of a modified bernstein polynomial for conformal array excitation amplitude synthesis

Cited by 90 publications

References 61 publications

Fast Optimization of Electromagnetic Design Problems Using the Covariance Matrix Adaptation Evolutionary Strategy

Fast Optimization of Electromagnetic Design Problems Using the Covariance Matrix Adaptation Evolutionary Strategy

Modified Differential Evolution Algorithm for Pattern Synthesis of Antenna Arrays

Synthesis of Unequally Spaced Antenna Arrays by Using Inheritance Learning Particle Swarm Optimization

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