Performance Comparison of Differential Evolution, Particle Swarm Optimization and Genetic Algorithm in the Design of Circularly Polarized Microstrip Antennas

Deb, Arindam; Roy, Jibendu Sekhar; Gupta, Bhaskar

doi:10.1109/tap.2014.2322880

Cited by 113 publications

(33 citation statements)

References 30 publications

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“…Furthermore, for the sake of evaluation reliability, computational models utilized in the design process should incorporate environmental components such as connectors. A large variety of optimization algorithms have been utilized and proposed for antenna design, including local search methods (both gradient‐based, and derivative‐free) as well as global algorithms, mostly population‐based metaheuristics (genetic algorithms, particle swarm optimizers, differential evolution, etc.). Recently, surrogate‐based optimization methods have been applied for computationally‐efficient optimization of antenna structures, including compact antennas …”

Section: Introductionmentioning

confidence: 99%

Simulation-based optimization for rigorous assessment of ground plane modifications in compact UWB antenna design

Haq

Koziel

2017

Int J RF Microw Comput Aided Eng

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Introducing ground plane modifications is a popular approach in the design of compact UWB antennas. Yet, specific topological alterations are normally reported on case to case basis without thorough investigations concerning their general suitability for antenna miniaturization. In particular, detailed performance comparison of different ground plane modifications is lacking in the literature. In this article, the effect of selected ground plane modifications on achievable miniaturization rate is considered based on a set of four UWB antennas. EM‐driven optimization is carried out to minimize the antenna footprints while maintaining acceptable matching within the UWB frequency range. In each case, all geometry parameters of the respective structures are utilized in the design process. For the sake of fair comparison, all antennas are implemented on the same dielectric substrate. Our results indicate a clear performance pattern, here, an advantage of the elliptical ground plane slit below the feed line over the rectangular one (average size reduction ratio of 26% versus 19% across the benchmark set). Our conjectures are confirmed by physical measurements of the fabricated antenna prototypes.

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Section: Introductionmentioning

confidence: 99%

Simulation-based optimization for rigorous assessment of ground plane modifications in compact UWB antenna design

Haq

Koziel

2017

Int J RF Microw Comput Aided Eng

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“…During the last decades evolutionary algorithms have been widely used for parameter optimization in different engineering tasks [1][2][3]. Engineering optimization has been widely involved in aerospace sciences because of its practicality in obtaining optimal solutions in different challenging problems including dynamics and control of nonlinear systems [4][5][6].…”

Section: Introductionmentioning

confidence: 99%

Analysis of a hybrid genetic simulated annealing strategy applied in multi-objective optimization of orbital maneuvers

Shirazi

2017

IEEE Aerosp. Electron. Syst. Mag.

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Optimization of orbital maneuvers is one of the main issues in conceptual and preliminary design of spacecraft in different space missions. The main issue in optimization of highthrust orbit transfers is that the common optimization algorithms such as Genetic Algorithm and Simulated Annealing are not effectual in finding optimal transfer when they are purely used in optimization. In such problems, modified algorithms are required to find the optimal transfer. Such modifications involve consecutive search and dynamic boundary delimitation. This paper presents a direct approach to optimize high-thrust orbit transfers using a hybrid algorithm based on Simulated Annealing and Genetic Algorithm. This multiobjective optimization method considers optimum fuel transfers while minimizing the error of orbital elements at the end of orbital maneuver. Trajectory optimization is conducted based on converting the orbit transfer problem into a parameter optimization one by assigning proper mathematical functions to the variation of thrust vector direction.Optimization problem is solved using intelligent boundary delimitation in a general optimization method. Taking advantage of nonlinear simulation, a technique is proposed to acquire good quantity for optimization variables, which results in enlarged convergence domain. Numerical example of a three dimensional optimal orbit transfer is analyzed and the accuracy of proposed algorithm is presented. Optimality and convergence of the proposed algorithm is discussed by comparing the results obtained by different approaches.Results confirm the efficiency of the proposed hybrid algorithm in comparison to Simulated Annealing and Genetic Algorithm.

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“…Particularly, DE may suffer from premature convergence and/or slow convergence when solving complex multimodal optimization problems. In order to improve the performance of the conventional DE, a number of DE variants have been proposed in recent decades [2, 6, 10]. Recognizing that the performance of DE depends on the control parameters, Brest et al [11] presented a self-adaptive DE (jDE), in which both F and CR are created independently for each individual by an adaptive mechanism.…”

Section: Introductionmentioning

confidence: 99%

An Enhanced Differential Evolution with Elite Chaotic Local Search

Guo

Huang

Deng

et al. 2015

Computational Intelligence and Neuroscience

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Differential evolution (DE) is a simple yet efficient evolutionary algorithm for real-world engineering problems. However, its search ability should be further enhanced to obtain better solutions when DE is applied to solve complex optimization problems. This paper presents an enhanced differential evolution with elite chaotic local search (DEECL). In DEECL, it utilizes a chaotic search strategy based on the heuristic information from the elite individuals to promote the exploitation power. Moreover, DEECL employs a simple and effective parameter adaptation mechanism to enhance the robustness. Experiments are conducted on a set of classical test functions. The experimental results show that DEECL is very competitive on the majority of the test functions.

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Performance Comparison of Differential Evolution, Particle Swarm Optimization and Genetic Algorithm in the Design of Circularly Polarized Microstrip Antennas

Cited by 113 publications

References 30 publications

Simulation-based optimization for rigorous assessment of ground plane modifications in compact UWB antenna design

Simulation-based optimization for rigorous assessment of ground plane modifications in compact UWB antenna design

Analysis of a hybrid genetic simulated annealing strategy applied in multi-objective optimization of orbital maneuvers

An Enhanced Differential Evolution with Elite Chaotic Local Search

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