Application of the invasive weed optimization technique for antenna configurations

Dadalipour, B.; Mallahzadeh, Alireza; Davoodi-Rad, Zahra

doi:10.1109/lapc.2008.4516957

Cited by 14 publications

(4 citation statements)

References 13 publications

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“…Inspired from the behavior of colonization of invasive weeds in nature that try to find a suitable place for growth and reproduction, the invasive weed optimization was first proposed by Mehrabian and Lucas for solving continuous optimization problems [12], has found several applications in antenna design [13][14][15][16][17] as well as array's far field pattern synthesis [18][19][20][21][22][23]. All the attempts have shown the robustness, high efficiency of the IWO.…”

Section: Description Of the Iwo-ift Methodsmentioning

confidence: 99%

“…In the proposed method, a recently developed algorithm, invasive weed optimization (IWO) [13], is used to perturb the ranking of the amplitudes of the best element excitations for the thinned array produced by IFT in order to find better solutions. Synthesis results for thinning circular arrays with a wide range of diameters validated the superiority of the IWO-IFT.…”

Section: Introductionmentioning

confidence: 99%

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Synthesis of Large Planar Thinned Arrays Using Iwo-Ift Algorithm

Wang¹,

Jiao²,

Liu³

et al. 2013

PIER

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Abstract-The iterative Fourier technique (IFT) is a high efficiency method that was proposed in recent past for the synthesis of large planar thinned arrays with isotropic radiating elements. However, the selection mechanism of IFT cannot always include the most useful elements in the "turned ON" families, which make the method trap in some local minima. Therefore, in this paper, inspired by invasive weed optimization (IWO) algorithm, a developed version of the iterative Fourier technique (IFT), IWO-IFT, is proposed for thinning large planar arrays. In this new method, the initial weeds are produced by IFT, and are further perturbed by IWO through repeatedly reproduction, dispersion, and exclusion over search space to find better weeds. Numerical results for synthesizing different circular thinned arrays demonstrated the superiority of IWO-IFT over the IFT method.

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Section: Description Of the Iwo-ift Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Synthesis of Large Planar Thinned Arrays Using Iwo-Ift Algorithm

Wang¹,

Jiao²,

Liu³

et al. 2013

PIER

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“…The PSO algorithm is one of the most powerful optimization methods based on an evolutionary computation technique, however, this algorithm has shown disadvantages such as premature convergence in addressing the multiparameter problems [11], The IWO algorithm is one of the more recent direct optimization methods, which was proposed by Mehrabian and Lucas in 2006 [12], The IWO algorithm is a bioinspired numerical optimization algorithm that simply simulates the natural behavior of weeds in colonizing and finding a suitable place for growth and reproduction. Despite its recent development, it has shown successful results in a number of practical applications like optimization and tuning of a robust controller [12], optimal positioning of piezoelectric actuators [13], development of a recommender system [14], antenna configuration optimization [15], design of an E-shaped multiple input multiple output (MIMO) antenna [16], design of a compact U-array MIMO antenna [17], DNA computing [18], and so on. However, it has been shown that the IWO algorithm imposes an amount of exploitation and is prone to getting trapped in local optima [11], Recently, in the literature, there has been considerable attention paid to combining and modifying conventional optimization algorithms in order to improve their performances and to overcome the drawbacks of these algorithm such as premature convergence, getting trapped in a local optima, and having a low solution precision.…”

Section: Introductionmentioning

confidence: 99%

Metaheuristic Design and Optimization of Fuzzy-Based Gas Turbine Engine Fuel Controller Using Hybrid Invasive Weed Optimization/Particle Swarm Optimization Algorithm

Mohammadi¹,

Montazeri-Gh²,

Khalaf

2013

Journal of Engineering for Gas Turbines and Power

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This paper presents the metaheuristic design and optimization of fuzzy-based gas turbine engine (GTE) fuel flow controller by means of a hybrid invasive weed optimization!particle swarm optimization (IWO/PSO) algorithm as an innovative guided search technique. In this regard, first, a Wiener model for the GTE as a block-structured model is developed and validated against experimental data. Subsequently, because of the nonlinear nature of GTE, a fuzzy logic controller (FLC) strategy is considered for the engine fuel system. For this purpose, an initial FLC is designed and the parameters are then tuned using a hybrid IWOIPSO algorithm where the tuning process is formulated as an engineering optimization problem. The fuel consumption, engine safety, and time response are the performance indices of the defined objective function. In addition, two sets of weighting factors for objective function are considered, whereas in one of them savings in fuel consumption and in another achieving a short response time for the engine is a priority. Moreover, the optimization process is performed in two stages during which the database and the rule base of the initial FLC are tuned sequentially. The simulation results confirm that the IWO/PSO-FLC approach is effective for GTE fuel controller design, resulting in improved engine performance as well as ensuring engine protection against physical limitations.

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“…application problems, such as configurations of antenna [12], design of encoding sequences for DNA computing [13], developing a recommender system [14] and adaptive beam forming [15] etc. Subsequently, the original IWO was extended to handle multi-objective problems in [16], which is named as IWO MO.…”

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confidence: 99%

Enhancing multi-objective Invasive Weed Optimization with information exchange in Intra- and Inter-Communities

Cai

2012

2012 IEEE Fifth International Conference on Advanced Computational Intelligence (ICACI)

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Inspired from colonizing weeds, a simple but effective multi-objective optimization algorithm, named as Multiobjective Invasive Weed Optimization (IWO MO), has been proposed recently and proved to be superior to other stateof-the-art algorithms. In this paper, we propose the Intraand Inter-operator, which exchanges information among the Intra-and Inter-Communities of weeds, to further improve the performance of the IWO MO. The proposed algorithm, named as IWO MO2, is tested on various multi-objective benchmark test functions. Results suggest that the proposed IWO MO2 is more effective on tackling multi-objective problems and the obtained Pareto approximative Front is very close to the true Pareto optimal Front.

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Application of the invasive weed optimization technique for antenna configurations

Cited by 14 publications

References 13 publications

Synthesis of Large Planar Thinned Arrays Using Iwo-Ift Algorithm

Synthesis of Large Planar Thinned Arrays Using Iwo-Ift Algorithm

Metaheuristic Design and Optimization of Fuzzy-Based Gas Turbine Engine Fuel Controller Using Hybrid Invasive Weed Optimization/Particle Swarm Optimization Algorithm

Enhancing multi-objective Invasive Weed Optimization with information exchange in Intra- and Inter-Communities

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