Invasive Weed Optimization and its Features in Electromagnetics

Karimkashi, Shaya; Kishk, Ahmed A.

doi:10.1109/tap.2010.2041163

Cited by 338 publications

(180 citation statements)

References 34 publications

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“…Maximum and minimum numbers of seeds are the other two criteria than influence the performance of the algorithm. A value between 3 and 5 for the maximum and 0 for the minimum yields good results as found in many examples [28]. Finally the maximum number of plants should also be chosen for IWO.…”

Section: Selection Of Iwo Control Parametersmentioning

confidence: 90%

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Performance Comparison of Invasive Weed Optimization and Particle Swarm Optimization Algorithm for the tuning of Power System Stabilizer in Multi-machine Power System

Ahmed¹,

Amin²

2012

IJCA

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In this paper, two evolutionary algorithms-Invasive Weed Optimization (IWO) based power system stabilizer (PSS) and particle swarm optimization (PSO) based power system stabilizer is designed for multi-machine power system to compare their tuning performances. IWO is a derivative-free real parameter optimization technique that mimics the ecological behavior of colonizing weeds. PSO is also a derivative-free and flexible optimizer which is powered by the behavior of organism, such as bird flocking. Eigen-value based objective function is considered for the tuning of PSSs to enhance system damping of electromechanical mode. The performance of proposed IWO-based PSS and PSO-based PSS is tested and demonstrated under different disturbances for a four machine example power system. The Eigen value analysis and non-linear time domain simulation results shows that both IWO-based PSS and PSO-based design can successfully damp out the oscillations and thus improve the stability of the system. However, the abilities like faster convergence and greater shifting of critical modes to the left of s-plane keeps the choice of IWO based design in front of PSO based design for the system under consideration. General TermsPower system stability, Multi-machine system, Optimization.

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Section: Selection Of Iwo Control Parametersmentioning

confidence: 90%

“…In this work a two-axis synchronous generator model [28] given in the appendix is used for the simulation purpose. The linearized model of the power system around an operating point is usually employed for PSS design problem.…”

Section: Problem Statement 21 System Model and Pss Structurementioning

confidence: 99%

Performance Comparison of Invasive Weed Optimization and Particle Swarm Optimization Algorithm for the tuning of Power System Stabilizer in Multi-machine Power System

Ahmed¹,

Amin²

2012

IJCA

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show abstract

“…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%

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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“…A basic overview of metaheuristic methods is provided in [23]. Such methods include Ant Colony Optimization [24], Covariance Matrix Adaptation Evolution Strategy (CMA-ES) [25], Genetic Algorithms (GA) [26], Invasive Weed Optimization (IWO) [27], PSO [5][6][7][8][9][10], Simulated Annealing [28], and Tabu Search [29]. Among these optimization techniques, the PSO is a practical balance between model simplicity and robust, rapid, global solution convergence.…”

Section: Metaheuristic Optimization Methodsmentioning

confidence: 99%

“…Normalizing with respect to the square root of the areanormalized aperture power would effectively reduce the slope by the taper efficiency; whereas, the normalization of (27) by the peak of the matching sum pattern sets the (dual) peaks of all difference patterns at the same level of about −2 dB and so provides normalization independent of the taper efficiency. Bayliss [18] suggests comparing distributions by relative angle sensitivity, defined as normalizing by the maximum possible slope.…”

Section: Radiation Pattern Characteristicsmentioning

confidence: 99%

Three-Parameter Elliptical Aperture Distributions for Sum and Difference Antenna Patterns Using Particle Swarm Optimization

Densmore¹,

Rahmat‐Samii

2013

PIER

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Abstract-This paper presents a unified analysis of the threeparameter aperture distributions for both sum and difference antenna patterns, suitable for communications or telemetry applications with either a stationary or tracking antenna, and with the parameters automatically determined by Particle-Swarm Optimization (PSO). These distributions can be created, for example, by reflector, phased array, or other antenna systems. The optimizations involve multiple objectives, for which Pareto efficiency concepts apply, and are accelerated by compact, analytical closed-form equations for key metrics of the distributions, including the far-field radiation pattern and detection slope of the difference pattern. The limiting cases of the three-parameter distributions are discussed and shown to generalize other distributions in the literature. A derivation of the generalized vector far fields provides the background for the distribution study and helps clarify the definition of cross-polarization in the farfield. Examples are given to show that the three-parameter (3P) distributions meet a range of system-level constraints for various applications, including a sidelobe mask for satellite ground stations and maximizing pointing error detection sensitivity while minimizing clutter from sidelobes for tracking applications. The equations for the relative angle sensitivity for the difference pattern are derived. A study of the sensitivity of the 3P parameter values is presented.

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Invasive Weed Optimization and its Features in Electromagnetics

Cited by 338 publications

References 34 publications

Performance Comparison of Invasive Weed Optimization and Particle Swarm Optimization Algorithm for the tuning of Power System Stabilizer in Multi-machine Power System

Performance Comparison of Invasive Weed Optimization and Particle Swarm Optimization Algorithm for the tuning of Power System Stabilizer in Multi-machine Power System

Synthesis of Large Planar Thinned Arrays Using Iwo-Ift Algorithm

Three-Parameter Elliptical Aperture Distributions for Sum and Difference Antenna Patterns Using Particle Swarm Optimization

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