Array Pattern Synthesis Using Particle Swarm Optimization with Dynamic Inertia Weight

Han, Chuang

doi:10.1155/2016/1829458

Cited by 12 publications

(11 citation statements)

References 17 publications

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“…We note, also, that very many papers that assume Gbest as orthodoxy also go on to mention the particle swarm's "well known tendency to converge prematurely." For example, this view point is clearly stated in Pant's study in 2008 [31], Van den Burgh et al's 2010 paper on PSO convergence [32] and Han and Wang's 2013 paper [33].…”

Section: F the Rise Of Gbestmentioning

confidence: 94%

Impact of Communication Topology in Particle Swarm Optimization

Blackwell

Kennedy

2019

IEEE Trans. Evol. Computat.

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Particle Swarm Optimisation has two salient components: a dynamical rule governing particle motion and an interparticle communication topology. Recent practice has focused on the fully connected topology (Gbest) despite earlier indications on the superiority of local particle neighborhoods. This paper seeks to address the controversy with empirical trials with canonical PSO on a large benchmark of functions, categorized into fourteen properties.This paper confirms the early lore that Gbest is the overall better algorithm for unimodal and separable problems and that a ring neighborhood of connectivity two (Lbest) is the preferred choice for multimodal, non-separable and composition functions. Topologies of intermediate particle connectivity were also tested and the difference in global/local performance was found to be even more marked.A measure of significant improvement is introduced in order to distinguish major improvements from refinements. Lbest, according to the experiments on the 84 test functions and a bimodal problem of adjustable severity, is found to have significant improvements later in the run, and to be more diverse at termination. A mobility study shows that Lbest is better able to jump between optimum basins. Indeed Gbest was unable to switch basins in the bi-modal trial.The implication is that Lbest's larger terminal diversity, its better ability to basin hop and its later significant improvement account for the performance enhancement. In several cases where Lbest was not the better algorithm, the trials show that Lbest was not stuck but would have continued to improve with an extended evaluation budget.Canonical PSO is a baseline algorithm and the ancestor of all contemporary PSO variants. These variants build on the basic structure of baseline PSO and the broad conclusions of this study are expected to follow through. In particular, research that fails to consider local topologies risks underplaying the success of the promoted algorithm.

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Section: F the Rise Of Gbestmentioning

confidence: 94%

Impact of Communication Topology in Particle Swarm Optimization

Blackwell

Kennedy

2019

IEEE Trans. Evol. Computat.

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“…When the termination condition is satisfied, the optimal variable values can be obtained as the optimal particle over the iteration history. For details of the PSO, readers could refer to [20] and the references therein.…”

Section: Optimization Model Of Suacramentioning

confidence: 99%

“…Due to its high search efficiency, PSO has been widely used in enhancing antenna gain [19] and beam pattern synthesis [20] and improving BCE of a MPT system [10]. In this work, the synthesis of the sparse uniform-amplitude transmitting array is discussed for the optimal MPT.…”

Section: Introductionmentioning

confidence: 99%

Synthesis of the Sparse Uniform-Amplitude Concentric Ring Transmitting Array for Optimal Microwave Power Transmission

Zhou

Yang

Rahim

2018

International Journal of Antennas and Propagation

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Beam capture efficiency (BCE) is one key factor of the overall efficiency for a microwave power transmission (MPT) system, while sparsification of a large-scale transmitting array has a practical significance. If all elements of the transmitting array are excited uniformly, the fabrication, maintenance, and feed network design would be greatly simplified. This paper describes the synthesis method of the sparse uniform-amplitude transmitting array with concentric ring layout using particle swarm optimization (PSO) algorithm while keeping a higher BCE. Based on this method, uniform exciting strategy, reduced number of elements, and a higher BCE are achieved simultaneously for optimal MPT. The numerical results of the sparse uniform-amplitude concentric ring arrays (SUACRAs) optimized by the proposed method are compared with those of the random-located uniform-amplitude array (RLUAA) and the stepped-amplitude array (SAA), both being reported in the literatures for the maximum BCE. Compared to the RLUAA, the SUACRA saves 32% elements with a 1.1% higher BCE. While compared to the SAA, the SUACRA saves 29.1% elements with a bit higher BCE. The proposed SUACRAs have higher BCEs, simple array arrangement and feed network, and could be used as the transmitting array for a large-scale MPT system.

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“…where α p M and α n M are the positive nondomination factor and the negative nondomination factor respectively, and t is the current iteration with the total iteration number T. This dynamic nondomination factor is easily realized, and we can use different formations according to the optimization problem [25].…”

Section: Dynamic Nondomination Strategymentioning

confidence: 99%