Particle swarm optimization in electromagnetics

By Jacob T. Robinson, Yahya Rahmat-Samii. IEEE Transactions on Antennas and Propagation, 2004

2,275 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Artificial Intelligence, Computational Theory and Mathematics

View Paper: https://www.semanticscholar.org/paper/7cd1e7844c057273417ec7c1255886d1687cdf01

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Citations in the corpus

Stochastic Optimization Methods Applied to Microwave Imaging: A Review (2007, background): “ticle swarm optimization (PSO), has been applied to several electromagnetic problems and, in some cases, it seemed to outperform other EAs (see, for example, [23]).”
Boundary Conditions in Particle Swarm Optimization Revisited (2007, background): “invisible, and damping, have been reported in literature [2], [4], and the unique features that distinguish each boundary condition are summarized in Fig.”
Invasive Weed Optimization and its Features in Electromagnetics (2010, background): “Among these optimizers, genetic algorithm (GA) [1] and particle swarm optimization (PSO) [2] have received considerable attentions by the electromagnetic community due to their efficiency and simplicity [3]–[6].”
Multiobjective robust optimization method for drawbead design in sheet metal forming (2010, background): “neutral network, pattern recognition, fuzzy system control and other fields [36–41].”
A review of particle swarm optimization. Part II: hybridisation, combinatorial, multicriteria and constrained optimization, and indicative applications (2008, methodology): “Robinson and Rahmat-Samii (2004) applied PSO to the design of a profiled corrugated horn antenna.”
Minimum Sidelobe Levels for Linear Arrays (2007, background): “For a discussion of the details of PSO, the reader is referred to [4], [17].”
Antenna Current Optimization using MATLAB and CVX (2016, methodology): “Global, stochastic, or metaheuristic optimization algorithms, such as Genetic Algorithms [44, 62], particle swarm [63], simulated annealing and Monte Carlo, are often used.”
Multiobjective Particle Swarm Optimization to Design a Time-Delay Equalizer Metasurface for an Electromagnetic Band-Gap Resonator Antenna (2017, methodology): “It was introduced to the field of electromagnetics in 2004 [2] and has been applied for several electromagnetic applications since then [3]–[7].”
Application of the invasive weed optimization technique for antenna configurations (2008, methodology): “Genetic algorithm [1], Particle swarm optimization [2, 3] and ant colony [4, 5] are such methods that have already been used in antenna optimization problems.”
Computational approach based on a particle swarm optimizer for microwave imaging of two-dimensional dielectric scatterers (2005, methodology): “applied and computational electromagnetics where GAs found great success (let us see [16]‐[18] for some applications in the field of antenna synthesis and [ 19 ] for a general overview).”
Evolutionary optimization as applied to inverse scattering problems (2009, background): “, the crossover, the mutation and the selection); • the easy manipulation of the calibration parameters [138] (i.”
Particle swarm optimization algorithm: an overview (2017, methodology): “There are two main methods to maintain the diversity of the MOPSO: Sigma method (Lovbjerg and Krink 2002) and ε -dominance method (Juang et al. 2011; Robinson and Rahmat-Samii 2004).”