Particle swarm, genetic algorithm, and their hybrids: optimization of a profiled corrugated horn antenna

By Jacob T. Robinson, S. Sinton, Yahya Rahmat-Samii. IEEE Antennas and Propagation Society International Symposium, 2002

396 citations recorded by the source corpus.

Subfields: Aerospace Engineering, Computational Theory and Mathematics, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/2b466ee2d8f0bf9aa655891a78b8a1685f2602cb

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Citations in the corpus

An improved GA and a novel PSO-GA-based hybrid algorithm (2005, background): “Particle Swarm Optimization (PSO) also is an e lutionary computational model which is based swarm intelligence.”
Parallel particle swarm optimization and finite- difference time-domain (PSO/FDTD) algorithm for multiband and wide-band patch antenna designs (2005, methodology): “PSO has been applied to many EM applications, such as the one-dimensional (1-D) and 2-D array synthesize [5]–[7], the corrugated horn design [8], and the reflector shaping [9].”
Particle swarm optimization algorithm: an overview (2017, methodology): “Robinson et al. (2002) pointed out that the PSO algorithm and GA algorithm could be used in turn, i.e., taking the population optimized by the PSO algorithm as the initial population of the GA algorithm, or conversely, taking the population optimized by GA algorithm as the initial population of the…”
Particle Swarm Optimization and Differential Evolution Algorithms: Technical Analysis, Applications and Hybridization Perspectives (2008, background): “One approach is to mutate parameters such as χ, C1 and C2, the position of the neighborhood best [26], as well as the inertia weight [25].”
Particle Swarm Optimization: A survey of historical and recent developments with hybridization perspectives (2018, methodology): “[36] 2002 GA-PSO, PSO-GA Engineering design optimization Krink and Løvbjerg [41] 2002 Life Cycle Model Unconstrained global optimization”
Computational approach based on a particle swarm optimizer for microwave imaging of two-dimensional dielectric scatterers (2005, background): “Reference problem geometry. 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).”
A Competitive Swarm Optimizer for Large Scale Optimization (2015, methodology): “One straightforward idea is to combine PSO with different evolutionary algorithms, such as genetic algorithms [26], differential evolution [27], and ant colony optimization [28], [29].”
A social learning particle swarm optimization algorithm for scalable optimization (2015, methodology): “Then, a detailed description of SL-PSO will be provided together with an analysis of the computational complexity and a convergence proof.”
Particle swarm optimization in electromagnetics (2004, methodology): “methods of optimization such as GA and micro-GA ( GA) [2], [12].”