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Cited by 372

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

Robinson, J., Sinton, S., Rahmat-Samii, Y.·2003·IEEE Antennas and Propagation Society International Symposium (IEEE Cat. No.02CH37313)

Abstract

Genetic algorithms (GA) have proven to be a useful method of optimization for difficult and discontinuous multidimensional engineering problems. A new method of optimization, particle swarm optimization (PSO), is able to accomplish the same goal as GA optimization in a new and faster way. The purpose of this paper is to investigate the foundations and performance of the two algorithms when applied to the design of a profiled corrugated horn antenna. Also investigated is the possibility of hybridizing the two algorithms.

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Metadata

Authors
Robinson, J., Sinton, S., & Rahmat-Samii, Y.
Venue
IEEE Antennas and Propagation Society International Symposium (IEEE Cat. No.02CH37313)
Publisher
IEEE
Published
2003-06-25
Volume
1
Pages
314-317
ISSN
1522-3965 (ISSN-L)
OpenAlex
W1858731859
Cited by
372
References
3
FWCI
12.03
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Particle swarm, genetic algorithm, and their hybrids: optimization of a profiled corrugated horn antenna. https://app.cochat.ai/papers/10.1109/aps.2002.1016311
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Robinson, J., Sinton, S., & Rahmat-Samii, Y. (2003). Particle swarm, genetic algorithm, and their hybrids: optimization of a profiled corrugated horn antenna. IEEE Antennas and Propagation Society International Symposium (IEEE Cat. No.02CH37313). https://doi.org/10.1109/aps.2002.1016311

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.