The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Genetic algorithm optimization applied to electromagnetics: a review
Abstract
Genetic algorithms are on the rise in electromagnetics as design tools and problem solvers because of their versatility and ability to optimize in complex multimodal search spaces. This paper describes the basic genetic algorithm and recounts its history in the electromagnetics literature. Also, the application of advanced genetic operators to the field of electromagnetics is described, and design results are presented for a number of different applications.
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Citations
Cites
Holland, J. H. (1992) · Scientific American · doi:10.1038/scientificamerican0792-66 · Cited by 5,764
Cited by
Differential Evolution as Applied to Electromagnetics
Rocca, P., Oliveri, G., & Massa, A. (2011) · IEEE Antennas and Propagation Magazine · doi:10.1109/map.2011.5773566 · Cited by 580
Metadata
- Authors
- Weile, D. S., & Michielssen, E.
- Venue
- IEEE Transactions on Antennas and Propagation
- Published
- 1997-03
- Volume
- 45
- Issue
- 3
- Pages
- 343-353
- ISSN
- 0018-926X (ISSN-L)
- OpenAlex
- W2149368520
- Cited by
- 881
- References
- 1
- FWCI
- 62.20
- Type
- journal article
- Language
- en
- Open access
- closed
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- Weile, D. S., & Michielssen, E. (1997). Genetic algorithm optimization applied to electromagnetics: a review. IEEE Transactions on Antennas and Propagation. https://doi.org/10.1109/8.558650
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
