Magnetic-inspired optimization algorithms: Operators and structures
- Submitting institution
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University of Hertfordshire
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 16422088
- Type
- D - Journal article
- DOI
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10.1016/j.swevo.2014.06.004
- Title of journal
- Swarm and Evolutionary Computation
- Article number
- -
- First page
- 82
- Volume
- 19
- Issue
- -
- ISSN
- 2210-6502
- Open access status
- Out of scope for open access requirements
- Month of publication
- July
- Year of publication
- 2014
- URL
-
-
- Supplementary information
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-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
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1
- Research group(s)
-
-
- Citation count
- 9
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This research proposes a new set of optimization algorithms. These algorithms have been used in real-world applications including wind energy optimization [1], antenna array optimization [2], training neural networks [3] etc.
[1] Behera, Sasmita, Subhrajit Sahoo, and B. B. Pati, Renewable and Sustainable Energy Reviews 48, 214-227 (2015).
[2] Bouchekara, H. R. E. H., Artificial Intelligence Review (2020), https://doi.org/10.1007/s10462-020-09890-x.
[3] Ansari, Abdollah, et al., IEEE Access 8 (2020): 176640-176650 (2020).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -