The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.
A comprehensive review of firefly algorithms
Open accessAbstract
Abstract The firefly algorithm has become an increasingly important tool of Swarm Intelligence that has been applied in almost all areas of optimization, as well as engineering practice. Many problems from various areas have been successfully solved using the firefly algorithm and its variants. In order to use the algorithm to solve diverse problems, the original firefly algorithm needs to be modified or hybridized. This paper carries out a comprehensive review of this living and evolving discipline of Swarm Intelligence, in order to show that the firefly algorithm could be applied to every problem arising in practice. On the other hand, it encourages new researchers and algorithm developers to use this simple and yet very efficient algorithm for problem solving. It often guarantees that the obtained results will meet the expectations.
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Cites
A fast and elitist multiobjective genetic algorithm: NSGA-II
Deb, K., Pratap, A., Agarwal, S., & Meyarivan, T. (2002) · IEEE Transactions on Evolutionary Computation · doi:10.1109/4235.996017 · Cited by 50,053
Storn, R., & Price, K. (1997) · Journal of Global Optimization · doi:10.1023/a:1008202821328 · Cited by 29,569
No free lunch theorems for optimization
Wolpert, D. H., & Macready, W. G. (1997) · IEEE Transactions on Evolutionary Computation · doi:10.1109/4235.585893 · Cited by 14,237
Differential Evolution: A Survey of the State-of-the-Art
Das, S., & Suganthan, P. N. (2011) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2010.2059031 · Cited by 5,307
Cited by
Bio inspired computing – A review of algorithms and scope of applications
Kar, A. K. (2016) · Expert Systems with Applications · doi:10.1016/j.eswa.2016.04.018 · Cited by 578
Wang, D., Luo, H., Grunder, O., Lin, Y., & Guo, H. (2017) · Applied Energy · doi:10.1016/j.apenergy.2016.12.134 · Cited by 312
A novel efficient substitution-box design based on firefly algorithm and discrete chaotic map
Ahmed, H. A., Zolkipli, M. F., & Ahmad, M. (2019) · Neural Computing and Applications · doi:10.1007/s00521-018-3557-3 · Cited by 142
Eren, Y., Küçükdemiral, İ. B., & Üstoğlu, İ. (2017) · Optimization in Renewable Energy Systems · doi:10.1016/b978-0-08-101041-9.00002-8 · Cited by 67
Miguel, L. F. F., Fadel Miguel, L. F., & Lopez, R. H. (2015) · Optimization and Engineering · doi:10.1007/s11081-014-9269-3 · Cited by 52
Metadata
- Authors
- Fister, I., Fister, I., Yang, X.-S., & Brest, J.
- Venue
- Swarm and Evolutionary Computation
- Publisher
- Elsevier BV
- Published
- 2013-12
- Volume
- 13
- Pages
- 34-46
- ISSN
- 2210-6502 (ISSN-L)
- OpenAlex
- W2044587647
- Cited by
- 1,308
- References
- 4
- FWCI
- 86.14
- Type
- journal article
- Language
- en
- Open access
- green
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- Fister, I., Fister, I., Yang, X.-S., & Brest, J. (2013). A comprehensive review of firefly algorithms. Swarm and Evolutionary Computation. https://doi.org/10.1016/j.swevo.2013.06.001
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