The DOI matches its Crossref record; 59 of the 59 references it cites were found in a registry or an index.
Moth–flame optimization algorithm: variants and applications
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Cites
Optimization by Simulated Annealing
Kirkpatrick, S., Gelatt, C. D., & Vecchi, M. P. (1983) · Science · doi:10.1126/science.220.4598.671 · Cited by 45,134
Particle swarm optimization: An overview
Poli, R., Kennedy, J., & Blackwell, T. (2007) · Swarm Intelligence · doi:10.1007/s11721-007-0002-0 · Cited by 21,101
(2019) · Handbook of Machine Learning · doi:10.1142/9789811205675_0004 · Cited by 6,270
A New Heuristic Optimization Algorithm: Harmony Search
Geem, Z. W., Kim, J. H., & Loganathan, G. V. (2001) · SIMULATION · doi:10.1177/003754970107600201 · Cited by 6,247
Salp Swarm Algorithm: A bio-inspired optimizer for engineering design problems
Mirjalili, S., Gandomi, A. H., Mirjalili, S. Z., Saremi, S., Faris, H., & Mirjalili, S. M. (2017) · Advances in Engineering Software · doi:10.1016/j.advengsoft.2017.07.002 · Cited by 5,082
Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm
Mirjalili, S. (2015) · Knowledge-Based Systems · doi:10.1016/j.knosys.2015.07.006 · Cited by 4,626
HEURISTICS FOR INTEGER PROGRAMMING USING SURROGATE CONSTRAINTS
Glover, F. (1977) · Decision Sciences · doi:10.1111/j.1540-5915.1977.tb01074.x · Cited by 1,363
The ecological impacts of nighttime light pollution: a mechanistic appraisal
Gaston, K. J., Bennie, J., Davies, T. W., & Hopkins, J. (2013) · Biological Reviews · doi:10.1111/brv.12036 · Cited by 1,110
Genetic Algorithms for Real Parameter Optimization
Wright, A. H. (1991) · Foundations of Genetic Algorithms · doi:10.1016/b978-0-08-050684-5.50016-1 · Cited by 998
Feature selection based on rough sets and particle swarm optimization
Wang, X., Yang, J., Teng, X., Xia, W., & Jensen, R. (2007) · Pattern Recognition Letters · doi:10.1016/j.patrec.2006.09.003 · Cited by 837
Cited by
Abualigah, L., & Diabat, A. (2021) · Cluster Computing · doi:10.1007/s10586-020-03075-5 · Cited by 355
Self-citation
Metadata
- Authors
- Shehab, M., Abualigah, L., Al Hamad, H., Alabool, H., Alshinwan, M., & Khasawneh, A. M.
- Venue
- Neural Computing and Applications
- Published
- 2019-10-31
- Volume
- 32
- Issue
- 14
- Pages
- 9859-9884
- ISSN
- 0941-0643 (ISSN-L)
- 1433-3058
- OpenAlex
- W2985638660
- Cited by
- 316
- References
- 59
- FWCI
- 14.04
- Type
- journal article
- Language
- en
- Open access
- closed
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- Shehab, M., Abualigah, L., Al Hamad, H., Alabool, H., Alshinwan, M., & Khasawneh, A. M. (2020). Moth–flame optimization algorithm: variants and applications. Neural Computing and Applications. https://doi.org/10.1007/s00521-019-04570-6
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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.
