The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Artificial gorilla troops optimizer: A new nature‐inspired metaheuristic algorithm for global optimization problems
Open accessAbstract
Metaheuristics play a critical role in solving optimization problems, and most of them have been inspired by the collective intelligence of natural organisms in nature. This paper proposes a new metaheuristic algorithm inspired by gorilla troops' social intelligence in nature, called Artificial Gorilla Troops Optimizer (GTO). In this algorithm, gorillas' collective life is mathematically formulated, and new mechanisms are designed to perform exploration and exploitation. To evaluate the GTO, we apply it to 52 standard benchmark functions and seven engineering problems. Friedman's test and Wilcoxon rank-sum statistical tests statistically compared the proposed method with several existing metaheuristics. The results demonstrate that the GTO performs better than comparative algorithms on most benchmark functions, particularly on high-dimensional problems. The results demonstrate that the GTO can provide superior results compared with other metaheuristics.
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Cites
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
Holland, J. H. (1992) · Scientific American · doi:10.1038/scientificamerican0792-66 · Cited by 5,764
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Rajwar, K., Deep, K., & Das, S. (2023) · Artificial Intelligence Review · doi:10.1007/s10462-023-10470-y · Cited by 687
Abdollahzadeh, B., Gharehchopogh, F. S., Khodadadi, N., & Mirjalili, S. (2022) · Advances in Engineering Software · doi:10.1016/j.advengsoft.2022.103282 · Cited by 482
Self-citationAdvances in Sparrow Search Algorithm: A Comprehensive Survey
Gharehchopogh, F. S., Namazi, M., Ebrahimi, L., & Abdollahzadeh, B. (2023) · Archives of Computational Methods in Engineering · doi:10.1007/s11831-022-09804-w · Cited by 399
Self-citationMafarja, M., Thaher, T., Al-Betar, M. A., Too, J., Awadallah, M. A., Abu Doush, I., & Turabieh, H. (2023) · Applied Intelligence · doi:10.1007/s10489-022-04427-x · Cited by 91
Metadata
- Authors
- Abdollahzadeh, B., Soleimanian Gharehchopogh, F., & Mirjalili, S.
- Venue
- International Journal of Intelligent Systems
- Publisher
- Wiley
- Published
- 2021-07-12
- Volume
- 36
- Issue
- 10
- Pages
- 5887-5958
- ISSN
- 0884-8173 (ISSN-L)
- 1098-111X
- OpenAlex
- W3185076117
- Cited by
- 1,057
- References
- 3
- FWCI
- 63.16
- Type
- journal article
- Language
- en
- Open access
- bronze
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- Abdollahzadeh, B., Soleimanian Gharehchopogh, F., & Mirjalili, S. (2021). Artificial gorilla troops optimizer: A new nature‐inspired metaheuristic algorithm for global optimization problems. International Journal of Intelligent Systems. https://doi.org/10.1002/int.22535
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