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A new meta-heuristic algorithm of giant trevally for solving engineering problems | ||
| Journal of Algorithms and Computation | ||
| دوره 55، شماره 1، شهریور 2023، صفحه 37-51 اصل مقاله (979.72 K) | ||
| نوع مقاله: Research Paper | ||
| شناسه دیجیتال (DOI): 10.22059/jac.2023.92495 | ||
| نویسنده | ||
| Marjan Aliyari* | ||
| Department of Mathematics of Ayatollah Borujerdi University, Borujerd, Iran | ||
| چکیده | ||
| As science and technology is progressing in engineering problems are also getting much more complex. So, solving these problems is of pivotal concern. Besides, the optimal solution among the solutions is of great value. Among them, innovative algorithms inspired by artificial intelligence or the hunting behavior of animals in nature have a special place. In this article, a new algorithm named Giant Trevally Optimizer (GTO) is presented, by simulating the hunting strategy of this type of fish, a novel algorithm with the same title is introduced, which has been examined, and subjected to various tests and criteria. In the performance studies of the GTO algorithm with several efficient meta-heuristic algorithms to find the global optimal solution, fifteen criterion functions having various features along with two hard problems in engineering design were used. The performance of the GTO algorithm has been better than other algorithms. | ||
| کلیدواژه‌ها | ||
| Swarm intelligence algorithm؛ Exploration؛ Exploitation؛ engineering problems | ||
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آمار تعداد مشاهده مقاله: 190 تعداد دریافت فایل اصل مقاله: 162 |
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