Department of Mathematics of Ayatollah Borujerdi University, Borujerd, Iran
10.22059/jac.2023.92495
Abstract
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.
Aliyari, M. (2023). A new meta-heuristic algorithm of giant trevally for solving engineering problems. Journal of Algorithms and Computation, 55(1), 37-51. doi: 10.22059/jac.2023.92495
MLA
Marjan Aliyari. "A new meta-heuristic algorithm of giant trevally for solving engineering problems". Journal of Algorithms and Computation, 55, 1, 2023, 37-51. doi: 10.22059/jac.2023.92495
HARVARD
Aliyari, M. (2023). 'A new meta-heuristic algorithm of giant trevally for solving engineering problems', Journal of Algorithms and Computation, 55(1), pp. 37-51. doi: 10.22059/jac.2023.92495
VANCOUVER
Aliyari, M. A new meta-heuristic algorithm of giant trevally for solving engineering problems. Journal of Algorithms and Computation, 2023; 55(1): 37-51. doi: 10.22059/jac.2023.92495
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