Sea-horse optimizer

version 3.0.0 (6.53 KB) by S. Zhao
Sea-horse optimizer: A novel nature-inspired meta-heuristic for global optimization problems

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Updated Sat, 15 Oct 2022 12:48:18 +0000

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This paper proposes a novel swarm intelligence-based metaheuristic called as sea-horse optimizer (SHO), which is inspired by the movement, predation and breeding behaviors of sea horses in nature. The performance of SHO is evaluated on 23 well-known functions and CEC2014 benchmark functions compared with six state-of-the-art metaheuristic algorithms. Five real-world engineering problems are utilized to test the effectiveness of SHO. The experimental results demonstrate that SHO is a high-performance optimizer and positive adaptability to deal with constraint problems.
Cite this paper as: Zhao S., Zhang T., Ma S., Wang M. (2022) Sea-horse optimizer: A novel nature-inspired meta-heuristic for global optimization problems, Applied Intelligence, 1-28. DOI: https://doi.org/10.1007/s10489-022-03994-3

Cite As

Zhao, Shijie, et al. “Sea-Horse Optimizer: a Novel Nature-Inspired Meta-Heuristic for Global Optimization Problems.” Applied Intelligence, Springer Science and Business Media LLC, Sept. 2022, doi:10.1007/s10489-022-03994-3.

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