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A Sinh Cosh optimizer
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DOI：10.1016/j.knosys.2023.111081.png)
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Abstract
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Currently, meta-heuristic algorithms have been widely studied and applied, but balancing exploration and exploitation remains a challenge. In this study, a novel meta-heuristic algorithm named Sinh Cosh Optimizer (SCHO) is proposed based on the mathematical inspiration of the characteristics of Sinh and Cosh. SCHO includes four steps: two different phases of exploration and exploitation, the bounded search strategy, and the switching mechanism. SCHO is compared with eight meta-heuristic algorithms for the 23 benchmark functions at different dimensions and CEC 2014, and its strong performance is validated. The efficiency and robustness of SCHO are verified by qualitative analysis, convergence curves, and two statistical tests. Furthermore, five engineering problems are presented. Source codes of SCHO are publicly available at https://www.mathworks.com/matlabce ntral/fileexchange/130734-a-sinh-cosh-optimizer.
Keywords:
Meta-heuristic
Sinh Cosh Optimizer (SCHO)
Mathematical inspiration
Benchmark function
Engineering design problems
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