A Sinh Cosh optimizer

被引：110

作者：

Bai, Jianfu ^{[1
]}

Li, Yifei ^{[1
]}

Zheng, Mingpo ^{[1
]}

Khatir, Samir ^{[1
]}

Benaissa, Brahim ^{[2
]}

Abualigah, Laith ^{[3
,4
,5
,6
]}

Wahab, Magd Abdel ^{[1
,7
]}

机构：

[1] Univ Ghent, Fac Engn & Architecture, Dept Elect Energy Met Mech Construct & Syst, Soete Lab, Ghent, Belgium

[2] Toyota Technol Inst, Design Engn Lab, Nagoya, Japan

[3] Lebanese Amer Univ, Dept Elect & Comp Engn, Byblos 135053, Lebanon

[4] Al Ahliyya Amman Univ, Hourani Ctr Appl Sci Res, Amman 19328, Jordan

[5] Middle East Univ, MEU Res Unit, Amman, Jordan

[6] Appl Sci private Univ, Appl Sci Res Ctr, Amman 11931, Jordan

[7] Yuan Ze Univ, Coll Engn, Taoyuan, Taiwan

来源：

KNOWLEDGE-BASED SYSTEMS | 2023年 / 282卷

关键词：

Meta-heuristic; Sinh Cosh Optimizer (SCHO); Mathematical inspiration; Benchmark function; Engineering design problems; ANT COLONY OPTIMIZATION; ALGORITHM; SEARCH; SWARM;

D O I：

10.1016/j.knosys.2023.111081

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

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.

引用

页数：29

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