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Article type: Research Article
Authors: Li, Xu-Dong | Wang, Jie-Sheng; * | Hao, Wen-Kuo | Song, Hao-Ming | Zhao, Xiao-Rui
Affiliations: School of Electronic and Information Engineering, University of Science and Technology Liaoning, Anshan, China
Correspondence: [*] Corresponding author. Jie-Sheng Wang, School of Electronic and Information Engineering, University of Science and Technology Liaoning, Anshan 114051, China. Tel.: +86 0412 2538355; E-mail: [email protected].
Abstract: With the increasing complexity and difficulty of numerical optimization problems in the real world, many efficient meta-heuristic optimization methods have been proposed to solve these problems. The arithmetic optimization algorithm (AOA) design is inspired by the distribution behavior of the main arithmetic operators in mathematics, including multiplication (M), division (D), subtraction (S) and addition (A). In order to improve the global search ability and local development ability of the AOA, the Lorentz triangle search variable step coefficient was proposed based on the broad-spectrum trigonometric functions combined with the Lorentz chaotic mapping strategy, which include a total of 24 search functions in four categories, such as regular trigonometric functions, inverse trigonometric functions, hyperbolic trigonometric functions, and inverse hyperbolic trigonometric functions. The position update was used to improve the convergence speed and accuracy of the algorithm. Through test experiments on benchmark functions and comparison with other well-known meta-heuristic algorithms, the superiority of the proposed improved AOA was proved.
Keywords: Arithmetic optimization algorithm, trigonometric function, function optimization
DOI: 10.3233/JIFS-221098
Journal: Journal of Intelligent & Fuzzy Systems, vol. 44, no. 3, pp. 3527-3559, 2023
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