An improved arithmetic optimization algorithm with hybrid elite pool strategies

This paper presents an improved arithmetic optimization algorithm that incorporates hybrid elite pool strategies to address the limitations of the arithmetic optimization algorithm (AOA). In AOA, the linear mathematical optimization acceleration (MOA) function cannot balance global exploitation and...

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Vydáno v:Soft computing (Berlin, Germany) Ročník 28; číslo 2; s. 1127 - 1155
Hlavní autoři: Liu, Haiyang, Zhang, Xingong, Zhang, Hanxiao, Cao, Zhong, Chen, Zhaohui
Médium: Journal Article
Jazyk:angličtina
Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.01.2024
Témata:
Artificial Intelligence
Computational Intelligence
Control
Engineering
Mathematical Logic and Foundations
Mechatronics
Optimization
Robotics
Arithmetic optimization algorithm (AOA)
Mathematical optimization acceleration (MOA) function
Hybrid elite pool strategy
Meta-heuristic algorithms
ISSN:1432-7643, 1433-7479
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Shrnutí:This paper presents an improved arithmetic optimization algorithm that incorporates hybrid elite pool strategies to address the limitations of the arithmetic optimization algorithm (AOA). In AOA, the linear mathematical optimization acceleration (MOA) function cannot balance global exploitation and local exploration well. Therefore, the accuracy and convergence speed of the algorithm cannot be guaranteed. To improve the performance of AOA, this paper reconstructed a nonlinear MOA function, which is expected to balance the exploitation and the exploration of AOA. Furthermore, four hybrid elite pool strategies are integrated to enhance the ability to escape local optima. The proposed algorithm inherits the fast convergence of AOA and develops the performance of escaping local optima. Numerical experiment results on benchmark functions and engineering problems show that the proposed algorithm outperforms other compared meta-heuristic algorithms in terms of convergence speed and accuracy.
ISSN:1432-7643
1433-7479
DOI:10.1007/s00500-023-09153-1