A Multi-Strategy Improved Arithmetic Optimization Algorithm

To improve the performance of the arithmetic optimization algorithm (AOA) and solve problems in the AOA, a novel improved AOA using a multi-strategy approach is proposed. Firstly, circle chaotic mapping is used to increase the diversity of the population. Secondly, a math optimizer accelerated (MOA)...

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Vydáno v:Symmetry (Basel) Ročník 14; číslo 5; s. 1011
Hlavní autoři: Liu, Zhilei, Li, Mingying, Pang, Guibing, Song, Hongxiang, Yu, Qi, Zhang, Hui
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 01.05.2022
Témata:
Accuracy
Algorithms
Arithmetic
Convergence
Cycloids
Exploitation
Monkeys & apes
Mutation
Optimization
Optimization algorithms
Performance enhancement
Population
Process controls
Water waves
ISSN:2073-8994, 2073-8994
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Shrnutí:To improve the performance of the arithmetic optimization algorithm (AOA) and solve problems in the AOA, a novel improved AOA using a multi-strategy approach is proposed. Firstly, circle chaotic mapping is used to increase the diversity of the population. Secondly, a math optimizer accelerated (MOA) function optimized by means of a composite cycloid is proposed to improve the convergence speed of the algorithm. Meanwhile, the symmetry of the composite cycloid is used to balance the global search ability in the early and late iterations. Thirdly, an optimal mutation strategy combining the sparrow elite mutation approach and Cauchy disturbances is used to increase the ability of individuals to jump out of the local optimal. The Rastrigin function is selected as the reference test function to analyze the effectiveness of the improved strategy. Twenty benchmark test functions, algorithm time complexity, the Wilcoxon rank-sum test, and the CEC2019 test set are selected to test the overall performance of the improved algorithm, and the results are then compared with those of other algorithms. The test results show that the improved algorithm has obvious advantages in terms of both its global search ability and convergence speed. Finally, the improved algorithm is applied to an engineering example to further verify its practicability.
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ISSN:2073-8994
2073-8994
DOI:10.3390/sym14051011