A hybrid Aquila Optimizer sine cosine Algorithm for Numerical Optimization
Authors: 
Fei Chu, Jiayang Wang, Fulin TianAuthors Info & Claims
Fei Chu, Jiayang Wang, Fulin TianAuthors Info & ClaimsAbstract
To address the shortcomings of the Aquila optimizer algorithm (AO), this paper proposes a novel hybrid Aquila Optimizer sine cosine Algorithm(AO-SCA). Firstly, Singer chaotic mapping is used for initialization, so that the initial solution position distribution was more homogeneous, and increased the richness of the population. Secondly, in the exploration phase of AO, the concept of sine and cosine algorithm is integrated and the nonlinear sine learning factor is introduced to balance the local and global digging ability and accelerate the convergence speed. Finally, through the numerical experiment simulation of 8 benchmark functions, the results show that the optimization ability and convergence speed of the proposed algorithm is better.
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- A hybrid Aquila Optimizer sine cosine Algorithm for Numerical Optimization
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Published In
March 2023
598 pages
ISBN:9781450399449
DOI:10.1145/3590003
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Association for Computing Machinery
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Published: 29 May 2023
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CACML 2023
CACML 2023: 2023 2nd Asia Conference on Algorithms, Computing and Machine Learning
March 17 - 19, 2023
Shanghai, China
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CACML '23 Paper Acceptance Rate 93 of 241 submissions, 39%;
Overall Acceptance Rate 93 of 241 submissions, 39%
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