Hybridized improvement of the chaotic Harris Hawk optimization algorithm and Aquila Optimizer

Yu-Jun Zhang; Juan Zhao; Zheng-Ming Gao

doi:10.1117/12.2634395

4 May 2022 Hybridized improvement of the chaotic Harris Hawk optimization algorithm and Aquila Optimizer

Yu-Jun Zhang, Juan Zhao, Zheng-Ming Gao

Proceedings Volume 12172, International Conference on Electronic Information Engineering and Computer Communication (EIECC 2021); 121721F (2022) https://doi.org/10.1117/12.2634395
Event: International Conference on Electronic Information Engineering and Computer Communication (EIECC 2021), 2021, Nanchang, China

Abstract

In the improvement of many meta-heuristic algorithms, two or more algorithms are often mixed into one algorithm to improve the convergence speed and accuracy of the algorithm. The search ability of Harris Hawk optimization (HHO) algorithm ^[1] is relatively weak, and the search ability of Aquila Optimizer (AO) is relatively strong. So, in this article, the Aquila Optimizer (AO) algorithm is mixed on the basis of the piecewise linear map enabled Harris Hawk optimization (HHO) algorithm, and the advantages of the AO algorithm are used to complement the disadvantages of the piecewise linear map enabled HHO algorithm. This hybrid algorithm is called CHHOAO. The results show that this hybrid improvement is effective and can significantly improve the optimization ability of the algorithm.

Citation Download Citation

Yu-Jun Zhang, Juan Zhao, and Zheng-Ming Gao "Hybridized improvement of the chaotic Harris Hawk optimization algorithm and Aquila Optimizer", Proc. SPIE 12172, International Conference on Electronic Information Engineering and Computer Communication (EIECC 2021), 121721F (4 May 2022); https://doi.org/10.1117/12.2634395

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KEYWORDS

Algorithm development

Optimization (mathematics)

Adaptive optics

Computer simulations

Detection and tracking algorithms

Electronics

Electronics engineering

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