An Adaptive Spiral Strategy Dung Beetle Optimization Algorithm: Research and Applications

文献类型： 外文期刊

第一作者： Wang, Xiong

作者： Wang, Xiong;Zhang, Yi;Zheng, Changbo;Feng, Shuwan;Yu, Hui;Hu, Bin;Xie, Zihan

作者机构：

关键词： swarm intelligence; optimization algorithm; engineering design; adaptive strategy; unmanned aerial vehicles

期刊名称：BIOMIMETICS （ 影响因子：3.9； 五年影响因子：4.0 ）

ISSN：

年卷期： 2024 年 9 卷 9 期

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收录情况： SCI

摘要： The Dung Beetle Optimization (DBO) algorithm, a well-established swarm intelligence technique, has shown considerable promise in solving complex engineering design challenges. However, it is hampered by limitations such as suboptimal population initialization, sluggish search speeds, and restricted global exploration capabilities. To overcome these shortcomings, we propose an enhanced version termed Adaptive Spiral Strategy Dung Beetle Optimization (ADBO). Key enhancements include the application of the Gaussian Chaos strategy for a more effective population initialization, the integration of the Whale Spiral Search Strategy inspired by the Whale Optimization Algorithm, and the introduction of an adaptive weight factor to improve search efficiency and enhance global exploration capabilities. These improvements collectively elevate the performance of the DBO algorithm, significantly enhancing its ability to address intricate real-world problems. We evaluate the ADBO algorithm against a suite of benchmark algorithms using the CEC2017 test functions, demonstrating its superiority. Furthermore, we validate its effectiveness through applications in diverse engineering domains such as robot manipulator design, triangular linkage problems, and unmanned aerial vehicle (UAV) path planning, highlighting its impact on improving UAV safety and energy efficiency.

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