融合多策略改进的黑翅鸢优化算法
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作者单位:

华北理工大学电气工程学院 唐山 063210

中图分类号:

TP301.6;TN2

基金项目:

河北省自然科学基金(F2018209201)项目资助


Black-winged kite optimization algorithm with multi-strategy improvement
Author:
Affiliation:

School of Electrical Engineering, North China University of Science and Technology,Tangshan 063210, China

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    摘要:

    针对基本黑翅鸢算法(BKA)收敛速度慢,易陷入局部最优等问题,提出了一种融合多策略改进的黑翅鸢算法(EBKA)。首先引入了追踪猎物位置更新策略,提高算法全局搜索能力,加快收敛速度。其次在攻击阶段提出自适应t螺旋策略,防止算法陷入局部最优。最后在迁移阶段,当黑翅鸢领导者失去领导作用时,提出了Levy切线飞行策略,避免算法早熟收敛。为了验证算法的改进效果,选取8种测试函数进行测试,并与5种群智能算法进行对比。实验结果表明:EBKA与其他群智能算法对比,在单峰函数上均能快速寻到理论最优值0,在多峰函数F5、F6、F8中30次左右就能收敛到最优值,并且F6、F7可以收敛到理论最优值0。证明了EBKA具有很好的收敛性能、稳定性和全局寻优能力。

    Abstract:

    In order to solve the problems of slow convergence speed of the basic black-winged kite algorithm (BKA) and easy to fall into local optimum, an enhanced black-winged kite algorithm (EBKA) with multi-strategy improvement was proposed. Firstly, the tracking prey location update strategy is introduced to improve the global search ability of the algorithm and accelerate the convergence speed. Secondly, an adaptive t-helix strategy is proposed in the attack stage to prevent the algorithm from falling into local optimum. Finally, in the migration stage, when the leader of the black-winged kite loses its leadership role, the Levy tangent flight strategy is proposed to avoid the premature convergence of the algorithm. In order to verify the improvement effect of the algorithm, 8 test functions were selected for testing and compared with 5 swarm intelligence algorithms. Experimental results show that compared with other swarm intelligence algorithms, EBKA can quickly find the theoretical optimal value of 0 on the single-peak function, converge to the optimal value in about 30 times in the multimodal function F5、F6 and F8, and converge to the theoretical optimal value of 0 in the F6 and F7. It is proved that EBKA has good convergence performance, stability and global optimization ability.

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引用本文

周建新,侯自川,李忠泽.融合多策略改进的黑翅鸢优化算法[J].电子测量技术,2024,47(22):104-110

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  • 在线发布日期: 2025-01-16
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