黑翅鸢与鹗融合的启发式优化算法及其工程应用

IF 3.4 3区 医学 Q1 ENGINEERING, MULTIDISCIPLINARY Biomimetics Pub Date : 2024-10-01 DOI:10.3390/biomimetics9100595
Zheng Zhang, Xiangkun Wang, Yinggao Yue
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引用次数: 0

摘要

近年来,作为多目标优化问题的一种解决方案,群智能优化方法逐渐受到人们的青睐。由于多目标优化问题具有高维目标空间,因此对它们的研究受到了广泛关注。黑翅风筝优化算法虽然结合了考奇突变来增强算法的优化能力,但仍然存在全局搜索和局部开发能力不平衡的问题,容易出现局部优化。为了提高黑翅风筝算法(BKA)的搜索能力,提出了黑翅风筝融合鱼鹰的启发式优化算法(OCBKA),该算法通过逻辑混沌映射初始化种群,并融合鱼鹰优化算法来提高算法的搜索性能。通过对 CEC2005 和 CEC2021 基准函数以及其他群智能优化方法和三个工程优化问题的解进行数值比较,证实了升级策略的有效性。根据数值实验结果,改进后的 OCBKA 具有很强的竞争力,因为与其他同类算法相比,它能以较高的收敛精度和较快的收敛时间处理复杂的工程优化问题。
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Heuristic Optimization Algorithm of Black-Winged Kite Fused with Osprey and Its Engineering Application.

Swarm intelligence optimization methods have steadily gained popularity as a solution to multi-objective optimization issues in recent years. Their study has garnered a lot of attention since multi-objective optimization problems have a hard high-dimensional goal space. The black-winged kite optimization algorithm still suffers from the imbalance between global search and local development capabilities, and it is prone to local optimization even though it combines Cauchy mutation to enhance the algorithm's optimization ability. The heuristic optimization algorithm of the black-winged kite fused with osprey (OCBKA), which initializes the population by logistic chaotic mapping and fuses the osprey optimization algorithm to improve the search performance of the algorithm, is proposed as a means of enhancing the search ability of the black-winged kite algorithm (BKA). By using numerical comparisons between the CEC2005 and CEC2021 benchmark functions, along with other swarm intelligence optimization methods and the solutions to three engineering optimization problems, the upgraded strategy's efficacy is confirmed. Based on numerical experiment findings, the revised OCBKA is very competitive because it can handle complicated engineering optimization problems with a high convergence accuracy and quick convergence time when compared to other comparable algorithms.

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来源期刊
Biomimetics
Biomimetics Biochemistry, Genetics and Molecular Biology-Biotechnology
CiteScore
3.50
自引率
11.10%
发文量
189
审稿时长
11 weeks
期刊最新文献
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