一个可变步骤群众搜索算法及其在函数问题中的应用
Yuqi Fan1, Huimin Yang1, Yaping Wang1
1Key Laboratory of Advanced Manufacturing and Intelligent Technology, Ministry of Education, School of Mechanical and Power Engineering, Harbin University of Science and Technology, Harbin 150080, China.
Biomimetics (Basel, Switzerland)
|September 27, 2023
概括
可变步骤群搜索算法 (VSCSA) 通过使用等号函数来提高搜索能力和速度来提高优化. 这种新的方法促进了人口的多样性和全球寻求更高准确性的全球搜索.
科学领域:
- 计算智能是一种计算智能.
- 超启发式优化优化
- 群集情报 群集情报 群集情报
背景情况:
- 优化算法对于解决各种领域的复杂问题至关重要.
- 乌搜索算法 (CSA) 是一种由乌行为启发的高效元启发.
- 一个CSA的局限性是它的固定飞行长度,可能导致局部最佳.
研究的目的:
- 介绍一个新的优化算法,变量步骤群众搜索算法 (VSCSA).
- 在标准的Crow搜索算法中解决局部最佳问题.
- 提高CSA的性能,融合速度和全球搜索能力.
主要方法:
- 拟议的VSCSA修改了Crow搜索算法,通过整合一个可变的步骤大小.
- 使用一个等号函数来动态调整搜索步骤长度.
- 人口多样性和全球搜索能力通过特定的更新机制得到增强.
主要成果:
- 在14个测试函数,2017年的CEC函数和工程问题上,VSCSA表现出卓越的性能.
- 实验结果显示,适应性值,融合速度和解决方案质量显著改善.
- 统计测试和搜索路径分析证实了VSCSA增强的全球搜索能力和准确性.
结论:
- 可变步骤群众搜索算法 (VSCSA) 有效地克服了标准CSA的局限性.
- VSCSA提供了增强的人口多样性,更快的融合,以及改进的全球搜索能力.
- 拟议的算法在解决复杂的优化问题方面表现出强大的竞争力和优势.
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