一个多策略的改进秘书鸟优化算法工程优化问题
Song Qin1, Junling Liu2, Xiaobo Bai1
1School of Art and Design, Xi'an University of Technology, Xi'an 710054, China.
Biomimetics (Basel, Switzerland)
|August 28, 2024
概括
一个新的多策略改进的秘书鸟优化算法 (MISBOA) 提高了工程优化的准确性和速度. 这种先进的算法在基准和现实世界问题上表现出卓越的性能,提高了效率.
科学领域:
- 计算智能是一种计算智能.
- 优化算法 优化算法
- 工程应用 工程应用
背景情况:
- 工程优化问题往往需要高精度和快速融合的算法.
- 现有的元启发算法,如秘书鸟优化算法 (SBOA),在复杂的问题解决上可能存在局限性.
- 增强人口多样性和搜索策略对于强大的优化性能至关重要.
研究的目的:
- 为了开发一个改进的优化算法,多策略改进的秘书鸟优化算法 (MISBOA).
- 为了提高SBOA的解决准确性和融合速度,用于工程优化任务.
- 在标准测试套件和现实工程问题上验证MISBOA的有效性.
主要方法:
- 整合一个反调节机制,使用增量 PID 控制来进行人口更新.
- 在狩猎阶段实施金色正弦导向策略,以提高捕获成功率.
- 在逃生阶段引入合作伪装和基于共因相似性的更新策略,以保持人口多样性.
主要成果:
- 在CCE2022测试套件上,MISBOA在第10和第20个维度上表现出卓越的综合性能.
- 在12个测试函数中,MISBOA在10个测试函数中 (83.33%) 获得了第一名,因为维度增加了,突出了改进的可扩展性.
- 该算法在5个现实世界优化问题的适应性值中表现出最佳性能,这表明精度和稳定性得到了增强.
结论:
- 综合改进策略显著提高了MISBOA的搜索准确性和稳定性.
- MISBOA为解决复杂的工程优化挑战提供了强大而高效的方法.
- 应用到综合四分法概括的Ball插值曲线优化导致更光滑的设计和更好的发电效率.
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