一个新的鹿旋风优化算法 (RCOA)
Gopal Chaudhary1, Bharat S Rawal2
1School of Engineering & Technology, Vivekananda Institute of Professional Studies - Technical Campus, Delhi, India. gopal.chaudhary88@gmail.com.
Scientific reports
|April 11, 2025
概括
鹿旋风优化算法 (RCOA),灵感来自鹿的行为,为复杂的优化问题提供了更高的准确性和稳定性. 这种新的元启发学平衡了探索和利用,以获得卓越的性能.
科学领域:
- 计算智能是一种计算智能.
- 优化算法 优化算法
- 超听证学是一种超听证学.
背景情况:
- 优化问题需要高效的算法来平衡勘探和开发.
- 现有的算法如PSO,DE,COA,GSA和WDO在性能和稳定性方面存在局限性.
- 受自然启发的算法为应对这些挑战提供了有希望的方法.
研究的目的:
- 介绍了新的鹿旋风优化算法 (RCOA).
- 评估RCOA在基准函数和现实世界问题上与已建立的算法对比的性能.
- 在准确性,融合速度和稳定性方面证明RCOA的有效性.
主要方法:
- 根据鹿在掠食者攻击期间的生存行为开发了RCOA.
- 在14个单模/多模基准函数和4个现实问题上测试了RCOA.
- 使用CEC'17基准套件 (50个维度) 对PSO,DE,COA,GSA,WDO和WOA进行RCOA比较.
主要成果:
- 在单模功能上,RCOA显示了比PSO,DE,COA,GSA提高5-12%.
- 在多式联网功能上,RCOA在准确性和一致性方面比WDO和PSO提高了10-15%.
- RCOA实现了卓越的融合速度和解决方案精度,在多个测试功能上表现优于现有方法.
结论:
- RCOA是一种强大可靠的优化方法.
- 通过威尔科克森签名-等级测试证实了统计学意义.
- RCOA适用于各种现实世界的优化应用.
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