先进的粘液模具算法结合了差异进化和威尔机制,用于工程设计.
Xinru Li1, Zihan Lin1, Haoxuan Lv1
1Key Laboratory of Intelligent Informatics for Safety & Emergency of Zhejiang Province, Wenzhou University, Wenzhou 325035, China.
iScience
|October 9, 2023
概括
本研究介绍了PSMADE,这是一个改进的粘液模具算法 (SMA),通过整合差异演化和威尔机制来提高优化速度和解决方案质量. 在复杂的工程问题上,PSMADE表现出卓越的性能.
科学领域:
- 计算智能是一种计算智能.
- 群集情报 群集情报 群集情报
- 优化算法 优化算法
背景情况:
- 粘菌算法 (SMA) 是一种基于人口的群体智能算法,其灵感来源于粘菌的食行为.
- SMA 存在缓慢的收和过早的收,这限制了它在复杂的优化任务中的有效性.
研究的目的:
- 提出一个改进的粘液模具算法,称为PSMADE,以解决原始SMA的局限性.
- 增强粘液模具算法的全球和本地搜索能力.
主要方法:
- PSMADE集成了差异进化 (DE) 算法的交叉和突变操作,以改善个体多样性和全球搜索.
- 纳入了带有禁忌表的威尔机制,以加强本地搜索和加速融合.
- 使用CEC 2014基准函数和四个现实世界受约束的工程问题来评估性能.
主要成果:
- 与14个元启发算法和15个改进的元启发算法相比,PSMADE表现显著提高了性能.
- 实验结果证实,PSMADE有效地克服了原始SMA的缓慢收和过早收问题.
- 拟议的算法在解决复杂的优化问题方面表现出色.
结论:
- PSMADE为粘液模具算法提供了一个强大的和有效的增强.
- 集成DE和威尔机制提供了一种强大的方法来改善群集智能优化.
- 作为解决复杂的现实世界工程问题的一种有价值的工具,PSMADE显示出巨大的潜力.
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