混沌增强的领导粘液模具算法用于具有频率约束的圆顶结构
Arnut Sutha1, Sawekchai Tangaramvong2, Wei Gao3
1Center of Excellence in Applied Mechanics and Structures, Department of Civil Engineering, Chulalongkorn University, Bangkok, 10330, Thailand.
Scientific reports
|August 24, 2025
概括
混沌增强的领导粘液模具算法 (CELSMA) 提高了高维工程优化. 这种新的方法增强了探索和利用,导致了更高的准确性和更快的融合.
科学领域:
- 工程优化
- 计算智能
- 生物启发的算法
背景情况:
- 传统的优化算法难以处理高维度的工程问题.
- 粘算法 (SMA) 提供了一个生物灵感的方法,但可以改进.
- 过早的融合和有限的勘探/开发是常见的挑战.
研究的目的:
- 介绍混沌增强的领导模算法 (CELSMA) 进行复杂的工程优化.
- 增强传统SMA以外的勘探和开发能力.
- 改善全球搜索行为并缓解过早的融合.
主要方法:
- CELSMA采用了三位候选领导人的多方领导策略.
- 包含混乱地图以利用 ergodic 和非重复性搜索属性.
- 应用最大特征矩阵 (LESM) 技术来加快托架结构的特征值计算.
主要成果:
- 在大型圆顶结构上,CELSMA-LESM表现出卓越的准确性和融合速度.
- 与基准相比,该算法在较少的代中始终实现最佳解决方案.
- 由于LESM技术,计算时间显著减少.
结论:
- CELSMA是一个先进的生物灵感优化技术,
- 混沌地图和多领导者策略的整合提高了优化性能.
- CELSMA-LESM方法提供了一个计算效率高和有效的解决方案来优化架结构.
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