LSWOA:用于数值和工程设计优化问题的增强鱼优化算法
Junhao Wei1, Yanzhao Gu1, Zhanxi Xie2
1Faculty of Applied Sciences, Macao Polytechnic University, Macao, China.
PloS one
|September 3, 2025
概括
提升的鱼优化算法 (LSWOA) 通过解决过早的融合和增强探索来改进原始算法. 这种新的方法在基准和工程优化任务中表现出卓越的表现.
科学领域:
- 计算智能
- 超听觉优化
- 算法增强
背景情况:
- 鱼优化算法 (WOA) 面临的局限性包括过早的融合,人口多样性的减少,缓慢的融合率和不高的准确性.
- 勘探和开采阶段之间的显著不平衡阻碍了WOA在复杂的优化问题上的有效性.
研究的目的:
- 引入一种新的增强型鱼优化算法 (LSWOA),旨在克服传统的WOA固有的局限性.
- 提高WOA的整体优化性能,融合速度和准确性.
主要方法:
- 实现了良好的节点集初始化,以获得更高质量的搜索基线.
- 引入基于距离的指导搜索策略以增强当地最佳逃生能力.
- 开发了一种增强的螺旋更新策略,具有动态参数调整,以平衡勘探和开采.
主要成果:
- 与其他元启发算法和WOA变体相比,LSWOA在各种维度基准函数中表现出优异的优化性能.
- 该算法在七个工程设计优化问题上取得了出色的结果,展示了其在现实应用中的有效性.
- LSWOA 显示了更好的融合速度和准确性,有效地解决了复杂的高维优化挑战.
结论:
- 拟议的LSWOA有效地减轻了标准WOA的弱点,提供了一个更强大,更有效的优化工具.
- 由于其强大的性能和适应性,LSWOA在现实世界的工程挑战中具有显著的应用潜力.
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