LSEWOA:一个增强的鱼优化算法,用于数值和工程设计优化问题的多策略
Junhao Wei1, Yanzhao Gu1, Yuzheng Yan1
1Faculty of Applied Sciences, Macao Polytechnic University, Macao 999078, China.
Sensors (Basel, Switzerland)
|April 12, 2025
概括
增强的鱼优化算法 (LSEWOA) 通过解决过早的收和平衡探索来改进经典算法. 在优化任务和工程设计问题上,LSEWOA表现出卓越的性能.
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:
- 鱼优化算法 (WOA) 是一种以其简单性而闻名的生物灵感的元启发,但遭受过早的融合和勘探-开发失衡.
- 现有的WOA变种在以后的代中与人口多样性和融合精度作斗争.
研究的目的:
- 提出一个新的多策略增强的鱼优化算法 (LSEWOA).
- 解决经典WOA的局限性,包括过早的融合和不良的勘探-开发平衡.
主要方法:
- 引入了良好的节点,为统一的鱼分布设置初始化.
- 开发了一种领导者-追随者搜索猎物策略和基于螺旋的围绕猎物策略.
- 实施了增强的螺旋更新战略,并重新设计了趋同因子更新机制.
主要成果:
- 在CEC2005基准函数上,LSEWOA表现优异.
- 定量分析显示,LSEWOA在各个维度 (30,50,100) 中超过了最先进的算法.
- 对九个工程设计优化问题的成功应用验证了现实世界的适用性.
结论:
- 莱斯沃有效地克服了经典WOA的缺点.
- 拟议的改进显著提高了融合率,准确性和人口多样性.
- 对于复杂的优化挑战,LSEWOA提供了强大而高效的解决方案.
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