开发和评估混合哈里斯·霍克斯优化算法,用于先进的工程应用程序
Himanshu Sharma1, Jumi Bharali2, Manish Motghare1
1Department of Electrical Engineering, G.H. Raisoni College of Engineering and Management, Nagpur, Maharashtra, India.
Scientific reports
|December 3, 2025
概括
开发了七种新的哈里斯优化器 (HHO) 变体,以改善融合和利用. 这些混合算法在复杂的工程问题上明显优于标准HHO和其他优化器.
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:
- 标准的哈里斯·霍克优化器 (HHO) 算法虽然有效,但受到了缓慢的融合和有限的利用能力,特别是在高维和受限制的问题上.
- 现有的优化算法往往难以有效地平衡探索和利用,导致过早的融合或次优化解决方案.
研究的目的:
- 通过整合适应机制,混乱动态,精英保护和交叉算法杂交来开发哈里斯优化器 (HHO) 的七种新型变体.
- 提高HHO中勘探和开采之间的平衡,以提高复杂优化任务的性能.
- 在基准函数和工程设计问题上,评估拟议的HHO变体与最先进的优化器的有效性.
主要方法:
- 开发了七种HHO变种:HHO-ADAP,HHO-CHAOS,HHO-Elite,HHO-GA,HHO-Inertia,HHO-PSO,以及HHO-ULTRA. 这些变种的产品包括:
- 对CEC 2014基准套件进行了严格的测试,涉及第10,30,50和100个维度.
- 对十个受约束的工程设计问题进行评估,并与CMA-ES,L-SHADE和WMA等高级优化器进行比较.
主要成果:
- 混合型HHO变种始终优于基线HHO和经典优化器,表现出优越的融合速度和解决方案准确性.
- HHO-PSO和HHO-Elite实现了高达35%的更快收,并达到低至10−216.16的溶液值.
- 像HHO-Elite,HHO-CHAOS和HHO-ADAP这样的变种有效地延迟了停滞,并保留了多式联运功能上的多样性.
- 对于工程问题 (例如压力容器,弹,接梁) 实现了近乎最佳的设计,其差异较低,运行时间明显更快,与领先的算法相比.
结论:
- 混合化显著提高了哈里斯·霍克优化器的稳定性,解决方案准确性和适应性.
- 拟议的HHO变种对于解决大规模,非线性和受约束优化问题非常有效.
- 开发的算法为工程和科学领域的应用提供了有前途的进步,需要高效的优化.
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