博诺博优化器:一个新的工具,用于全球优化小原子集群
Bhrigu Chakraborty1, Ranita Pal2, Dilip Kumar Pratihar3
1Department of Chemistry, Indian Institute of Technology Kharagpur, Kharagpur 721302, India.
The journal of physical chemistry. A
|May 2, 2024
概括
我们介绍了Bonobo优化器 (BO),这是一个新的元启发算法,用于在化学系统中找到全球最小能量结构. 这个优化器表现出卓越的效率和稳定性,特别是在原子集群优化方面.
科学领域:
- 计算化学的计算化学
- 材料科学 材料科学 材料科学
- 化学物理 化学物理
背景情况:
- 确定全球最低能量配置对于理解化学系统至关重要.
- 随着系统规模和复杂性的增加,结构和结合性调查面临重大挑战.
- 超启发式算法为化学中的复杂优化问题提供了潜在的解决方案.
研究的目的:
- 介绍和评估Bonobo优化器 (BO),一种新的元启发算法,用于化学结构和结合调查.
- 评估BO在寻找全球最低能耗配置方面的性能,稳定性和效率.
- 将BO的应用扩展到对原子集群的优化.
主要方法:
- 开发和应用博诺博优化器 (BO),灵感来自博诺博的社会和生殖行为.
- 对BO在小型碳集群上的表现进行系统评估.
- 参数研究来评估算法的适应性和趋同.
- 对现有的全球优化算法进行统计验证和比较分析.
主要成果:
- 波诺波优化器 (BO) 始终趋向于小型碳集群的全球最小结构.
- 参数研究证实了算法的适应性和稳定性.
- 对比分析显示,BO的效率优于已有的全球优化算法.
- 严格的统计验证证实了观察到的性能.
结论:
- 波诺波优化器 (BO) 是一种强大而高效的元启发算法,用于解决复杂的化学优化问题.
- 对于优化原子集群,BO显示出显著的前景,推进了计算化学.
- 这项研究验证了BO作为一个有价值的工具,用于阐明化学系统中的全球最小能量配置.
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