均衡优化算法的最新发展:其变体和应用
Rebika Rai1, Krishna Gopal Dhal2
1Department of Computer Applications, Sikkim University, Sikkim, India.
这篇评论探讨了平衡优化器 (EO),这是一个基于物理学的自然灵感算法. 它涵盖了EO的变化,优势,弱点和优化问题的应用,如图像分类.
科学领域:
- 计算智能是一种计算智能.
- 优化算法 优化算法
- 大自然启发的计算
背景情况:
- 自然启发的元启发算法是广泛使用的计算范式.
- 平衡优化器 (EO) 是一种基于物理的优化算法,其灵感来自动态源和流水模型.
研究的目的:
- 提供对平衡优化器 (EO) 和其变体的全面审查.
- 分析不同EO变体的优缺点.
- 确定EO的核心优化问题和应用领域.
主要方法:
- 系统的文献审查来自主要出版商的175篇研究文章.
- 分析EO的理论基础及其在各种修改中的适应.
- 检查EO在各种应用领域的性能.
主要成果:
- 识别了均衡优化器的许多变化和修改.
- 讨论了EO的优点和局限性及其对不同问题类型的变体.
- 在图像分类和调度问题等领域目录化EO的应用.
结论:
- 平衡优化器是一个公认的,适应性强的,以自然为灵感的算法.
- 了解EO的优点和弱点有助于研究人员选择合适的变体.
- 确定了EO的未来研究方向,以进一步提高其能力.
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