参数优化的进化算法 - - 30年后
Thomas H W Bäck1, Anna V Kononova2, Bas van Stein3
1Leiden Institute of Advanced Computer Science, Leiden University, Netherlands t.h.w.baeck@liacs.leidenuniv.nl.
Evolutionary computation
|June 20, 2023
概括
这篇综述强调了30年来对参数优化的进化算法,强调需要更少,精确的基准算法和自动化设计,而不是新的,以自然为灵感的方法.
科学领域:
- 计算机科学 计算机科学
- 人工智能的人工智能
- 优化优化 优化优化
背景情况:
- 进化算法在过去30年 (1993-2023) 中显著提升了参数优化.
- 关键的发展包括共变矩阵适应演变战略,多式联络,代理辅助和多目标优化.
- 新兴的算法,如粒子群优化和差异进化也获得了突出地位.
研究的目的:
- 从1993年到2023年,审查参数优化进化算法的重大发展.
- 批判性地评估目前提出众多新算法的趋势.
- 倡导改善基准测试和自动化算法设计.
主要方法:
- 关于进化算法及其在参数优化中的应用的文献综述.
- 分析算法开发和基准分析实践的趋势.
- 讨论自动化算法设计框架.
主要成果:
- 在多式联运,代理辅助和多目标优化等专业领域取得了显著进展.
- 新算法的扩散往往缺乏严格的验证.
- 自动化算法设计呈现出一个有前途的未来方向.
结论:
- 需要整合研究工作,专注于更少,更强大的算法.
- 严格的基准测试对于评估新优化算法的实用性至关重要.
- 自动化算法设计为开发更系统,更有效的优化工具提供了一条道路.
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