领地微分元进化:一种算法,用于寻找一个多变量函数的所有理想的最优值
Richard Wehr1,2, Scott R Saleska3
1Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ, 85721, U.S.A.
Evolutionary computation
|June 30, 2023
概括
领地微分元进化 (TDME) 是一种新的算法,可以有效地为复杂的函数找到最佳解决方案. 在各种问题上,TDME的性能优于现有的方法,而不需要对参数进行调整.
科学领域:
- 优化算法 优化算法
- 计算智能是一种计算智能.
- 进化计算是一种进化计算.
背景情况:
- 多模式优化问题存在重大挑战,因为多个最佳.
- 现有的算法经常与高维或复杂的景观作斗争.
- 希尔VallEA算法是标准基准套件的领先方法.
研究的目的:
- 介绍领土微分元进化 (TDME) 算法.
- 评估TDME的表现与已建立的算法比如HillVallEA.
- 证明TDME在标准和新基准问题上的有效性.
主要方法:
- 实施领土差异化元进化 (TDME) 算法.
- 使用渐进式化机制进行优化.
- 测试标准和新的基准函数,包括高维和多式问题.
主要成果:
- 在标准基准套件上,TDME的表现与HillVallEA相提并论.
- 在一个更全面,更多样化的基准指标套件上,TDME的表现明显优于HillVallEA.
- 在没有针对特定问题的参数调整的情况下,TDME 实现了卓越的结果.
结论:
- TDME是一个高效,多功能和可靠的算法,用于多模式优化.
- 与现有的最先进的方法相比,TDME提供了优势,特别是在各种问题场景中.
- 该算法的稳定性和缺乏参数调整使其具有广泛的适用性.
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