.png){kind=icon}
返回
Cultured differential evolution for constrained optimization
.png){kind=icon}
PRE
AI
DOI：10.1016/j.cma.2005.09.006.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
A cultural algorithm with a differential evolution population is proposed in this paper. This cultural algorithm uses different knowledge sources to influence the variation operator of the differential evolution algorithm, in order to reduce the number of fitness function evaluations required to obtain competitive results. Comparisons are provided with respect to three techniques that are representative of the state-of-the-art in the area. The results obtained by our algorithm are similar (in quality) to those obtained by the other approaches with respect to which it was compared. However, our approach requires a lower number of fitness function evaluations than the others. (c) 2005 Elsevier B.V. All rights reserved.
Keyword:
evolutionary algorithms
optimization
differential evolution cultural algorithms
evolutionary optimization
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
7.3
论文数:
1.3W
被引数:
5.6W
机构
暂无机构信息
引用论文
.png){kind=icon}
查看更多内容