期刊
2019 IEEE CONGRESS ON EVOLUTIONARY COMPUTATION (CEC)
卷 -, 期 -, 页码 19-26出版社
IEEE
DOI: 10.1109/cec.2019.8789904
关键词
differential evolution; optimization; global optimum; accuracy
资金
- Slovenian Research Agency [P2-0041, P2-0069]
Real parameter optimization problems are often very complex and computationally expensive. We can find such problems in engineering and scientific applications. In this paper, a new algorithm is proposed to tackle the 100-Digit Challenge. There are 10 functions representing 10 optimization problems, and the goal is to compute each function's minimum value to 10 digits of accuracy. There is no limit on either time or the maximum number of function evaluations. The proposed algorithm is based on the self-adaptive differential evolution algorithm jDE. Our algorithm uses two populations and some other mechanisms when tackling the challenge. We provide the score for each function as required by the organizers of this challenge competition.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据