Differential Evolution Algorithm Based on Adaptive Rank Exponent and Parameters

被引：0

作者：

Mai, Weijie ^{[1
]}

Wei, Mingzhu ^{[1
]}

Shen, Fengshan ^{[1
]}

Yuan, Feng ^{[1
]}

机构：

[1] Guangzhou & Chinese Acad Sci, Inst Software Applicat Technol, Guangzhou, Peoples R China

来源：

COMPUTER SUPPORTED COOPERATIVE WORK AND SOCIAL COMPUTING, CHINESECSCW 2021, PT I | 2022年 / 1491卷

关键词：

Differential evolution algorithm; Adaptive rank exponent and parameters; Mutation strategy; OPTIMIZATION;

D O I：

10.1007/978-981-19-4546-5_18

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Differential evolution algorithm is a very useful and impactful method for handling global numerical optimization issue in the evolutionary algorithm family. However, there are still some shortcomings. Such as, the performance of DE is depend on its mutation strategy and parameters setting. In this article, we present a new fashione differential evolution algorithm which called AFP-DE with adaptive rank exponent and parameters. Compared with the update variant DE algorithms, the experiment shows that performance of AFP-DE is better than them with good performance.

引用

页码：217 / 229

页数：13

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