Generalised opposition-based differential evolution: an experimental study

被引：12

作者：

Wang, Hui ^{[1
]}

Rahnamayan, Shahryar ^{[2
]}

Zeng, Sanyou ^{[3
]}

机构：

[1] Nanchang Inst Technol, Sch Informat Engn, Nanchang 330099, Jiangxi, Peoples R China

[2] UOIT, Fac Engn & Appl Sci, Oshawa, ON L1H 7K4, Canada

[3] China Univ Geosci, Sch Comp Sci, Wuhan 430074, Hubei, Peoples R China

来源：

INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY | 2012年 / 43卷 / 04期

关键词：

differential evolution; DE; generalised opposition-based learning; OBL; diversity; global optimisation;

D O I：

10.1504/IJCAT.2012.047155

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

This paper presents an experimental study of generalised opposition-based differential evolution (GODE). A comprehensive set of experiments on 13 benchmark functions is conducted, including opposite points versus random points, diversity analysis, and comparisons of GODE with four other recent variants of differential evolution (DE). Experimental results show that GODE obtains better performance when compared with other involved algorithms.

引用

页码：311 / 319

页数：9

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