BFGS-GSO for Global Optimization Problems

被引：2

作者：

Ouyang, Aijia ^{[1
,2
]}

Liu, Libin ^{[3
]}

Yue, Guangxue ^{[4
]}

Zhou, Xu ^{[2
]}

Li, Kenli ^{[2
]}

机构：

[1] Hunan Sci & Technol Econ Trade Vocat Coll, Coll Comp, Hengyang, Hunan, Peoples R China

[2] Hunan Univ, Coll Informat Sci & Engn, Changsha 410082, Hunan, Peoples R China

[3] Univ Chizhou, Dept Math & Comp Sci, Chizhou 247000, Peoples R China

[4] Jiaxing Univ, Coll Math & Informat Engn, Jiaxing 314001, Peoples R China

来源：

JOURNAL OF COMPUTERS | 2014年 / 9卷 / 04期

基金：

中国国家自然科学基金;

关键词：

Global optimization; GSO; BFGS operator; BFGS-GSO; function;

D O I：

10.4304/jcp.9.4.966-973

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

To make glowworm swarm optimization (GSO) algorithm solve multi-extremum global optimization more effectively, taking into consideration the disadvantages and some unique advantages of GSO, the paper proposes a hybrid algorithm of Broyden-Fletcher-GoldfarbShanno (BFGS) algorithm and GSO, i.e., BFGS-GSO by adding BFGS local optimization operator in it, which can solve the problems effectively such as unsatisfying solving precision, and slow convergence speed in the later period. Through the simulation of eight standard test functions, the effectiveness of the algorithm is tested and improved. It proves that the improved BFGS-GSO abounds in better multi-extremum global optimization in comparison with the basic GSO.

引用

页码：966 / 973

页数：8

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