Improved gravitational search algorithm based on chaotic local search

CASIA OpenIR > 多模态人工智能系统全国重点实验室 > 人工智能与机器学习（杨雪冰）-技术团队

	Improved gravitational search algorithm based on chaotic local search
	Guo, Zhaolu 1,2; Zhang, Wensheng2 ; Wang, Shenwen 3
发表期刊	INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION
ISSN	1758-0366
	2021
卷号	17 期号:3 页码:154-164
通讯作者	Guo, Zhaolu(gzl@jxust.edu.cn)
摘要	The traditional gravitational search algorithm (GSA) maintains good diversity of solutions but often demonstrates weak local search ability. To promote the local search ability of GSA, a new GSA based on chaotic local search (CLSGSA) is introduced in this paper. In its search operations, CLSGSA first executes the conventional search operations of the basic GSA to maintain the diversity of solutions. After that, CLSGSA executes a chaotic local search with the search experience from the current best solution to increase the local search capability. In the experiments, we utilise a suite of benchmark functions to verify the performance of CLSGSA. Moreover, we compare the proposed CLSGSA with several GSA variants. The comparisons validate the effectiveness of CLSGSA.
关键词	evolutionary algorithm optimisation algorithm gravitational search local search chaotic map
关键词[WOS]	DIFFERENTIAL EVOLUTION ; OPTIMIZATION ALGORITHM ; GLOBAL OPTIMIZATION
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61662029] ; Education Department Scientific Research Foundation of Jiangxi Province, China[GJJ160623] ; Education Department Scientific Research Foundation of Jiangxi Province, China[GJJ170495] ; Program of Qingjiang Excellent Young Talents, Jiangxi University of Science and Technology
项目资助者	National Natural Science Foundation of China ; Education Department Scientific Research Foundation of Jiangxi Province, China ; Program of Qingjiang Excellent Young Talents, Jiangxi University of Science and Technology
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence ; Computer Science, Theory & Methods
WOS记录号	WOS:000649186100003
出版者	INDERSCIENCE ENTERPRISES LTD
七大方向——子方向分类	计算智能
引用统计	被引频次：5[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/44489
专题	多模态人工智能系统全国重点实验室_人工智能与机器学习（杨雪冰）-技术团队
通讯作者	Guo, Zhaolu
作者单位	1.Jiangxi Univ Sci & Technol, Sch Sci, Ganzhou 341000, Peoples R China 2.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 3.Hebei GEO Univ, Sch Informat Engn, Shijiazhuang 050031, Hebei, Peoples R China
第一作者单位	中国科学院自动化研究所
通讯作者单位	中国科学院自动化研究所
推荐引用方式 GB/T 7714	Guo, Zhaolu,Zhang, Wensheng,Wang, Shenwen. Improved gravitational search algorithm based on chaotic local search[J]. INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION,2021,17(3):154-164.
APA	Guo, Zhaolu,Zhang, Wensheng,&Wang, Shenwen.(2021).Improved gravitational search algorithm based on chaotic local search.INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION,17(3),154-164.
MLA	Guo, Zhaolu,et al."Improved gravitational search algorithm based on chaotic local search".INTERNATIONAL JOURNAL OF BIO-INSPIRED COMPUTATION 17.3(2021):154-164.