Hybrid many-objective cuckoo search algorithm withLevyand exponential distributions

doi:10.1007/s12293-020-00308-3

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

	Hybrid many-objective cuckoo search algorithm withLevyand exponential distributions
	Cui, Zhihua 1; Zhang, Maoqing 2; Wang, Hui 3; Cai, Xingjuan 1; Zhang, Wensheng4 ; Chen, Jinjun 5
发表期刊	MEMETIC COMPUTING
ISSN	1865-9284
	2020-07-26
页码	15
通讯作者	Zhang, Maoqing(maoqing_zhang@163.com)
摘要	Hybrid many-objective cuckoo search algorithm (HMaOCS) is a newly proposed method for Many-objective optimization problems (MaOPs), and has achieved promising performance. However,Levyand Gaussian distributions used in global search manner of HMaOCS is originally proposed for optimization problems with one objective, and they are not suitable for MaOPs as illustrated in this paper. To further exploit the potential of HMaOCS, this paper investigates four different probability distributions and their six corresponding combinations. Comparison results illustrate that the combination ofLevyand Exponential distributions is able to greatly improve HMaOCS. On the basis of comparison results and analysis on both DTLZ and WFG test suites with 2, 3, 4, 6, 8 and 10 objectives, it can be concluded that HMaOCS withLevyand Exponential distributions exhibits better performance compared with most advanced algorithms.
关键词	HMaOCS Cuckoo search Levydistribution Exponential distribution
DOI	10.1007/s12293-020-00308-3
关键词[WOS]	EVOLUTIONARY ALGORITHM ; SELECTION
收录类别	SCI
语种	英语
资助项目	National Natural Science Foundation of China[61806138] ; National Natural Science Foundation of China[U1636220] ; National Natural Science Foundation of China[61663028] ; National Natural Science Foundation of China[71771176] ; National Natural Science Foundation of China[51775385] ; National Natural Science Foundation of China[61703279] ; National Natural Science Foundation of China[71371142] ; Natural Science Foundation of Shanxi Province[201801D121127] ; PhD Research Startup Foundation of Taiyuan University of Science and Technology[20182002] ; Distinguished Young Talents Plan of Jiang-xi Province[20171BCB23075] ; Natural Science Foundation of Jiang-xi Province[20171BAB202035]
项目资助者	National Natural Science Foundation of China ; Natural Science Foundation of Shanxi Province ; PhD Research Startup Foundation of Taiyuan University of Science and Technology ; Distinguished Young Talents Plan of Jiang-xi Province ; Natural Science Foundation of Jiang-xi Province
WOS研究方向	Computer Science ; Operations Research & Management Science
WOS类目	Computer Science, Artificial Intelligence ; Operations Research & Management Science
WOS记录号	WOS:000552582000001
出版者	SPRINGER HEIDELBERG
引用统计	被引频次：15[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/173211/40278
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	Zhang, Maoqing
作者单位	1.Taiyuan Univ Sci & Technol, Complex Syst & Computat Intelligence Lab, Taiyuan 030024, Shanxi, Peoples R China 2.Tongji Univ, Sch Elect & Informat Engn, Shanghai 201804, Peoples R China 3.Nanchang Inst Technol, Sch Informat Engn, Nanchang 330099, Jiangxi, Peoples R China 4.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China 5.Swinburne Univ Technol, Melbourne, Vic 3000, Australia
推荐引用方式 GB/T 7714	Cui, Zhihua,Zhang, Maoqing,Wang, Hui,et al. Hybrid many-objective cuckoo search algorithm withLevyand exponential distributions[J]. MEMETIC COMPUTING,2020:15.
APA	Cui, Zhihua,Zhang, Maoqing,Wang, Hui,Cai, Xingjuan,Zhang, Wensheng,&Chen, Jinjun.(2020).Hybrid many-objective cuckoo search algorithm withLevyand exponential distributions.MEMETIC COMPUTING,15.
MLA	Cui, Zhihua,et al."Hybrid many-objective cuckoo search algorithm withLevyand exponential distributions".MEMETIC COMPUTING (2020):15.