A hybrid many-objective cuckoo search algorithm

doi:10.1007/s00500-019-04004-4

CORC > 自动化研究所 > 中国科学院自动化研究所 > 精密感知与控制研究中心 > 人工智能与机器学习

	A hybrid many-objective cuckoo search algorithm
	Cui, Zhihua 2; Zhang, Maoqing 1; Wang, Hui 3; Cai, Xingjuan 2; Zhang, Wensheng 4
刊名	SOFT COMPUTING
	2019-11-01
卷号	23 期号:21 页码:10681-10697
关键词	Cuckoo search Many-objective optimization problems Non-dominated sorting Reference points
ISSN号	1432-7643
DOI	10.1007/s00500-019-04004-4
通讯作者	Zhang, Maoqing(maoqing_zhang@163.com) ; Cai, Xingjuan(xingjuancai@163.com)
英文摘要	Cuckoo search (CS) is an excellent population-based algorithm and has shown promising performance in dealing with single- and multi-objective optimization problems. However, for many-objective optimization problems (MaOPs), CS cannot be directly employed. So far, few paper have been reported to use CS to solve MaOPs. In this paper, we try to propose a hybrid many-objective cuckoo search (HMaOCS) for MaOPs. In HMaOCS, the standard CS is firstly modified to effectively deal with MaOPs. Then, non-dominated sorting and the strategy of reference points are employed to ensure the convergence and diversity. In order to verify the performance of HMaOCS, DTLZ and WFG benchmark sets are utilized in the experiments. Experimental results show that HMaOCS can achieve promising performance compared with five other well-known many-objective optimization algorithms.
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]
WOS关键词	MULTIOBJECTIVE EVOLUTIONARY ALGORITHM ; NONDOMINATED SORTING APPROACH ; OPTIMIZATION ALGORITHM ; GENETIC ALGORITHM ; FIREFLY ALGORITHM ; BAT ALGORITHM
WOS研究方向	Computer Science
语种	英语
出版者	SPRINGER
WOS记录号	WOS:000492901800008
资助机构	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
内容类型	期刊论文
源URL	[http://ir.ia.ac.cn/handle/173211/28850]
专题	精密感知与控制研究中心_人工智能与机器学习
通讯作者	Zhang, Maoqing; Cai, Xingjuan
作者单位	1.Tongji Univ, Sch Elect & Informat, Shanghai 201804, Peoples R China 2.Taiyuan Univ Sci & Technol, Complex Syst & Computat Intelligence Lab, Taiyuan 030024, Shanxi, 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
推荐引用方式 GB/T 7714	Cui, Zhihua,Zhang, Maoqing,Wang, Hui,et al. A hybrid many-objective cuckoo search algorithm[J]. SOFT COMPUTING,2019,23(21):10681-10697.
APA	Cui, Zhihua,Zhang, Maoqing,Wang, Hui,Cai, Xingjuan,&Zhang, Wensheng.(2019).A hybrid many-objective cuckoo search algorithm.SOFT COMPUTING,23(21),10681-10697.
MLA	Cui, Zhihua,et al."A hybrid many-objective cuckoo search algorithm".SOFT COMPUTING 23.21(2019):10681-10697.