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A hybrid many-objective cuckoo search algorithm

文献类型：期刊论文

作者Cui, Zhihua3; Zhang, Maoqing1; Wang, Hui4; Cai, Xingjuan3; Zhang, Wensheng2
刊名SOFT COMPUTING
出版日期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
DOI10.1007/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.
WOS关键词MULTIOBJECTIVE EVOLUTIONARY ALGORITHM ; NONDOMINATED SORTING APPROACH ; OPTIMIZATION ALGORITHM ; GENETIC ALGORITHM ; FIREFLY ALGORITHM ; BAT ALGORITHM
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研究方向Computer Science
语种英语
WOS记录号WOS:000492901800008
出版者SPRINGER
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
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.Chinese Acad Sci, Inst Automat, Beijing 100190, Peoples R China
3.Taiyuan Univ Sci & Technol, Complex Syst & Computat Intelligence Lab, Taiyuan 030024, Shanxi, Peoples R China
4.Nanchang Inst Technol, Sch Informat Engn, Nanchang 330099, Jiangxi, 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.

入库方式： OAI收割

来源：自动化研究所

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