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Hybrid many-objective cuckoo search algorithm withLevyand exponential distributions

文献类型：期刊论文

作者Cui, Zhihua2; Zhang, Maoqing3; Wang, Hui1; Cai, Xingjuan2; Zhang, Wensheng4; Chen, Jinjun5
刊名MEMETIC COMPUTING
出版日期2020-07-26
页码15
关键词HMaOCS Cuckoo search Levydistribution Exponential distribution
ISSN号1865-9284
DOI10.1007/s12293-020-00308-3
通讯作者Zhang, Maoqing(maoqing_zhang@163.com)
英文摘要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.
WOS关键词EVOLUTIONARY ALGORITHM ; SELECTION
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 ; Operations Research & Management Science
语种英语
WOS记录号WOS:000552582000001
出版者SPRINGER HEIDELBERG
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/173211/40277]  
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
作者单位1.Nanchang Inst Technol, Sch Informat Engn, Nanchang 330099, Jiangxi, Peoples R China
2.Taiyuan Univ Sci & Technol, Complex Syst & Computat Intelligence Lab, Taiyuan 030024, Shanxi, Peoples R China
3.Tongji Univ, Sch Elect & Informat Engn, Shanghai 201804, 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.

入库方式： OAI收割

来源：自动化研究所

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