| Title | Enhancing Diversity by Local Subset Selection in Evolutionary Multiobjective Optimization |
| Author | |
| Publication Years | 2022
|
| DOI | |
| Source Title | |
| ISSN | 1941-0026
|
| Volume | PPIssue:99Pages:1-1 |
| Keywords | |
| URL | [Source Record] |
| SUSTech Authorship | Others
|
| Data Source | IEEE
|
| PDF url | https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=9843885 |
| Citation statistics |
Cited Times [WOS]:0
|
| Document Type | Journal Article |
| Identifier | http://kc.sustech.edu.cn/handle/2SGJ60CL/375590 |
| Department | Department of Computer Science and Engineering |
| Affiliation | 1.Shanghai Institute of AI for Education, and the School of Computer Science and Technology, East China Normal University, Shanghai, China 2.Department of Computer Science and Engineering, Guangdong Key Laboratory of Brain-Inspired Intelligent Computation, Southern University of Science and Technology, Shenzhen, China |
| Recommended Citation GB/T 7714 |
Zihan Wang,Bochao Mao,Hao Hao,et al. Enhancing Diversity by Local Subset Selection in Evolutionary Multiobjective Optimization[J]. IEEE Transactions on Evolutionary Computation,2022,PP(99):1-1.
|
| APA |
Zihan Wang,Bochao Mao,Hao Hao,Wenjing Hong,Chunyun Xiao,&Aimin Zhou.(2022).Enhancing Diversity by Local Subset Selection in Evolutionary Multiobjective Optimization.IEEE Transactions on Evolutionary Computation,PP(99),1-1.
|
| MLA |
Zihan Wang,et al."Enhancing Diversity by Local Subset Selection in Evolutionary Multiobjective Optimization".IEEE Transactions on Evolutionary Computation PP.99(2022):1-1.
|
| Files in This Item: | There are no files associated with this item. | |||||
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