| Title | RM-SAEA: Regularity Model Based Surrogate-Assisted Evolutionary Algorithms for Expensive Multi-Objective Optimization. |
| Author | |
| Corresponding Author | Wenjing Hong |
| Publication Years | 2023-02
|
| Conference Name | the 2023 Genetic and Evolutionary Computation Conference (GECCO 2023）
|
| Conference Date | Jul 15, 2023 - Jul 19, 2023
|
| Conference Place | Lisbon
|
| SUSTech Authorship | Others
|
| Data Source | 人工提交
|
| Document Type | Conference paper |
| Identifier | http://kc.sustech.edu.cn/handle/2SGJ60CL/523789 |
| Department | Department of Computer Science and Engineering 理学院_统计与数据科学系 |
| Affiliation | 1.Shanghai Institute of AI for Education and School of Computer Science and Technology, East China Normal University, Shanghai, China 2.Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation, Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China 3.Shanghai Institute of AI for Education and School of Computer Science and Technology, East China Normal University, Shanghai, China 4.Guangdong Provincial Key Laboratory of Brain-Inspired Intelligent Computation, Department of Computer Science and Engineering, Department of Statistics and Data Science, Southern University of Science and Technology, Shenzhen, China |
| Corresponding Author Affilication | Department of Computer Science and Engineering |
| Recommended Citation GB/T 7714 |
Yongfan Lu,Bingdong Li,Wenjing Hong,et al. RM-SAEA: Regularity Model Based Surrogate-Assisted Evolutionary Algorithms for Expensive Multi-Objective Optimization.[C],2023.
|
| Files in This Item: | There are no files associated with this item. | |||||
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
;
Edit Comment