Evolutionary Dynamic Multiobjective Optimization via Learning From Historical Search Process

Zhao，Qi1; Yan，Bai1; Shi，Yuhui2; Middendorf，Martin3

2022-07

10.1109/TCYB.2021.3059252

IEEE Transactions on Cybernetics   影响因子和分区

2168-2275

Change response dynamic optimization evolutionary algorithm (EA) learning multiobjective optimization

SCI ; EI

第一

20211310144476

Computational efficiency ; Data mining ; Evolutionary algorithms ; Forecasting

Data Processing and Image Processing:723.2 ; Optimization Techniques:921.5

IEEE

1.Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China, and also with the School of Computer Science and Technology, University of Science and Technology of China, Hefei 230027, China.
2.Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China (e-mail: shiyh@sustech.edu.cn)
3.Department of Computer Science, Leipzig University, 04009 Leipzig, Germany.

Zhao，Qi,Yan，Bai,Shi，Yuhui,et al. Evolutionary Dynamic Multiobjective Optimization via Learning From Historical Search Process[J]. IEEE Transactions on Cybernetics,2022,52(7):6119-6130.

Zhao，Qi,Yan，Bai,Shi，Yuhui,&Middendorf，Martin.(2022).Evolutionary Dynamic Multiobjective Optimization via Learning From Historical Search Process.IEEE Transactions on Cybernetics,52(7),6119-6130.

Zhao，Qi,et al."Evolutionary Dynamic Multiobjective Optimization via Learning From Historical Search Process".IEEE Transactions on Cybernetics 52.7(2022):6119-6130.