Note: Some publications are made on-line available for faster dissemination. The copyright of the papers is owned by their publisher. Source code is for free use for academic research ONLY.

Publications of Yaochu Jin

My citation profiles as of 07.14.2024:

Orcid: https://orcid.org/0000-0003-1100-0631  Guide2Research Profile

Google Scholar: h-index: 110, i10-index: 416, citations: 51,323

Web of  Science, h-index: 81, citations: 24,980

Scopus Author Profile: h-index=83, citations = 29,402

Research Gate: citations: 39,058

DBLP Computer Science Bibliography.

IEEE Xplore Author Profile

 

 

PlatEMO, a Single-, Multi- and Many-objective Optimization Tool

 

In Press / Accepted / Under Review

 

1.     Wenxuan Fang, Wei Du, Guo Yu, Renchu He, and Yaochu Jin. Preference prediction for evolutionary multi-objective optimization for gasoline blending scheduling. IEEE Transactions on Artificial Intelligence, 2024 (accepted)

 

2.     Qi-Te Yang, Jian-Yu Li, Zhi-Hui Zhan, Yunliang Jiang, Yaochu Jin, and Jun Zhang. A hierarchical and ensemble surrogate-assisted evolutionary algorithm with model reduction for expensive many-objective optimization. IEEE Transactions on Evolutionary Computation, 2024 (accepted)

 

3.     Xuemin Yan, Yan Xiao, and Yaochu Jin. Generative large language models explained. IEEE Computational Intelligence Magazine, 2024 (accepted)

 

4.     Xilu Wang and Yaochu Jin. Distilling ensemble surrogates for federated data-driven many-task optimization. IEEE Transactions on Evolutionary Computation, 2024 (accepted)

 

5.     Shangshang Yang, Haiping Ma, Ying Bi, Ye Tian, Limiao Zhang, Yaochu Jin, and Xingyi Zhang. An evolutionary multi-objective neural architecture search approach to advancing cognitive diagnosis in intelligent education. IEEE Transactions on Evolutionary Computation, 2024 (accepted)

 

6.     Xueming Yan, Yan Xiao, and Yaochu Jin. Generative Large Language Models Explained. IEEE Computational Intelligence Magazine, 2024 (accepted)

 

7.     Xiangyu Wang, Ran Cheng, and Yaochu Jin. Sparse large-scale multi-objective optimization by identifying non-zero decision variables. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2024 (accepted)

 

8.     Ye Tian, Luchen Wang, Shangshang Yang, Jinliang Ding, Yaochu Jin, and Xingyi Zhang. Neural network-based dimensionality reduction for large-scale binary optimization with millions of variables. IEEE Transactions on Evolutionary Computation, 2024 (accepted)

 

9.     Haofeng Wu, Qingda Chen, Jiaxin Chen, Yaochu Jin, Jinliang Ding, Xingyi Zhang, and Tianyou Chai. A multi-stage expensive constrained multi-objective optimization algorithm based on ensemble infill criterion. IEEE Transactions on Evolutionary Computation, 2024 (accepted)

 

10.  Tianzi Zheng, Jianchang Liu, Yaochu Jin, and Yuanchao Liu. A multitask-assisted evolutionary algorithm for constrained multimodal multiobjective optimization. IEEE Transactions on Evolutionary Computation, 2024 (accepted)

 

11.  Yuping Yan, Xilu Wang, Peter Ligeti, and Yaochu Jin. DP-FSAEA: Differential privacy for federated surrogate-assisted evolutionary algorithms. IEEE Transactions on Evolutionary Computation, 2024 (accepted)

 

12.  Maojiang Tian, Mingke Chen, Wei Du, Yang Tang and Yaochu Jin. An enhanced differential grouping method for large-scale overlapping problems. IEEE Transactions on Evolutionary Computation, 2024 (accepted)

 

13.  Beichen Huang, Ran Cheng, Zhuozhao Li, Yaochu Jin, and Kay Chen Tan. EvoX: A distributed GPU-accelerated framework for scalable evolutionary computation. IEEE Transactions on Evolutionary Computation, 2024 (accepted)

 

14.  Linqiang Pan, Jianqing Lin, Handing Wang, Cheng He, Kay Chen Tan, and Yaochu Jin. Computationally expensive high-dimensional multiobjective optimization via surrogate-assisted reformulation and decomposition. IEEE Transactions on Evolutionary Computation, 2024 (accepted)

 

15.  Haoran Gu, Handing Wang, Cheng He, Bo Yuan, and Yaochu Jin. Large-scale multiobjective evolutionary algorithm guided by low-dimensional surrogates of scalarization functions. Evolutionary Computation, 2024 (accepted)

 

16.  Wanting Zhang, Wei Du, Renchu He, Wenli Du, and Yaochu Jin. Large-scale continuous-time crude oil scheduling: A variable-length evolutionary optimization approach. IEEE Transactions on Automation Science and Engineering, 2024 (accepted)</