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
03.03.2024:

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

Google Scholar: h-index: 108, i10-index: 416, citations: 50,029

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.     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)

 

2.     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)

 

3.     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)

 

4.     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)

 

5.     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)

 

6.     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)

 

7.     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)

 

8.     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)

 

9.     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)

 

10.   Xinan Chen, Ruibing Bai, Rong Qu, and Yaochu Jin. Deep reinforcement learning assisted genetic programming ensemble hyper-heuristics for dynamic scheduling of container port trucks. IEEE Transactions on Evolutionary Computation, 2024 (accepted)

 

11.   Wei Song, Shaocong Liu, Xinjie Wangm Yinan Guo, Shengxiang Yang, and Yaochu Jin. Learning to guide particle search for dynamic multiobjective optimization. IEEE Transactions on Cybernetics, 2024 (accepted)

 

12.   Jianping Luo, Yongfei Dong, Qiqi Liu, Zexuan Zhu, Wenming Cao, Kay Chen Tan, and Yaochu Jin. A new multitask joint learning framework for expensive multi-objective optimization problems. IEEE Transactions on Emerging Technologies in Computational Intelligence, 2024 (accepted)

 

13.   Wenxuan Fang, Wei Du, Renchu He, Yang Tang, Yaochu Jin. Diffusion model-based multiobjective optimization for gasoline blending scheduling. IEEE Computational Intelligence Magazine, 2024 (accepted)

 

14.   Shiqing Liu, Xueming Yan, and Yaochu Jin. An edge-aware graph autoencoder trained on scale-imbalanced data for travelling salesman problems. Knowledge-Based Systems, 2024 (accepted)

 

15.   Haofeng Wu, Yaochu Jin, Kailai Gao, Jinliang Ding, and Ran Cheng. Surrogate-assisted evolutionary multi-objective optimization of medium-scale problems by random grouping and sparse Gaussian modeling. IEEE Transactions on Emerging Technologies in Computational Intelligence, 2024 (accepted)

 

16.   Wei Du, Wenxuan Fang, Liang Chen, Yang Tang, and Yaochu Jin. A novel dual-stage evolutionary algorithm for finding robust solutions. IEEE Transactions on Emerging Topics in Computational Intelligence, 2024 (accepted)

 

17.   Leming Wu, Yaochu Jin, Yuping Yan, Kuangrong Hao. FL-OTCSEnc: Towards secure federated learning with deep compressed sensing. Knowledge-Based Systems, 2024 (accepted)

 

18.  Guoyang Xie, Jinbao Wang, Jiaqi Liu, Yong Liu, Chengjie Wang, Feng Zheng, and Yaochu Jin.