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 08.08.2025:
Orcid: https://orcid.org/0000-0003-1100-0631 Guide2Research Profile
Google
Scholar: h-index: 122, i10-index: 485, citations:
62,762
Web of
Science, h-index: 95, citations: 35,674
Scopus
Author Profile: h-index=102, citations = 43,615
Research Gate: citations: 39,058
DBLP Computer Science Bibliography.
PlatEMO, a Single-, Multi- and Many-objective Optimization Tool
1.
Tianzi Zheng, Jianchang
Liu, Yaochu Jin, Xiangyu Wang, and Yuanchao Liu. Large-scale multimodal multiobjective
optimization based on multiview diversity enhancement mechanism. IEEE
Transactions on Evolutionary Computation, 2025 (accepted)
2.
Jie Zhao, Kang Hao Cheong, and Yaochu Jin. Multi-domain evolutionary optimization of
network structures. IEEE Transactions on Cybernetics, 2025 (accepted)
3. Xueming Yan, Ziqi Wang and Yaochu Jin. Heterogeneity-aware federated graph neural networks for incomplete multi-view clustering. IEEE Transactions on Emerging Topics in Computational Intelligence, 2025 (accepted)
4. Yongxin Deng, Xihe Qiu, Xiaoyu Tan and Yaochu Jin. FedSlate: A Federated deep reinforcement learning recommender system. IEEE Transactions on Emerging Topics in Computational Intelligence, 2025 (accepted)
5. Jing Jane Liang, Genyue Liu, Ying Bi, Mingyuan Yu, Mengnan Liu, and Yaochu Jin. Evolutionary neural architecture search for remote sensing image classification. IEEE Transactions on Neural Networks and Learning Systems, 2025 (accepted)
6. Qiqi Liu, Yaochu Jin and Guodong Chen. Optimization of an implicit acquisition function for federated Bayesian many-task optimization. IEEE Transactions on Evolutionary Computation, 2025 (accepted)
7. Shuai Wang and Yaochu Jin. MFEA-RCIM: A multi-factorial evolutionary algorithm for determining robust and influential seeds from competitive networks under structural failures.
IEEE Transactions on
Cybernetics, 2025
(accepted)
8. Shulei Liu, Junchi Yan, Handing Wang, and Yaochu Jin. Morphology evolution for embodied robot design with a classifier-guided diffusion model. IEEE Transactions on Evolutionary Computation, 2025 (accepted)
9.
Yaqing Hou, Jie Kang, Haiyin
Piao,
Yifeng Zeng, Yew-Soon Ong, Yaochu Jin, and Qiang Zhang. Cooperative multiagent
learning and exploration with min–max intrinsic motivation. IEEE
Transactions on Cybernetics, 2025 (accepted)
10. Zhening Liu, Handing Wang, Maoguo Gong, Yaochu Jin, Data stream driven dynamic multiobjective optimization using surrogate transfer. IEEE Transactions on Emerging Topics in Computational Intelligence, 2025 (accepted)
11. Wei Song, Zhi Liu, Jian Yu, Xiaoyan Sun, Yaochu Jin and Khin Wee Lai. Multisource and hidden source-based knowledge transfer for solving dynamic multiobjective optimization problems. IEEE Transactions on Evolutionary Computation, 2025 (accepted)
12. Xiaoyu
Zhong, Xiangjuan Yao, Kangjia Qiao, Dunwei Gong and Yaochu Jin. An indicator-based
evolutionary algorithm for large-scale constrained multi-objective optimization.
IEEE Transactions on Evolutionary Computation, 2025 (accepted)
13. Kaili Zhao, Xilu Wang, Chaoli Sun, Yaochu Jin, and Asad Hayat. Efficient large-scale expensive optimization via surrogate-assisted sub-problem selection. IEEE Transactions on Evolutionary Computation, 2025 (accepted)
14. Feng
Xiao, Ruyu Liu, Xu Cheng, Haoyu Zhang, Jianhua Zhang, and Yaochu Jin. Dual-branch semantic
enhancement network joint with iterative self-matching training strategy for
semi-supervised semantic segmentation. IEEE Transactions on Emerging
Topics in Computational Intelligence, 2025 (accepted)
15. 严宇萍，高婷，谢雨晗，金耀初。群智能系统的安全与隐私保护综述。电信科学， 2025
16. Fei Wu, Tao Shen,
Thomas Bäck, Jingyuan Chen,
Gang Huang, Yaochu Jin, Kun Kuang, Kengze Li, Cewu Lu, Jiaxu Miao, Yongwei Wang, Ying Wei, Fan Wu, Junchi
Yan, Hongxia Yang, Yi Yang, Shengyu
Zhang, Zhou Zhao, Yueting Zhuang, and Yunhe Pan. Knowledge-empowered,
collaborative, and co-evolving AI models: The post-LLM roadmap. Engineering,
2024 (accepted)
17. Jianqing Lin, Cheng He, Hanjing
Jiang, Yabing Huang, and Yaochu Jin. Surrogate-assisted multiobjective gene selection for cell classification from
large-scale single-cell RNA sequencing data. IEEE Transactions on
Evolutionary Computation, 2025 (accepted)
18. Qihang Peng, Hongliang Guo,
Boyang Li, Chih-Yung Wen,
and Yaochu Jin. SMC-searcher:
signal mediated coordination for decentralized multi-robot adversarial moving
target search. IEEE Transactions on Emerging Topics in Computational
Intelligence, 2025 (accepted)
19. Xihe Qiu, Haoyu Wang, Xiaoyu Tan, and Yaochu
Jin. CVDLLM: Automated
cardiovascular disease diagnosis with large-language-model-assisted graph
attentive feature interaction. IEEE Transactions on Artificial
Intelligence, 2025 (accepted)
20. Ziwei Dong, Shuai Mao, Wei Du, Yaochu Jin,
and Yang Tang. Two-group
distributed optimization under cooperative-collaborative networks with linear
convergence. IEEE Transactions on Circuits and Systems I: Regular Papers,
2024 (accepted)
21. Xueming Yan, Han Huang, Yaochu Jin, Zilong Wang, and Zhifeng Hao. Neural
architecture search based on bipartite graphs for text classification. IEEE
Transactions on Neural Networks and Learning Systems, 2024 (accepted)
22. Haoran Gu, Hangding Wang, Yaochu
Jin. Surrogate-assisted
neighborhood search with only a few weight vectors for expensive large-scale multiobjective binary optimization. IEEE
Transactions on Evolutionary Computation, 2024 (accepted)
23. Yan Xiao, Yaochu
Jin, Bin Wang, Yan Zhang, Kuangrong Hao, and Haizhou Li. Zero-Shot relation
classification through inference on category attributes. IEEE
Transactions on Neural Networks and Learning Systems, 2024 (accepted)
24. Wenxuan Fang, Wei Du, Guo
Yu, Renchu He, and Yaochu Jin. Preference
prediction-based evolutionary multi-objective optimization for gasoline
blending scheduling. IEEE Transactions on Artificial Intelligence,
2024 (accepted)
25. 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)
26. Huiting Li, Yaochu Jin
and Ran Cheng. Adaptive
multi-stage evolutionary search for constrained multi-objective optimization.
Complex & Intelligent Systems, 2024
27. Xilu Wang and Yaochu
Jin. Distilling
ensemble surrogates for federated data-driven many-task optimization. IEEE
Transactions on Evolutionary Computation, 2024 (accepted)
28. 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)
29. 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)
30. 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)
31. 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)
32. 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)
33. 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)
34. 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)
35. 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)
36.
Yifei Sun, Zhuo Liu, Yaochu Jin, Xin Sun, Yifei Cao and Jie Yang. Global and
cluster structural balance via a priority strategy based memetic algorithm. IEEE Transactions
on Emerging Topics in Computational Intelligence,
2024 (accepted)
37. Langchun Si, Xingyi Zhang, Ye Tian, Shangshang Yang, Limiao Zhang, and Yaochu Jin. Linear subspace surrogate modelling for large-scale expensive single / multi-objective optimization. IEEE Transactions on Evolutionary Computation, 2023 (accepted)
38. Rui Wang, Oguzhan Ersoy, Hangyu Zhu, Yaochu Jin, and Kaitai
Liang. FEVERLESS:
Fast and secure vertical federated learning based on XGBoost for decentralized
labels. IEEE Transactions on Big Data, 2022
(accepted)
39. Zeqi Zheng, Yanchen
Huang, Yingchao Yu, Zizheng
Zhu, Junfeng Tang, Zhaofei
Yu, and Yaochu Jin. SpiLiFormer: Enhancing spiking transformers with lateral inhibition. The 20th IEEE/CVF
International Conference on Computer Vision (ICCV 2025), Oct 19
– 23th, 2025, Honolulu, Hawaii, 2025
40. Qiqi Liu, Jiaqiang Li, Yuchen
Liu, Yaochu Jin, Lingjuan Lv,
Xiaohu Qu, and Han Yu. Personalized federated
learning under local supervision. The 20th IEEE/CVF International Conference on Computer
Vision (ICCV 2025), Oct 19
– 23th, 2025, Honolulu, Hawaii, 2025
41. Peng Liao, Xilu Wang, Yaochu
Jin, Wenli Du, and Han Hu. Neural Architecture
Search Driven by Locally Guided Diffusion for Personalized Federated Learning. The 20th IEEE/CVF
International Conference on Computer Vision (ICCV 2025), Oct 19
– 23th, 2025, Honolulu, Hawaii, 2025
42. Shunchang Liu, Zhuan Shi, Lingjuan Lyu, Yaochu Jin, and Boi Faltings. CopyJudge: Automated copyright infringement identification and mitigation in text-to-image diffusion models. The 33rd ACM International Conference on Multimedia (ACM MM 2025), Dublin, Ireland, Oct. 27-31 2025
43. Mengmeng Chen, Xiaohu Wu, Qiqi Liu, Tiantian He, Yew-Soon Ong, Yaochu Jin, Qicheng Lao, and Han Yu. Voronoi-grid-based Pareto front learning and its application to collaborative federated learning. International Conference on Machine Learning (ICML 2025), Vancouver, July 2025
44. Leming Wu, Yaochu Jin,
Kuangrong Hao, and Han Yu. Local data quantity - Aware
weighted averaging for federated learning with dishonest clients. IEEE
International Conference on Multimedia & Expo 2025, Nantes, France,
from June 30 to July 4, 2025
45. Zihan Ye, Shreyank Gowda, Shiming Chen, Xiaobo Jin, Xiaowei Huang, Haotian Xu, Fahad Shahbaz Khan, Yaochu Jin, Kaizhu Huang. ZeroDiff: Solidified Visual-semantic Correlation in Zero-Shot Learning. The Thirteenth International Conference on Learning Representations (ICLR 2025)
46. Ciyuan Peng, Yuelong Huang, Qichao Dong, Shuo Yu, Feng Xia, Chengqi Zhang, Yaochu Jin. Biologically Plausible Brain Graph Transformer. The Thirteenth International Conference on Learning Representation (ICLR 2025)
47. Limiao Zhang, Xinyang Qi, Maiping Ma, Jie Gao, Xingyi Zhang, Yanqing Hu, and Yaochu Jin. Spatial-temporal analysis of collective emotional resonance during global health crisis. The Web Conference 2025, 2025
48. Yuchen Liu, Chen Chen, Lingjuan Lyu, Yaochu Jin, and Gang Chen. Exploit gradient skewness to circumvent Byzantine defenses for federated learning. The 39th Annual AAAI Conference on Artificial Intelligence (AAAI 2025), 2025
49.
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, 29(4): 1371-1385 2025
50. Tonghao Wang, Xingguang Peng, Xiaokang Lei, Handing Wang and
Yaochu Jin. Knowledge-assisted
evolutionary task scheduling for hierarchical multiagent systems with
transferable surrogates. Swarm and Evolutionary Computation, Volume
98, 102107, October 2025
51. 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, 29(4): 1941-0026, 2025
52.
Yihao Liu, Xu Cao, Tingting Chen, Yankai Jiang,
Junjie You, Minghua Wu, Xiaosong Wang, Mengling Feng, Yaochu Jin, and Jintai Chen. From
screens to scenes: A survey of embodied AI in healthcare. Information
Fusion. 119, 103033, 2025
53. Luying Feng, Lianghong Gui, Wenzhu Xu, Xiang Wang, Canjun
Yang, Yaochu Jin and Wei Yang. Locomotion joint angle and
moment estimation with soft wearable sensors for personalized exosuit control. IEEE Transactions on Neural Systems
and Rehabilitation Engineering, 33: 1048 – 1060, 2025
54. Zhen Yang, Yiping Zhu, Yunliang Jiang, Yaochu Jin, Feng Ju, and Yang Feng. An adaptive multitask optimization algorithm based on competitive scoring. Swarm and Evolutionary Computation, 92: 101798, 2025
55. 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, 22: 2526-2541, 2025
56.
Ziwei Dong, Yaochu Jin,
Shuai Mao, Wei Ren, Wei Du, and Yang Tang. Distributed optimization
with asynchronous computation and event-triggered communication. IEEE
Transactions on Automatic Control, 70(2): 1084 – 1099, 2025
57. Danya Xu, Yi Liu, Guanghui Wen, Yaochu Jin, Tianyou
Chai, and Tao Yang. DeFedTL: A decentralized federated transfer learning method
for fault diagnosis. IEEE Transactions on Industrial Informatics,
21(2): 1704 – 1713, 2025
58. Qihang Peng, , .
PF-MAAC:
A learning-based method for probabilistic optimization in time-constrained
non-adversarial moving target search. Swarm and Evolutionary Computation,
92: 101785, 2025
59. Junfeng Tang, Handing Wang, and Yaochu Jin. Knee-oriented expensive many-objective optimization via aggregation-dominance: A multi-task perspective. Swarm and Evolutionary Computation, 92: 101813, 2025
60. Xueming Yan, Chuyue Wang, and Yaochu Jin. Federated training of GNNs with similarity graph reasoning for text-image retrieval. Neurocomputing, Volume 623, 28 March 2025, 12941
61. Zhihao Yu, , g, and Yaochu Jin. Mde-EvoNAS:
Automatic
network architecture design for monocular depth estimation via evolutionary
neural architecture search. Swarm and Evolutionary
Computation, Volume 93, Article No. 101837, 2025
62. Xingyi Zhang, Ran Cheng, Ye Tian and Yaochu Jin. Evolutionary Large-Scale Multi-Objective Optimization and Applications. John Wiley & Sons, 2024
63. Ruyu Liu, Haoyu Zhang, Yaochu Jin. ColVO: Colonoscopic visual odometry considering geometric and photometric consistency. The 32ed ACM International Conference on Multimedia (ACM MM 2024), 28 October - 1 November 2024, Melbourne, Australia
64. Peng Liao, Xilu Wang, Wenli Du, and Yaochu Jin. MO-EMT-NAS: Multi-objective continuous transfer of architectural knowledge between tasks from different datasets. The 18th European Conference on Computer Vision (ECCV 2024), Milano, September 29 – October 4, 2024
65. Zhaoxin Wang, Handing Wang, Cong Tian, and Yaochu Jin. Adversarial training: A bi-level optimization perspective. The 18th European Conference on Computer Vision (ECCV 2024), Milano, September 29 – October 4, 2024
66. Yan Xiao, Yaochu Jin, Kuangrong Hao. Federated document-level biomedical relation extraction with localized context contrast. COLING 2024 - The 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation. Torino, Italy, May 20-25, 2024
67.
颜学明，黄翰，金耀初，钟国，郝志峰。面向不平衡短文本情感多分类的三阶语义图数据增广方法。计算机学报，47(12): 2742-2759,
2024
68. Guodong Chen, Jiu Jimmy Jiao,
Qiqi Liu, Zhongzheng Wang, and Yaochu Jin. Machine-learning-accelerated
multi-objective design of fractured geothermal systems. Nexus, 1(4):100044, 2024
69. Xuemin Yan, Yan Xiao, and Yaochu
Jin. Generative
large language models explained. IEEE Computational Intelligence
Magazine, 19(4): 45 – 46, 2024
Interactive version: https://ieeexplore.ieee.org/document/10709782/interactive
70. Zhenshou Song, Handing Wang, Bing Xue, Mengjie Zhang, and Yaochu Jin. Balancing objective optimization and constraint satisfaction in expensive constrained evolutionary multi-objective optimization. IEEE Transactions on Evolutionary Computation, 28(5): 1286 – 1300, 2024
71. Danial Yazdani, Mohammad Nabi Omidvar, Donya Yazdani, Juergen Branke, Trung Thanh Nguyen, Amir H. Gandomi, Yaochu Jin and Xin Yao. Robust optimization over time: A critical review. IEEE Transactions on Evolutionary Computation, 28(5): 1265 – 1285, 2024
72. Hangyu Zhu, Xilu Wang, and Yaochu Jin. Federated
many-task Bayesian optimization. IEEE Transactions on
Evolutionary Computation, 28(4): 980 – 993, 2024
73. 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, 54(10): 6280 – 6292, 2024
74. Foivos Ntelemis, Yaochu Jin and Spencer Thomas. A generic
self-supervised framework of learning invariant discriminative features.
IEEE Transactions on Neural Networks and Learning Systems, 35(9): 12938 – 12952, 2024
75.
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, 54(9): 5529 – 5542, 2024
76. Yuanchao Liu, Jianchang Liu, Jinliang Ding, Shangshang Yang, and Yaochu Jin. A surrogate-assisted differential evolution with knowledge transfer for expensive incremental optimization problems. IEEE Transactions on Evolutionary Computation, 28(4): 1039 – 1053, 2024
77.
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, 8(5): 3263 –
3278, 2024
78.
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, 8(5): 3589-3602, 2024
79. Xiaoyu Tan, Chao Qu, Junwu Xiong, James
Zhang, Xihe Qiu, and Yaochu Jin. Model-based off-policy
deep reinforcement learning with model-embedding. IEEE Transactions on
Emerging Technologies in Computational Intelligence, 8(4): 2974-2986, 2024
80. Qiqi Liu, Leming Wu, and Yaochu Jin. Federated
Bayesian optimization via compressed sensing. Information Sciences,
681:121148, 2024
81.
Yong Pang, Shuai Zhang, Yaochu Jin, Yitang Wang, Xiaonan Lai,
Xueguan Song. Surrogate
information transfer and fusion in high-dimensional expensive optimization
problems. Swarm and Evolutionary Computation, 88: 101586, 2024
82. Zhifeng Hao, Yaochu Jin,
Xueming Yan, Chuyue Wang, Shangshang Yang, Hong Ge. Cross-modal
hashing retrieval with compatible triplet representation. Neurocomputing,
602:128293, 2024
83.
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, 8(2): 1894 –
1909, 2024
84.
Leming Wu,
Yaochu Jin, Yuping Yan, Kuangrong
Hao. FL-OTCSEnc: Towards secure federated learning with deep
compressed sensing. Knowledge-Based Systems, 291: 111534, 2024
85. Peng Yue, Yaochu Jin, Xuewu Dai, Zhenhua Feng, and Dongliang
Cui. Reinforcement
learning for scalable train timetable rescheduling with graph representation.
IEEE Transactions on Intelligent Transportation Systems, 25(7): 6472 – 6485,
2024
86. Guoyang Xie, Jinbao Wang, Jiaqi Liu,
Yong Liu, Chengjie Wang, Feng Zheng, and Yaochu Jin. IM-IAD: Industrial image anomaly
detection benchmark in manufacturing. IEEE Transactions on Cybernetics,
54(5): 2720 – 2733, 2024
87.
Wenxuan Fang, Wei Du, Renchu
He, Yang Tang, Yaochu Jin. Diffusion
model-based multiobjective optimization for gasoline
blending scheduling. IEEE Computational Intelligence Magazine,
19(2): 61 – 76, 2024
88.
Zhen
Yang, Jie Zhang, Yunliang Jiang, and Yaochu Jin. An energy-efficient
convolution-based partitioned collaborative perception algorithm for
large-scale IoT services. IEEE Transactions on Industrial Informatics,
20(5): 7404 – 7413, 2024
89. Shuangming Yang, Haowen Wang, Yanwei Pang, Yaochu Jin, Bernable
Linares-Barranco. Integrating
visual perception with decision making in neuromorphic fault-tolerant
quadruplet-spike learning framework. IEEE Transactions on Systems, Man,
and Cybernetics: Systems, 54(3): 1502 – 1514, 2024
90.
Shiqing
Liu, Xueming Yan, and Yaochu Jin. An
edge-aware graph autoencoder trained on scale-imbalanced data for travelling
salesman problems. Knowledge-Based Systems, 291: 111559, 2024
91. Xiangyu Wang, Xuemin Yan, and Yaochu Jin. A graph
neural network with negative message passing and uniformity maximization for
graph coloring. Complex & Intelligent Systems, 10: 4445–4455, 2024
92. Fei Ming, Wenyin Gong, and Yaochu Jin. Even search in a promising region for constrained multi-objective optimization. IEEE/CAA Journal of Automatica Sinica, 11(2): 474–486, 2024
93. Qiqi Liu, Yuping Yan, Yaochu Jin, Xilu Wang, Peter Ligeti, Guo Yu, Xueming Yan. Secure federated evolutionary optimization - A survey. Engineering, 34: 23-42, 2024
94. Qiqi Liu, Yuping Yan, Peter Ligetti, and Yaochu Jin. A secure federated data-driven evolutionary multi-objective optimization algorithm. IEEE Transactions on Emerging Topics in Computational Intelligence, 8(1): 191 – 205, 2024
95. Hongbin Li, Chaojun Ma, Chuanji Zhang, Qing Chen, Cheng He, and Yaochu
Jin. A knowledge-based cooperative co-evolutionary algorithm for
non-contact voltage measurement. IEEE Transactions on Emerging
Topics in Computational Intelligence, 8(2): 1142 – 1155, 2024
96. Qiqi Liu, Yuping Yan, and Yaochu Jin. Privacy-preserving federated Bayesian optimization with learnable noise. Information Sciences, 653: 119739, 2024
97. Peng Yue, Yaochu Jin, Xuewu Dai, Zhenjua Feng, and Donglin Cui. Reinforcement learning for online dispatching policy in real-time train timetable rescheduling. IEEE Transactions on Intelligent Transportation Systems, 25(1): 478 – 490, 2024
98. Huiting Li, Yaochu Jin and Tianyou Chai. Evolutionary
multi-objective Bayesian optimization based on multisource online transfer
learning. IEEE Transactions on Emerging Topics in Computational
Intelligence, 24(1): 488 – 502, 2024
99. Jiaqi Liu, Guoyang Xie, Jingbao Wang, Shangnian Li, Chengjie Wang, Feng Zheng, and Yaochu Jin. Deep industrial image anomaly detection: A survey. Machine Intelligence Research, 21: 104–135, 2024
100.
Hongliang Guo, Qihang
Peng, Zhiguang Cao, and Yaochu Jin. DRL-searcher:
A unified approach to multirobot efficient search for a moving target.
IEEE Transactions on Neural Networks and Learning Systems, 35(3): 3215 – 3228, 2024
101.
Yuping Yan, Mohammed B.M.
Kamel, Marcell Zoltay, Marcell Gal, Roland Hollos, Yaochu Jin, Peter
Ligeti and Akos Tenyi. FedlabX: A practical and privacy-preserving framework for
federated learning. Complex & Intelligent Systems, 10: 677–690, 2024
102.
Xueming Yan, Han Huang, Yaochu
Jin, Liang Chen, Zhanning Liang, and Zhifeng Hao. Neural
architecture search via multi-hashing embedding and graph tensor networks for
multilingual text classification. IEEE Transactions on Emerging
Topics in Computational Intelligence, 8(1): 350 – 363, 2024
103. Lianbo Ma, Nan Li, Guo Yu, Xiaoyu Geng, Shi Cheng, Xingwei Wang, Min Huang, and Yaochu Jin. Pareto-wise ranking classifier for multi-objective evolutionary neural architecture search. IEEE Transactions on Evolutionary Computation, 28(3): 570 – 581, 2024
104. Zhichao Lu, Ran Cheng, Yaochu Jin, Kay Chen Tan, and Kalyanmoy Deb. Neural architecture search as multiobjective optimization benchmarks: Problem formulation and performance assessment. IEEE Transactions on Evolutionary Computation, 28(2): 323 – 337, 2024
105. Cheng He, Ran Cheng, Lianghao Li, Tan Kay Chen, and Yaochu Jin. Evolutionary large-scale multiobjective optimization using reformulation based decision variable analysis. IEEE Transactions on Evolutionary Computation, 28(1): 47 – 61, 2024
106. Xinjie Wang, Yaochu Jin, Wenli Du, and Jun Wang. Evolving dual-threshold Bienenstock-Cooper-Munro learning rules in Echo State Networks. IEEE Transactions on Neural Networks and Learning Systems, 35(2): 1572 – 1583, 2024
107.
Haofeng Wu, Qingda Chen, Yaochu Jin,
Jinliang Ding, and Tianyou Chai. A surrogate-assisted
expensive constrained multi-objective optimization algorithm based on adaptive
switching of acquisition functions. IEEE Transactions on Emerging
Technologies in Computational Intelligence, 8(2): 2050 - 2064, 2024
108.
Wanting Zhang, Wei Du, Guo
Yu, Renchu He, Wenli Du, and Yaochu Jin. Knowledge-assisted
dual-stage evolutionary optimization of large-scale crude oil scheduling. IEEE
Transactions on Emerging Topics in Computational Intelligence, 8(2): 1567 – 1581, 2025
109.
Yaqing Hou, Mingyang Sun,
Yifeng Zeng, Yew-Soon Ong, Yaochu Jin, Hongwei Ge, and Qiang Zhang. A
multi-agent cooperative learning system with evolution of social robots.
IEEE Transactions on Evolutionary Computation, 28(2), 2024
110.
Mengxuan Zhang, Long Liu, Yaochu Jin,
Zhiku Lei, Zhigang Wang, and Licheng Jiao. Tree-shaped
multi-objective evolutionary CNN for hyperspectral image classification. Applied
Soft Computing, 152, Article No. 111174, 2024
111. Fei Li, Zhengkun Shang, Yuanchao Liu, Hao Shen, and Yaochu Jin. Inverse distance weighting and radial basis function based surrogate model for high-dimensional expensive multi-objective optimization. Applied Soft Computing, 152:11194, 2024
112. Yaochu Jin. Computational evolution of neural and morphological systems. Springer, 2023
113. Zhaoxin Wang, Handing Wang, Cong Tian, and Yaochu Jin. Adversarial training of deep neural networks guided by texture and structural information. The 31st ACM International Conference on Multimedia (ACM MM 2023), Ottawa, Canada, Oct 29-Nov 3, 2023
114. Peng Liao, Yaochu Jin and Wenli Du. EMT-NAS: Transferring architectural knowledge between tasks from different datasets. The IEEE/CVF Conference on Computer Vision and Pattern Recognition 2023 (CVPR 2023), Vancouver, Canada, June 18-22, 2023
115. Guoyang Xie, Jinbao Wang, Jiaqi Liu, Yaochu Jin, and Feng Zheng. Pushing the limits of fewshot anomaly detection in industry vision: Graphcore. The Eleventh International Conference on Learning Representations (ICLR 2023), Kigali, Rwanda, May 1-5, 2023
116. Lingrui Zhang, Shuheng Zhang, Guoyang Xie, Jiaqi Liu, Hua Yan, Jinbao Wang, Feng Zheng, and Yaochu Jin. What makes a good data augmentation for few-shot unsupervised image anomaly detection? CVPR 2023 Workshop
117. Haoran Gu, Handing Wang, and Yaochu Jin. Effects of Pareto set on the performance of problem reformulation-based large-scale multiobjective optimization algorithms. Congress on Evolutionary Computation, Chicago, USA, July 1-5, 2023
118. Shiqing Liu, Xilu Wang, and Yaochu Jin. Federated Bayesian optimization for privacy-preserving neural architecture search. Congress on Evolutionary Computation, Chicago, USA, July 1-5, 2023
119.
Shiqing Liu, Xueming Yan,
and Yaochu Jin. End-to-end Pareto set
prediction with graph neural networks for multi-objective facility location.
Evolutionary Multi-Criterion Optimization (EMO2023)
120.
Lianbo Ma, Yang Liu, Guo
Yu, Xinzhe Wang, Hongwei Mo, Gai-Ge Wang, Yaochu Jin, Ying Tan. Decomposition-based
multi-objective optimization for variable-length mixed-variable Pareto
optimization and its application in cloud service allocation. IEEE
Transactions on Systems, Man and Cybernetics: Systems, 53(11): 7138 – 7151, 2023
121.
Hongliang Guo, Wenda
Sheng, Chen Gao, and Yaochu Jin. DRL-Router:
Distributional reinforcement learning based router for the reliable shortest
path problems. IEEE Intelligent Transportation Systems Magazine,
15(5):
91 – 108, 2023
122.
Xilu Wang, Yaochu Jin,
Sebastian Schmitt, and Markus Olhofer. Alleviating
search bias in Bayesian evolutionary optimization with many heterogeneous
objectives. IEEE Transactions on Systems, Man, and Cybernetics:
Systems, 54(1): 143 – 155, 2023
123.
Guoyang Xie, Yawen Huang,
Jinbao Wang, Jiayi Lyu, Feng Zheng, Yefeng Zheng, and Yaochu Jin. Cross-modality
neuroimage synthesis: A survey. ACM Computing Surveys, 56(3): 80, 2023
124.
Nan Li, Lianbo Ma, Guo Yu,
Bing Xie, Mengjie Zhang, and Yaochu Jin. Survey on
evolutionary deep learning: Principles, algorithms, applications, and open
issues. ACM Computing Surveys, 56(2): Article No. 41, 2023
125.
Qiqi Liu, Felix Lanfermann,
Tobias Rodemann, Markus Olhofer, and Yaochu Jin. Surrogate-assisted
many-objective optimization of building energy management. IEEE
Computational Intelligence Magazine, 18(4): 14 – 28, 2023
126.
Hui Bai, Ran Cheng, Danial
Yazdani, Kay Chen Tan, and Yaochu Jin. Evolutionary
large-scale dynamic optimization using bi-level variable grouping. IEEE
Transactions on Cybernetics, 5(11): 6937 – 6950, 2023
127.
Xueming Yan, Zhihang Fang
and Yaochu Jin. An adaptive n-gram transformer for multi-scale scene text recognition.
Knowledge-Based Systems, 280: 110964, 2023
128.
Dinghua Xue, Tao Lei,
Shuangming Yang, Zhiyong Lv, Tongfei Liu, Yaochu Jin and Asoke K. Nandi.
Triple
change detection network via joint multi-frequency and full-scale
swin-transformer for remote sensing images. IEEE Transactions on
Geoscience and Remote Sensing, 61: 4408415, 2023
129.
Jia Liu and Yaochu Jin.
A
comprehensive survey of robust deep learning in computer vision. Journal
of Automation and Intelligence, 2(4): 175-195, 2023
130.
Tao Lei, Yetong Xu,
Hailong Ning, Zhiyong Lv, Chongdan Min, Yaochu Jin and Asoke K. Nandi. Lightweight
structure-aware transformer network for VHR remote sensing image change
detection. Geoscience and Remote Sensing Letters, 23: 6000305, 2023
131.
Zhun Fan,
Zhaojun Wang, Wenji Li, Xiaomin Zhu, Bingliang Hu,
An-Min Zou, Weidong Bao, Minqiang Gu, Zhifeng Hao and Yaochu Jin.
Automated pattern generation for swarm robots using constrained
multi-objective genetic programming. Swarm and Evolutionary
Computation, 81, 101337, 2023
132.
Xi Zhang, Yaochu Jin,
and Feng Qian. A
self-adaptive dynamic multi-objective optimization algorithm based on transfer
learning and elitism-based mutation.
Neurocomputing, 559: 126761, 2023
133.
Ye Tian, Xiaopeng Li,
Haiping Ma, Xingyi Zhang, Kay Chen Tan, and Yaochu Jin. Deep
reinforcement learning based adaptive operator selection for evolutionary
multi-objective optimization. IEEE Transactions on Emerging
Topics in Computational Intelligence, 7(4): 1051 – 1064, 2023
134.
Cuie Yang, Jinliang Ding, Yaochu
Jin, and Tianyou Chai. A
data stream ensemble assisted multifactorial evolutionary algorithm for offline
data-driven dynamic optimization. Evolutionary
Computation, 31 (4): 433–458, 2023
135.
Minyang Chen, Wei Du, Yang
Tang, Yaochu Jin, and Gary G. Yan. A
decomposition method for both additively and non-additively separable problems.
IEEE Transactions on Evolutionary Computation, 27(6): 1720 – 1734, 2023
136.
Xueming Yan, Yaochu Jin,
Xiaohua Ke, and Zhifeng Hao. Multi-task
evolutionary optimization of multi-echelon location routing problems via a
hierarchical fuzzy graph. Complex &
Intelligent Systems, 9: 6845–6862, 2023
137.
Shuai Wang, Beichen Ding, and Yaochu Jin. A multi-factorial
evolutionary algorithm with asynchronous optimization processes for solving the
robust influence maximization problem. IEEE
Computational Intelligence Magazine, 18(3): 41 – 53, 2023
138.
Haoran Gu, Handing Wang,
and Yaochu Jin. Surrogate-assisted
differential evolution with adaptive multi-subspace search for large-scale
expensive optimization. IEEE Transactions
on Evolutionary Computation, 27(6): 1765 – 1779, 2023
139.
Guoyang Xie, Jinbao Wang, Guo
Yu, Jiayi Lyu, Feng Zheng, and Yaochu Jin. Tiny adversarial multi-objective one-shot neural architecture search.
Complex & Intelligent Systems, 9: 6117–6138, 2023
140.
Xilu Wang and Yaochu
Jin. Personalized Bayesian optimization for noisy problems. Complex
& Intelligent Systems, 9: 5745–5760, 2023
141.
Hangyu Zhu, Rui Wang, Yaochu
Jin, and Kaitai Liang. PIVODL:
Privacy-preserving vertical federated learning over distributed labels.
IEEE Transactions on Artificial Intelligence, 4(5): 988 – 1001, 2023
142. Cheng He, Lianghao Li, Ran Cheng and Yaochu Jin. Evolutionary multiobjective optimization via efficient sampling-based offspring generation. Complex & Intelligent Systems, 9: 4977–4993, 2023
143. Tuo Zhang, Handing Wang, Bo Yuan, Yaochu Jin, and Xin Yao. Surrogate-assisted evolutionary Q-learning for black-box dynamic time-linkage optimization problems. IEEE Transactions on Evolutionary Computation, 27(5):1162-1176, 2023
144.
Zhening Liu, Handing Wang
and Yaochu Jin. Performance indicator based adaptive model selection for offline
data-driven multi-objective evolutionary optimization. IEEE
Transactions on Cybernetics, 53(10): 6263-6276, 2023
145.
Leming
Wu, Yaochu Jin, Kuangrong Hao. Optimized
compressed sensing for communication efficient federated learning. Knowledge-Based
Systems, 278, Article No. 110805, 2023
146. Yan Zhou, Yaochu Jin, Yao Sun, and Jinliang Ding. Surrogate-assisted cooperative co-evolutionary reservoir architecture search for liquid state machines. IEEE Transactions on Emerging Topics in Computational Intelligence, 7(5): 1484 – 1498, 2023
147. Zhenshou Song, Handing Wang and Yaochu Jin. A surrogate-assisted evolutionary framework with regions of interests-based data selection for expensive constrained optimization, IEEE Transactions on Systems, Man and Cybernetics: Systems, 53(1): 6268-6280, 2023
148. Shufen Qin, Chaoli Sun, Qiqi Liu, and Yaochu Jin. A performance indicator-based infill criterion for expensive multi-/many-objective optimization. IEEE Transactions on Evolutionary Computation, 27(4): 1085-1099, 2023
149. Xilu Wang, Yaochu Jin, Sebastian Schmitt and Markus Olhofer. Recent advances in Bayesian Optimization. ACM Computing Surveys, 55:287, 2023
150. Zhihua Liu, Lei Tong, Long Chen, Zheheng Jiang, Feixiang Zhou, Qianni Zhang, Xiangrong Zhang, Yaochu Jin, and Huiyu Zhou. Deep Learning Based Brain Tumor Segmentation: A Survey. Complex & Intelligent Systems, 9:1001–1026, 2023
151. Jinbao Wang, Guoyang Xie, Yawen Huang, Jiayi Lyu, Feng Zheng, and Yaochu Jin. FedMed-GAN: Federated domain translation on unsupervised cross-modality brain image synthesis. Neurocomputing, 546:126282, 2023
152. Rongsheng Wang, Qi Zhang, Xuewu Dai, Zhiming Yuan, Tao Zhang, Shuxin Ding, and Yaochu Jin. An efficient evolutionary algorithm for high-speed train rescheduling under a partial station blockage. Applied Soft Computing, 110590, 2023
153. Meirong Chen, Yinan Guo, Yaochu Jin, Shengxiang Yang, Dunwei Gong, and Zekuan Yu. An environment-driven hybrid evolutionary algorithm for dynamic multi-objective optimization problems. Complex & Intelligent Systems, 9:659–675 (2023)
154. Yapei Wu, Xingguang Peng, Handing Wang, Yaochu Jin, and Demin Xu. Cooperative coevolutionary CMA-ES with landscape-aware grouping in noisy environments. IEEE Transactions on Evolutionary Computation, 27(3): 686-700, 2023
155. Shuai Wang, Yaochu Jin, and Ming Cai. Enhancing the robustness of networks against multiple damage models using a multifactorial evolutionary algorithm. IEEE Transactions on Systems, Man and Cybernetics: Systems, 53(7):4176-4188, 2023
156. Jia Liu, Ran Cheng, and Yaochu Jin. Bi-fidelity evolutionary multiobjective search for adversarially robust deep neural architectures. Neurocomputing, 550: 126465, 2023
157.
Xi Zhang, Guo Yu, Yaochu
Jin, Feng Qian. An adaptive Gaussian process based manifold transfer learning to
expensive dynamic multi-objective optimization. Neurocomputing,
538, No. 126212, 2023
158. Tao Lei, Xinzhe Geng, Hailong Ning, Zhiyong Lv, Maoguo Gong, Yaochu Jin, and Asoke K. Nandi. Ultra-light spatial-spectral feature cooperation network for change detection in remote sensing images. Transactions on Geoscience and Remote Sensing, 61, Article No: 4402114, 2023
159. Meng Wu, Xiaomin Zhu, Li Ma, Weidong Bao, Zhun Fan, Yaochu Jin. Multi-robot target entrapment using cooperative hierarchical gene regulatory network. Swarm and Evolutionary Computation, 80, No. 101310, 2023
160. Xi Zhang, Guo Yu, Yaochu Jin, Feng Qian. Elitism-based transfer learning and diversity maintenance for dynamic multi-objective optimization. Information Sciences, 636, No.118927, 2023
161. Yuanchao Liu, Jianchang Liu, Yaochu Jin, Fei Li and Tianzi Zheng. A surrogate-assisted two-stage differential evolution for expensive constrained optimization. IEEE Transactions on Emerging Technologies in Computational Intelligence, 7(3):715-730, 2023
162. Shangshang Yang, Haoyu Wei, Haiping Ma, Ye Tian, Xingyi Zhang, Yunbo Cao, and Yaochu Jin. Cognitive diagnosis-based personalized exercise group assembly via a multi-objective evolutionary algorithm. IEEE Transactions on Emerging Topics in Computational Intelligence, 7(3):829-844, 2023
163.
Xi Zhang, Guo Yu, Yaochu
Jin, and Feng Qian. An adaptive Gaussian process based manifold transfer learning to expensive
dynamic multi-objective optimization. Neurocomputing,
538:126212, 2023
164. Ye Tian, Jingwen Pan, Shangshang Yang, Xingyi Zhang, Shuping He, and Yaochu Jin. Imperceptible and sparse adversarial attacks via a dual-population based constrained evolutionary algorithm. IEEE Transactions on Artificial Intelligence, 4(2): 268 – 281, 2023
165. Xi Zhang, Guo Yu, Yaochu Jin, and Fen Qian. Elitism-based transfer learning and diversity maintenance for dynamic multi-objective optimization. Information Sciences, 636:118927, 2023
166. Shuangming Yang, Yanwei Oang, Tao Lei, and Yaochu Jin. Spike-driven multi-scale learning with hybrid mechanisms of spiking dendrites. Neurocomputing, 542:120246, 2023
167. Ye Tian, Xinyi Zhang, Cheng He Cheng, Kay Chen Tan, and Yaochu Jin. Principled design of translation, scale, and rotation invariant variation operators for metaheuristics. Chinese Journal of Electronics, 23(1), 2023
168. Hui Bai, Ran Cheng, and Yaochu Jin. Evolutionary reinforcement learning: A survey. Intelligent Computing, 0025, April 2023. DOI: 10.34133/icomputing.0025
169. Guo Yu, Yaochu Jin, Markus Olhofer, Qiqi Liu, and Wenli Du. Solution set augmentation for knee identification in multiobjective decision analysis. IEEE Transactions on Cybernetics, 53(4): 2480-2493, 2023
170. Zhen Yang, Jie Zhang, Yunliang Jiang, and Yaochu Jin. A self-organizing IoT service perception algorithm based on human visual direction sensitive system. IEEE Internet of Things Journal, 10(7): 6193-6204, 2023
171. Yan Xiao, Yaochu Jin, and Kuangrong Hao. Adaptive prototypical networks with label words and joint representation learning for few-shot relation classification. IEEE Transactions on Neural Networks and Learning Systems, 34(3): 1406 – 1417, 2023
172. Ye Tian, Weijian Zhu, Xingyi Zhang, and Yaochu Jin. A practical tutorial on solving optimization problems via PlatEMO. Neurocomputing, 518: 190-205, 2023
173. Xilu Wang and Yaochu Jin. Knowledge transfer based on particle filters for multi-objective optimization. Mathematical and Computational Applications, Special Issue on “Evolutionary Multi-objective Optimization: An Honorary Issue Dedicated to Professor Kalyanmoy Deb. 28(1), 14, 2023
174. Shiqiang Zhu, Ting Yu, Tao Xu, Hongyang Chen, Schahram Dustdar, Sylvain Gigan, Deniz Gunduz, Ekram Hossain, Yaochu Jin, Feng Lin, Bo Liu, Zhiguo Wan, Ji Zhang, Zhifeng Zhao, Wentao Zhu, Zuoning Chen, Tariq Durrani, Huaimin Wang, Jiangxing Wu, Tongyi Zhang, Yunhe Pan. Intelligent computing: The latest advances, challenges, and future. Intelligent Computing, 0006, 2023 DOI: 10.34133/icomputing.0006
175. Ye Tian, Langchun Si, Xingyi Zhang, Kay Chen Tan, and Yaochu Jin. Local model based Pareto front estimation for multi-objective optimization. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 53(1): 623-634, 2023
176. Yaochu Jin, Hangyu Zhu, Jinjin Xu, and Yang Chen. Federated Learning: Fundamentals and Advances. Springer. 2022
177. Yitian Hong, Yaochu Jin, and Yang Tang. Rethinking individual global max in cooperative multi-agent reinforcement learning. The Thirty-Sixth Annual Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans, USA, November 26 - December 4, 2022
178. Guoyang Xie, Jinbao Wang, Yawen Huang, Yefeng Zheng, Feng Zheng, and Yaochu Jin. FedMed-ATL: Misaligned unpaired brain image synthesis via affine transform loss. The 30th ACM International Conference on Multimedia (ACM MM 2022), Lisboa, Portugal, October 10 - 14, 2022
179. Shiqing Liu, Haoyu Zhang, and Yaochu Jin. A survey on computationally efficient neural architecture search. Journal of Automation and Intelligence, 1(1): 100002, 2022
180. Jinghao Zhang, Zhenhua Feng, Guosheng Hu and Yaochu Jin. MixProp: Towards high-performance image recognition via dual batch normalisation. International Workshop on Multimodal Video Search by Examples. BMVC 2022 Workshop Proceedings, 24th November 2022
181. Lianghao Li, Cheng He, Ran Cheng, Hongbin Li, Linqiang Pan, and Yaochu Jin. A fast sampling based evolutionary algorithm for million-dimensional multiobjective optimization. Swarm and Evolutionary Computation, 75, 101181, 2022
182. Xiaoshu Xiang, Ye Tian, Ran Cheng, Xingyi Zhang, Shengxiang Yang and Yaochu Jin. A benchmark generator for online dynamic single-objective and multi-objective optimization problems. Information Sciences, 613: 591-608, 2022
183. Shaotao Chen, Xihe Qiu, Xiaoyu Tan, Zhijun Fang, and Yaochu Jin. A model-based hybrid soft actor-critic deep reinforcement learning algorithm for optimal ventilator settings. Information Sciences, 611:47-64, 2022
184. Qiqi Liu, Yaochu Jin, Martin Heiderich, and Tobias Rodemann. Coordinated Adaptation of Reference Vectors and Scalarizing Functions in Evolutionary Many-objective Optimization. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 53(2): 763 – 775, 2022
185. Foivos Ntelemis, Yaochu Jin, and Spencer A. Thomas. Information maximization clustering via multi-view self-labelling. Knowledge-Based Systems, 250: 109042, 2022
Code uploaded in GitHub
186. Ye Tian, Haowen Chen, Haiping Ma, Xingyi Zhang, Kay Chen Tan and Yaochu Jin. Integrating conjugate gradients into evolutionary algorithms for large-scale continuous multi-objective optimization. IEEE/CAA Journal of Automatica Sinica, 9(10): 1801–1817, 2022
187. Xiangyu Wang, Bingran Zhang, Jian Wang, Kai Zhang, and Yaochu Jin. A cluster-based competitive particle swarm optimizer with a sparse truncation operator for multi-objective optimization. Swarm and Evolutionary Computation, 71:101083, 2022
188. Patrick Brosnan, Guohong Tian, Hongguang Zhang, Zhong Wu, and Yaochu Jin. Non-linear and multi-domain modelling of a permanent magnet linear synchronous machine for free piston engine generators. Energy Conversion and Management: X, 14:100195, 2022
189. Qiqi Liu, Yaochu Jin, Martin Martin Heiderich, and Tobias Rodemann. Surrogate-assisted evolutionary optimization of expensive many-objective irregular problems. Knowledge-Based Systems, 240:108197, 2022
190. Ye Tian, Shichen Peng, Shangshang Yang, Xingyi Zhang, Kay Chen Tan and Yaochu Jin. Action command encoding for surrogate assisted neural architecture search. IEEE Transactions on Cognitive and Developmental Systems, 14(3): 1129 – 1142, 2022
191. Foivos Ntelemis, Yaochu Jin, and Spencer A. Thomas. Image clustering using an augmented generative adversarial network and information maximization. IEEE Transactions on Neural Networks and Learning Systems, 33(12): 7461 – 7474, 2022
192. Tonghao Wang, Xingguang Peng, Yaochu Jin and Demin Xu. Experience sharing based memetic transfer learning for multiagent reinforcement learning. Memetic Computing, 14:3–17, 2022
193. Qiqi Liu, Yaochu Jin, Martin Heiderich, Tobias Rodemann and Guo Yu. An adaptive reference vector guided evolutionary algorithm using growing neural gas for many-objective optimization of irregular problems. IEEE Transactions on Cybernetics, 52(5): 2698 – 2711, 2022
194. Ye Tian, Yuandong Feng, Chao Wang, Ruifen Cao, Xingyi Zhang, Xi Pei, Kay Chen Tan, and Yaochu Jin. A large-scale combinatorial many-objective evolutionary algorithm for intensity-modulated radiotherapy planning. IEEE Transactions on Evolutionary Computation, 26(6): 1511-1525, 2022
195. Guo Yu, Lianbo Ma, Yaochu Jin, Wenli Du, Qiqi Liu, and Hengmin Zhang. A survey on knee-oriented multi-objective evolutionary optimization. IEEE Transactions on Evolutionary Computation, 26(6):1452-1472, 2022
196. Qiqi Liu, Ran Cheng, Yaochu Jin, Martin Heiderich, and Tobias Rodemann. Reference vector assisted adaptive model management for surrogate-assisted many-objective optimization. IEEE Transactions on Systems, Man, and Cybernetics – Systems, 52(12): 7760-7773, 2022
197. Sutong Wang, Dujuan Wang, Yunqiang Yin, Yanzhang Wang, and Yaochu Jin. Interpretability-based multimodal convolutional neural networks for skin lesion diagnosis. IEEE Transactions on Cybernetics, 52(12): 12623-12637, 2022
198. Sheng Qi, Juan Zou, Shengxiang Yang, Yaochu Jin, Jinhua Zheng, Xu Yang. A self-exploratory competitive swarm optimization algorithm for large-scale multiobjective optimization. Information Sciences, 609: 1601-1620, 2022
199. Haoyu Zhang, Yaochu Jin, and Kuangrong Hao. Evolutionary search for complete neural network architectures with partial weight sharing. IEEE Transactions on Evolutionary Computation, 26(5): 1072-1086, 2022
200. Xiangyu Wang, Kai Zhang, Jian Wang, and Yaochu Jin. An Enhanced competitive swarm optimizer with strongly convex sparse operator for large-scale multi-objective optimization. IEEE Transactions on Evolutionary Computation, 26(5): 859-871, 2022
201. Xinjie Wang, Yaochu Jin and Kuangrong Hao. Computational modeling of structural synaptic plasticity in echo state networks. IEEE Transactions on Cybernetics, 52(10): 11254-11266, 2022
202. Shangshang Yang and Ye Tian and Cheng He and Xingyi Zhang and Kay Chen Tan, and Yaochu Jin. A gradient guided evolutionary approach to training deep neural networks. IEEE Transactions on Neural Networks and Learning Systems, 33(9): 4861-4875, 2022
203. Ye Tian, Yajie Zhang, Yansen Su, Xingyi Zhang, Kay Chen Tan, and Yaochu Jin. Balancing objective optimization and constraint satisfaction in constrained evolutionary multi-objective optimization. IEEE Transactions on Cybernetics, 52(9): 9559-9572, 2022
204. Ye Tian, Chang Lu, Xingyi Zhang, Fan Cheng, and Yaochu Jin. A pattern mining based evolutionary algorithm for large-scale sparse multi-objective optimization problems. IEEE Transactions on Cybernetics, 52(7): 6784-6797, 2022
205. Xilu Wang, Yaochu Jin, Sebastian Schmitt, and Markus Olhofer. Transfer learning based co-surrogate assisted evolutionary bi-objective optimization for objectives with non-uniform evaluation times. Evolutionary Computation, 30 (2): 221–251, 2022
206. Xiaoshu Xiang, Ye Tian, Xingyi Zhang, Jianhua Xiao and Yaochu Jin. A pairwise proximity learning-based ant colony algorithm for dynamic vehicle routing problems. IEEE Transactions on Intelligent Transportation Systems, 23(6): 5275 – 5286, 2022
207. Jianchang Liu, Yuanchao Liu, Yaochu Jin, and Fei Li. A decision variable assortment based evolutionary algorithm for dominance robust multi-objective optimization. IEEE Transactions on Systems, Man and Cybernetics: Systems, 52(5): 3360 – 3375, 2022
208. Hangyu Zhu and Yaochu Jin. Real-time federated evolutionary neural architecture search. IEEE Transactions on Evolutionary Computation, 26(2): 364-378, 2022
209. Qing Chen, Yaochu Jin and Yongduan Song. Fault-tolerant adaptive tracking control of Euler-Lagrange systems — An echo state network approach driven by reinforcement learning. Neurocomputing, 481:109-116, 2022
210. Yan Xiao, Yaochu Jin, Ran Cheng, and Kuangrong Hao. Hybrid attention-based transformer block model for distant supervision relation extraction. Neurocomputing, 470: 29-39, 2022
211. Jinjin Xu, Wenli Du, Yaochu Jin, Wangli He, and Ran Cheng. Ternary compression for communication-efficient federated learning. IEEE Transactions on Neural Networks and Learning Systems, 33(3): 1162-1176, 2022
212. Dan Guo, Xilu Wang, Kailai Gao, Yaochu Jin, Jinliang Ding, and Tianyou Chai. Evolutionary optimization of high-dimensional multi- and many-objective expensive problems assisted by a dropout neural network. IEEE Transactions on Systems, Man and Cybernetics: Systems, 52(4): 2084-2097, 2022
Matlab code on GitHub
213. Yuanchao Liu, Jianchang Liu, and Yaochu Jin. Surrogate-assisted multi-population particle swarm optimizer for high-dimensional expensive optimization. IEEE Transactions on Systems, Man and Cybernetics: Systems, 52(4): 2084-2097, 2022
214. Yajun Ru, Xihe Qiu, Xiaoyu Tan, Bin Chen, Yongbin Gao, and Yaochu Jin. Sparse-attentive meta temporal point process for clinical decision support, Neurocomputing, 485: 114-123, 2022
215. Dong Han, Wenli Du, Yaochu Jin, Wei Du, and Guo Yu. A fuzzy constraint handling technique for decomposition-based constrained multi- and many-objective optimization. Information Science, 597:318-340, 2022
216. Wei Du, Wenjiang Song, Yang Tang, Yaochu Jin, and Feng Qian. Searching for robustness intervals in evolutionary robust optimization. IEEE Transactions on Evolutionary Computation, 26(1): 58-72, 2022
217. Ye Tian, Langchun Si, Xingyi Zhang, Ran Cheng, Cheng He, Kay Chen Tan, and Yaochu Jin. Evolutionary large-scale multi-objective optimization: A survey. ACM Computing Surveys, 54(8): 174, 2022
218. Xiaojun Zhou, Jianpeng Long, Yaochu Jin, Guo Yu, Chunhua Yang. A fast constrained state transition algorithm. Neurocomputing, 470:29-39, 2022
219. Xihe Qiu, Xiaoyu Tan, Qiong Li, Shaotao Chen, Yajun Ru, and Yaochu Jin. A latent batch-constrained deep reinforcement learning approach for precision dosing clinical decision support. Knowledge-Based Systems, 237, 107689, 2022
220. Yaochu Jin, Handing Wang, Chaoli Sun. Data-Driven Evolutionary Optimization. Springer, June 2021 (Monograph)
221. Ye Tian, Chang Lu, Xingyi Zhang, and Yaochu Jin. Solving large-scale multiobjective optimization problems with sparse optimal solutions via unsupervised neural networks. IEEE Transactions on Cybernetics, 51(6): 3115 – 3128, 2021
222. Ruochen Liu, Jianxia Li, Yaochu Jin and Licheng Jiao. A self-adaptive response strategy for dynamic multi-objective evolutionary optimization based on objective space decomposition. Evolutionary Computation, 29 (4): 491–519, 2021
223. Jinjin Xu, Yaochu Jin, and Wenli Du. A federated data-driven evolutionary algorithm for expensive multi/many-objective optimization. Complex & Intelligent Systems, 7:3093–3109, 2021
224. Ataollah Ramezan Shirazi and Yaochu Jin. Regulated morphogen gradients for target surrounding and adaptive shape formation. IEEE Transactions on Cognitive and Developmental Systems, 13(4): 818-826, 2021
225. Xilu Wang, Yaochu Jin, Sebastian Schmitt, Markus Olhofer, and Richard Allmendinger. Transfer learning based surrogate assisted evolutionary bi-objective optimization for objectives with different evaluation times. Knowledge-Based Systems, 227, 107190, 2021
226. Zhenshou Song, Handing Wang, Cheng He, and Yaochu Jin. A Kriging-assisted two-archive evolutionary algorithm for expensive many-objective optimization. IEEE Transactions on Evolutionary Computation, 25(6):1013-1027, 2021
227. Sutong Wang, Yunqiang Yin, Dujuan Wang, Zehui Lv, Yanzhang Wang, and Yaochu Jin. An interpretable deep neural network for colorectal polyp diagnosis under colonoscopy. Knowledge-Based Systems, 234:107568, 2021
228. Hangyu Zhu, Jinjin Xu, Shiqing Liu and Yaochu Jin. Federated learning on non-iid data: A survey. Neurocomputing, 465: 371-390, 2021
229. Jinjin Xu, Yaochu Jin, Wenli Du, and Sai Gu. A federated data-driven evolutionary algorithm. Knowledge-Based Systems, 233:107532, December 2021
230. Hangyu Zhu, Rui Wang, Yaochu Jin, Kaitai Liang, and Jianting Ning. Distributed additive encryption and quantization for privacy preserving federated deep learning. Neurocomputing, 463: 309-327, 2021
231. Shufen Qin, Chaoli Sun, Yaochu Jin, Ying Tan and Jonathan Fieldsend. Large-scale evolutionary multi-objective optimization assisted by directed sampling. IEEE Transactions on Evolutionary Computation, 25(4): 724 – 738, 2021
Matlab code here
232. Danial Yazdani, Ran Cheng, Donya Yazdani, Juergen Branke, Yaochu Jin, and Xin Yao. A survey of evolutionary continuous dynamic optimization over two decades – Part A. IEEE Transactions on Evolutionary Computation, 25(4): 609 – 629, 2021
233. Danial Yazdani, Ran Cheng, Donya Yazdani, Juergen Branke, Yaochu Jin, and Xin Yao. A survey of evolutionary continuous dynamic optimization over two decades – Part B. IEEE Transactions on Evolutionary Computation, 25(4): 630 – 650, 2021
234. Ye Tian, Ruchen Liu, Xingyi Zhang, Haiping Ma, Kay Chen Tan, and Yaochu Jin. A multi-population evolutionary algorithm for large-scale multi-modal multi-objective optimization problems. IEEE Transactions on Evolutionary Computation, 25(3): 405 – 418, 2021
235. Shuai Wang, Jing Liu and Yaochu Jin. A computationally efficient evolutionary algorithm for multi-objective network robustness optimization. IEEE Transactions on Evolutionary Computation, 25(3): 419 – 432, 2021
236. Cheng He, Ran Cheng, Ye Tian, Xingyi Zhang, Kay Chen Tan, and Yaochu Jin. Paired offspring generation for scalable constrained multiobjective optimization. IEEE Transactions on Evolutionary Computation, 25(3): 448 – 462, 2021
237. Jia Liu and Yaochu Jin. Multi-objective search of robust neural architectures against multiple types of adversarial attacks. Neurocomputing, 453: 73-84, 2021
238. Huangke Chen, Ran Cheng, Witold Pedrycz, and Yaochu Jin. Solving many-objective optimization problems via multistage evolutionary search. IEEE Transactions on Systems, Man and Cybernetics: Systems, 51(6): 3552-3564, 2021
239. Cheng He, Shihua Huang, Ran Cheng, Kay Chen Tan, and Yaochu Jin. Evolutionary multi-objective optimization driven by generative adversarial networks. IEEE Transactions on Cybernetics, 51(6): 3129-3142, 2021
240. Huaming Chen, Fuyi Li, Lei Wang, Yaochu Jin, Chi-Hung Chi, Lukasz Kurgan, Jiangning Song, Jun Shen. Systematic evaluation of machine learning methods for identifying human-pathogen protein-protein interactions. Briefings in Bioinformatics, 22(3): bbaa068, May 2021. https://doi.org/10.1093/bib/bbaa068
241. Xinjie Wang, Yaochu Jin, and Kuangrong Hao. Synergies between synaptic and intrinsic plasticity in echo state networks. Neurocomputing, 432: 32-43, 2021
242. Hangyu Zhu, Haoyu Zhang, and Yaochu Jin. From federated learning to federated neural architecture search: A survey. Complex & Intelligent Systems, 7:639–657, 2021
243. Pengfei Huang, Handing Wang, and Yaochu Jin. Offline data-driven evolutionary optimization based on tri-training. Swarm and Evolutionary Computation, 60:100800, 2021
244. Hao Wang, Chaoli Sun, Guochen Zhang, Jonathan E. Fieldsend, and Yaochu Jin. Non-dominated sorting on performance indicators for evolutionary many-objective optimization. Information Sciences, 551:23-38, 2021
245. Qian Zhang, Jie Lu, and Yaochu Jin. Artificial intelligence in recommender systems. Complex & Intelligent Systems, 7:439–457, 2021
246. Sampo Kuutti, Richard Bowden, Yaochu Jin, Phil Barber, and Saber Fallah. A survey of deep learning applications to autonomous vehicle control. IEEE Transactions on Intelligent Transportation Systems, 22(2): 712 – 733, 2021
247. Haoyu Zhang, Yaochu Jin, Ran Cheng, and Kuangrong Hao. Efficient evolutionary search of attention convolutional networks via sampled training and node inheritance. IEEE Transactions on Evolutionary Computation, 25(2): 371 – 385, 2021
248. Hangyu Zhu and Yaochu Jin. Toward real-time federated evolutionary neural architecture search. In: N. Pillay and R. Qu (eds.), Automated Design of Machine Learning and Search Algorithms, Natural Computing Series, Springer, 2021. https://doi.org/10.1007/978-3-030-72069-8_8
249. Peng Liao, Chaoli Sun, Guochen Zhang and Yaochu Jin. Multi-surrogate multi-tasking optimization of expensive problems. Knowledge-Based Systems, 551: 23-38, 2021
250. Handing Wang, Liang Feng, Yaochu Jin, John Doherty. Surrogate-assisted evolutionary multitasking for expensive minimax optimization in multiple scenarios. IEEE Computational Intelligence Magazine, 16(1): 34-48, 2021
251. Guo Yu, Yaochu Jin, and Markus Olhofer. A multi-objective evolutionary algorithm for finding knee regions using two localized dominance relationships. IEEE Transactions on Evolutionary Computation, 25(1):145-158, 2021 Code available at GitHub
252. Ye Tian, Tao Zhang, Jianhua Xiao, Xingyi Zhang, and Yaochu Jin. A coevolutionary framework for constrained multi-objective optimization problems. IEEE Transactions on Evolutionary Computation, 25(1):102-116, 2021
253. Shuai Wang, Jing Liu and Yaochu Jin. Finding influential nodes in multiplex networks using a memetic algorithm. IEEE Transactions on Cybernetics, 51(2): 900-912, 2021
254. Yicun Hua, Qiqi Liu, Kuangrong Hao, and Yaochu Jin. A survey of evolutionary algorithms for multi-objective optimization problems with irregular Pareto fronts. IEEE/CAA Journal of Automatica Sinica, 8(2): 303-318, 2021
255. Lucas Z. Bissaro, Yaochu Jin, and Murillo G. Carneiro. Regular echo state networks: simple and accurate reservoir models to real-world applications. SAC 2021: 1063-1069
256.
Dujuan Wang, Yunqiang Yin,
and Yaochu Jin. Rescheduling Under Disruptions in Manufacturing Systems.
Springer, Singapore, 2020 (Monograph)
257. Ye Tian, Shichen Peng, Xingyi Zhang, Tobias Rodemann, Kay Chen Tan, and Yaochu Jin. A recommender system for metaheuristic algorithms for continuous optimization based on deep recurrent neural networks. IEEE Transactions on Artificial Intelligence, 1(1):5-18, 2020
258. Li Huang, Yongsheng Ding, Mengchu Zhou, Yaochu Jin, and Kuangrong Hao. Multiple-solution optimization strategy for multirobot task allocation. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 50(11): 4283-4294, 2020
259. Yang Chen, Xiaoyan Sun, and Yaochu Jin. Communication-efficient federated deep learning with layer-wise asynchronous model update and temporally weighted aggregation. IEEE Transactions on Neural Networks and Learning Systems. 31(10): 4229 – 4238, 2020
Code here.
260. Shuai Wang, Jing Liu and Yaochu Jin. Surrogate-assisted robust optimization of large-scale networks based on graph embedding. IEEE Transactions on Evolutionary Computation, 24(4): 735-749, 2020
261. Yicun Hua, Yaochu Jin, Kuangrong Hao, and Yuan Cao. Generating multiple reference vectors for a class of many-objective optimization problems with degenerate Pareto fronts. Complex & Intelligent Systems, 6(2): 275–285, 2020
Matlab code here
262. Ye Tian, Xiutao Zheng, Xingyi Zhang, and Yaochu Jin. Efficient large-scale multi-objective optimization based on a competitive swarm optimizer. IEEE Transactions on Cybernetics, 50(8):3696-3708, 2020
263. Guo Yu, Yaochu Jin, and Markus Olhofer. Benchmark problems and performance indicators for search of knee points in multi-objective optimization. IEEE Transactions on Cybernetics, 50(8): 3531-3544, 2020
Java code here
264. Yan Zhou, Yaochu Jin, and Jinliang Ding. Surrogate-assisted evolutionary search of spiking neural architectures in liquid state machines. Neurocomputing, 406: 12-23, 2020
265. Yuanjun Huang, Yaochu Jin, Kuangrong Hao. Decision-making and multi-objectivization for cost sensitive robust optimization over time. Knowledge-Based Systems, 199: 105857, 2020
266. Yang Chen, Yaochu Jin, Xiaoyan Sun. Language model based interactive estimation of distribution algorithm. Knowledge-Based Systems, 200: 105980, 2020
267. Handing Wang, Yaochu Jin, Cuie Yang, and Licheng Jiao. Transfer stacking from low- to high-fidelity: A surrogate-assisted bi-fidelity evolutionary algorithm. Applied Soft Computing, 92: 106276, 2020
268. Guoxia Fu, Chaoli Sun, Ying Tan, Guochen Zhang, and Yaochu Jin. A surrogate-assisted evolutionary algorithm with random feature selection for large-scale expensive problems. Parallel Problem Solving from Nature, September 2020, Leiden, The Netherlands
269. Cheng He, Ye Tian, Handing Wang, and Yaochu Jin. A repository of real-world datasets for data-driven evolutionary multiobjective optimization. Complex & Intelligent Systems, 6:189–197, 2020
270. Cuie Yang, Jinliang Ding, Yaochu Jin, Tianyou Chai. Off-line data-driven multi-objective optimization: Knowledge transfer between surrogates and generation of final solutions. IEEE Transactions on Evolutionary Computation, 24(3):409-423, 2020
271. Shuai Wang, Jing Liu, and Yaochu Jin. Robust structural balance in signed networks using a multiobjective evolutionary algorithm. IEEE Computational Intelligence Magazine, 15(2):24-35, 2020
272. Yuanchao Liu, Jianchang Liu, Yaochu Jin, Fei Li, Tianzi Zheng. An affinity propagation clustering based particle swarm optimizer for dynamic optimization. Knowledge-Based Systems, 195: 105711, 2020
273. Hangyu Zhu and Yaochu Jin. Multi-objective evolutionary federated learning. IEEE Transactions on Neural Networks and Learning Systems, 31(4): 1310-1322, 2020
274. Xinjie Wang, Yaochu Jin and Kuangrong Hao. Evolving local plasticity rules for synergistic learning in echo state networks. IEEE Transactions on Neural Networks and Learning System, 31(4):1363-1374, 2020
275. Yanan Sun, Handing Wang, Bing Xue, Yaochu Jin, Gary G. Yen, and Mengjie Zhang. Surrogate-assisted evolutionary deep learning using an end-to-end random forest-based performance predictor. IEEE Transactions on Evolutionary Computation, 24(2):350-364, 2020
276. Ye Tian, Xingyi Zhang, Chao Wang, and Yaochu Jin. An evolutionary algorithm for large-scale sparse multi-objective optimization problems. IEEE Transactions on Evolutionary Computation, 24(2):380-393, 2020
277. Ye Tian, Xinyi Zhang, Ran Cheng, Cheng He, and Yaochu Jin. Guiding evolutionary multi-objective optimization with generic front modeling. IEEE Transactions on Cybernetics, 50(3): 2168-2267, 2020
278. Xilu Wang, Yaochu Jin, Sebastian Schmitt, and Markus Olhofer. An adaptive Bayesian approach to surrogate-assisted evolutionary multi-objective optimization. Information Sciences, 519:317-331, 2020
279. Handing Wang and Yaochu Jin. A random forest assisted evolutionary algorithm for data-driven constrained multi-objective combinatorial optimization of trauma systems. IEEE Transactions on Cybernetics, 50(2): 536-549, 2020
280. Xingyi Zhang, Kefei Zhou, Hebin Pan, Lei Zhang, Xiangxiang Zeng, Yaochu Jin. A network reduction based multi-objective evolutionary algorithm for community detection in large-scale complex networks. IEEE Transactions on Cybernetics, 50(2): 703-716, 2020
281. Sutong Wang, Yuyan Wang, Dujuan Wang, Yunqiang Yin, Yanzhang Wang, and Yaochu Jin. An improved random forest-based rule extraction method for breast cancer diagnosis. Applied Soft Computing, 86, 105941, 2020
282. Zhen Yang, Yongsheng Ding, Yaochu Jin, and Kuangrong Hao. Immune-endocrine system inspired hierarchical coevolutionary multiobjective optimization algorithm for IoT service. IEEE Transactions on Cybernetics, 50(1): 164-177, 2020
283. Xilu Wang, Yaochu Jin, Sebastian Schmitt, and Markus Olhofer. Transfer learning for Gaussian process assisted evolutionary bi-objective optimization for objectives with different evaluation times. Genetic and Evolutionary Computation Conference (GECCO 2020), 587–594, Cancun, Mexico, July 2020
Errata (Corrections of the simulation results of an algorithm under comparison)
284. Rahma Fourati, Boudour Ammar, Yaochu Jin and Adel M. Alimi. EEG feature learning with intrinsic plasticity based deep echo state network. International Joint Conference on Neural Networks International Joint Conference on Neural Networks (IJCNN 2020), Glasgow, UK, July 2020
285. Xinjie Wang, Yaochu Jin and Kuangrong Hao. A gated recurrent unit based echo state network. International Joint Conference on Neural Networks International Joint Conference on Neural Networks (IJCNN 2020), Glasgow, UK, July 2020
286. Huaming Chen, Yaochu Jin, Lei Wang, Chi-Hung Chi and Jun Shen. HIME: Mining and ensembling heterogeneous information for protein-protein interaction prediction. International Joint Conference on Neural Networks (IJCNN 2020), Glasgow, UK, July 2020
287. Ye Tian, Ran Cheng, Xingyi Zhang and Yaochu Jin. Techniques for accelerating multi-objective evolutionary algorithms in PlatEMO. Congress on Evolutionary Computation (CEC 2020), Glasgow, UK, July 2020
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288. Cheng He, Lianghao Li, Ye Tian, Xingyi Zhang, Ran Cheng, Yaochu Jin and Xin Yao. Accelerating large-scale multi-objective optimization via problem reformulation. IEEE Transactions on Evolutionary Computation, 23(6): 949 – 961, 2019
289. Cuie Yang, Jinliang Ding, Yaochu Jin, Chengzhi Wang, Tianyou Chai. Multi-tasking multi-objective evolutionary operational indices optimization of beneficiation processes. IEEE Transactions on Automation Science and Engineering, 16(3):1046 – 1057, 2019
290. Zhen Yang, Yaochu Jin, and Kuangrong Hao. A bio-inspired self-learning coevolutionary dynamic multiobjective optimization algorithm for Internet of Things services. IEEE Transactions on Evolutionary Computation, 23(4): 675 – 688, 2019
291. Fan Guo, Lihong Ren, Yaochu Jin, and Yongsheng Ding. A dynamic SVR–ARMA model with improved fruit fly algorithm for the nonlinear fiber stretching process. Natural Computing, 18(4): 735-746, 2019
292. Du-Juan Wang, Feng Liu and Yaochu Jin. A proactive scheduling approach to steel rolling process with stochastic machine breakdown. Natural Computing, 18(4):679-694 2019
293. Xin Ye, Jia Li, Sihao Liu, Jiwei Liang and Yaochu Jin. A hybrid instance-intensive workflow scheduling method in private cloud environment. Natural Computing, 18(4): 735-746, 2019
294. Huaming Chen, Lei Wang, Yaochu Jin, Chi-Hung Chi, Fucun Li, Huaiyuan Chu, and Jun Shen. Hyperparameters estimation in SVM with GPU acceleration for prediction of protein-protein interactions. IEEE BigData 2019.
295. Ye Tian, Shichen Peng, Tobias Rodemann, Xingyi Zhang, and Yaochu Jin. Automated selection of evolutionary multi-objective optimization algorithms. IEEE Symposium Series on Computational Intelligence, Xiamen, China, December 2019
296. Jia Liu and Yaochu Jin. Evolving hyperparameters for training deep neural networks against adversarial attacks. IEEE Symposium Series on Computational Intelligence, Xiamen, China, December 2019
297. Shufen Qin, Chaoli Sun, Yaochu Jin and Guochen Zhang. Bayesian approaches to surrogate-assisted evolutionary multi-objective optimization: A comparative study. IEEE Symposium Series on Computational Intelligence, Xiamen, China, December 2019
298. Ye Tian, Ran Cheng, Xingyi Zhang, Miqing Li, and Yaochu Jin. Diversity assessment of multi-objective evolutionary algorithms: Performance metric and benchmark problems. IEEE Computational Intelligence Magazine, 14(3): 61-74, 2019
299. Dong Han, Wenli Du, Wei Du, Yaochu Jin and Chunping Wu. An adaptive decomposition-based evolutionary algorithm for many-objective optimization. Information Sciences, 491: 204-222, 2019
300. Xinjie Wang, Yaochu Jin, and Kuangrong Hao. Echo state networks regulated by local intrinsic plasticity rules for regression. Neurocomputing, 351: 111-122, 2019
301. Xingguang Peng, Yaochu Jin, and Handing Wang. Multi-modal optimization enhanced cooperative coevolution for large-scale optimization. IEEE Transactions on Cybernetics, 49(9): 3507-3520, 2019
302. Miao Rong, Dunwei Gong, Yong Zhang, Yaochu Jin, and Witold Pedrycz. Multi-directional prediction approach for dynamic multi-objective optimization problems. IEEE Transactions on Cybernetics, 49(9):3362-3374, 2019
303. Yaochu Jin, Handing Wang, Tinkle Chugh, Dan Guo, and Kaisa Miettinen. Data-driven evolutionary optimization: An overview and case studies. IEEE Transactions on Evolutionary Computation, 23(3): 442-458, 2019
304. Jie Tian, Ying Tan, Jianchao Zeng, Chaoli Sun, and Yaochu Jin. Multi-objective infill criterion driven Gaussian process assisted particle swarm optimization of high-dimensional expensive problems. IEEE Transactions on Evolutionary Computation, 23(3):459 -472, 2019
305. Yicun Hua, Yaochu Jin and Kuangrong Hao. A clustering based adaptive evolutionary algorithm for multi-objective optimization with irregular Pareto fronts. IEEE Transactions on Cybernetics, 49(7):2758-2770, 2019
Matlab code here (Note that this code should be run within the PlatEMO Software tool) or here, which can run independently.
306. Jinliang Ding, Cuie Yang, Qiong Xiao, Tianyou Chai, and Yaochu Jin. Dynamic evolutionary multi-objective optimization for raw ore allocation in mineral processing. IEEE Transactions on Emerging Topics in Computational Intelligence, 3(1): 36-48, 2019
307. Ye Tian, Ran Cheng, Xingyi Zhang, Yansen Su, and Yaochu Jin. A strengthened dominance relation considering convergence and diversity for evolutionary many-objective optimization. IEEE Transactions on Evolutionary Computation, 23(2): 331 – 345, 2019
308. Handing Wang, Yaochu Jin, Chaoli Sun and John Doherty. Offline data-driven evolutionary optimization using selective surrogate ensembles. IEEE Transactions on Evolutionary Computation, 23(2):203-216, 2019
Matlab code in GitHub
309. Murillo. G. Carneiro, Ran Cheng, Liang Zhao, Yaochu Jin. Particle swarm optimization for network-based data classification. Neural Networks, 110: 243-255, 2019
310. Tinkle Chugh, Tomas Kratky, Kaisa Miettinen, Yaochu Jin, Pekka Makonen. Multiobjective shape design in a ventilation system with a preference-driven surrogate-assisted evolutionary algorithm. Proceedings of the Genetic and Evolutionary Computation Conference, Pages 1147–1155, July 2019
311. Shufen Qin, Chaoli Sun, Yaochu Jin, Lier Lan and Ying Tan. A new selection strategy for decomposition-based evolutionary many-objective optimization. IEEE Congress on Evolutionary Computation, Wellington, New Zealand, June 2019
312. Hao Wang, Chaoli Sun, Yaochu Jin, Shufen Qin and Haibo Yu. A Multi-indicator based Selection Strategy for Evolutionary Many-objective Optimization. IEEE Congress on Evolutionary Computation, Wellington, New Zealand, June 2019
313. Qiqi Liu, Yaochu Jin, Martin Heiderich and Tobias Rodemann. Adaptation of reference vectors for evolutionary many-objective optimization of problems with irregular Pareto fronts. IEEE Congress on Evolutionary Computation, Wellington, New Zealand, June 2019
314. Guo Yu, Yaochu Jin and Markus Olhofer. References or preferences - rethinking many-objective evolutionary optimization. IEEE Congress on Evolutionary Computation, Wellington, New Zealand, June 2019
315. Cheng He, Ran Cheng, Yaochu Jin and Xin Yao. Surrogate-assisted expensive many-objective optimization by model fusion. IEEE Congress on Evolutionary Computation, Wellington, New Zealand, June 2019
316. Ye Tian, Shangshang Yang, Xingyi Zhang and Yaochu Jin. Using PlatEMO to solve multi-objective optimization problems in applications: A case study on feature selection. IEEE Congress on Evolutionary Computation, Wellington, New Zealand, June 2019
317. Yan Zhou, Yaochu Jin and Jinliang Ding. Evolutionary optimization of liquid state machines for robust learning. International Symposium on Neural Networks, Moscow, Russia, July 10-12, 2019
318. Dan Guo, Yaochu Jin, Jinliang Ding, and Tianyou Chai. Heterogeneous ensemble based infill criterion for evolutionary multi-objective optimization of expensive problems. IEEE Transactions on Cybernetics, 49(3):1012-1025, 2019
319. Jinliang Ding, Cuie Yang, Yaochu Jin and Tianyou Chai. Generalized multi-tasking for evolutionary optimization of expensive problems. IEEE Transactions on Evolutionary Computation, 23(1): 44-58, 2019
320. Linqiang Pan, Cheng He, Ye Tian, Handing Wang, Xingyi Zhang, and Yaochu Jin. A classification based surrogate-assisted evolutionary algorithm for expensive many-objective optimization. IEEE Transactions on Evolutionary Computation, 23(1):74-88, 2019
321. Wei Du, Weimin Zhong, Yang Tang, Wenli Du and Yaochu Jin. High-dimensional robust multi-objective optimization for order scheduling: A decision variable classification approach. IEEE Transactions on Industrial Informatics, 15(1): 293-304, 2019
322. Qinqin Fan, Yaochu Jin, Weili Wang, and Xuefeng Yan. A performance-driven multi-algorithm selection strategy for energy consumption optimization of sea-rail intermodal transportation. Swarm and Evolutionary Computation, 44:1-17, 2019
323. Yuyan Han, Dunwei Gong, Yaochu Jin, and Quanke Pan. Evolutionary multi-objective blocking lot-streaming flow shop scheduling with machine breakdowns. IEEE Transactions on Cybernetics, 49(1): 184-197, 2019
324. Yuyan Wang, Dujuan Wang, Xin Ye, Yanzhang Wang, Yunqiang Yin, and Yaochu Jin. A tree ensemble-based two-stage model for advanced-stage colorectal cancer survival prediction. Information Sciences, 474:106-124, 2019
325. Ruwang Jiao, Sanyou Zeng, Changhe Li, Yuhong Jiang and Yaochu Jin. A complete expected improvement criterion for Gaussian process assisted highly constrained expensive optimization. Information Sciences, 471, 80-96, 2019
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326. Handing Wang, Yaochu Jin and John Doherty. A generic test suite for evolutionary multi-fidelity optimization. IEEE Transactions on Evolutionary Computation. 22(6): 836 – 850, 2018
Matlab code in GitHub
327. Shaoze Cui, Dujuan Wang, Yanzhang Wang, Pay-Wen Yu, Yaochu Jin. An improved support vector machine-based diabetic readmission prediction. Computer Methods and Programs in Biomedicine, 166: 123-135, 2018
328. Ran Cheng, Cheng He, Yaochu Jin, and Xin Yao. Model-based evolutionary algorithms – A short survey. Complex & Intelligent Systems, 4:283-292, 2018
329. Zhenping Xie, and Yaochu Jin. An extended reinforcement learning framework to model cognitive development with enactive pattern representation. IEEE Transactions on Cognitive and Developmental Systems, 10(3): 738-750, 2018
330. Fei Li, Ran Cheng, Jianchang Liu, and Yaochu Jin. TS-R2EA: A two-stage R2 indicator based evolutionary algorithm for many-objective optimization. Applied Soft Computing, 67: 245-260, 2018
331. Haibo Yu, Ying Tan, Jianchao Zeng, Chaoli Sun and Yaochu Jin. Surrogate-assisted hierarchical particle swarm optimization. Information Sciences, 454-455: 59-72, 2018
332. Zhaomin Chen, Chai Kiat Yeo, Bu Sung Lee, Chiew Tong Lau and Yaochu Jin. Evolutionary multi-objective optimization based ensemble autoencoders for image outlier detection. Neurocomputing, 309: 192-200 2018
333. Chao Qian, Yu Yang, Ke Tang, Yaochu Jin, Xin Yao, and Zhi-Hua Zhou. On the effectiveness of sampling for evolutionary optimization in noisy environments. Evolutionary Computation, 26(2):237-267, 2018
334. Ye Tian, Ran Cheng, Xingyi Zhang, Fan Cheng, and Yaochu Jin. An indicator based multi-objective evolutionary algorithm with reference point adaptation for better versatility. IEEE Transactions on Evolutionary Computation, 22(4): 609 - 622, 2018
Matlab code here
335. Chaoli Sun, Jinliang Ding, Jianchao Zeng and Yaochu Jin. Fitness approximation assisted competitive swarm optimizer for large scale expensive optimization problems. Memetic Computing, 10(2):123-134 2018.
336. Chaoli Sun, Yaochu Jin and Ying Tan. Semi-supervised learning assisted particle swarm optimization of computationally expensive problems. Genetic and Evolutionary Computation Conference, pp.45-52, Kyoto, Japan, 15-19 July 2018
337. Guo Yu, Yaochu Jin and Markus Olhofer. A method for a posteriori identification of knee points based on solution density. Congress on Evolutionary Computation, Rio de Janeiro, Brazil, 8-13 July 2018
338. Handing Wang, John Doherty and Yaochu Jin. Hierarchical surrogate-assisted evolutionary multi-scenario airfoil shape optimization. Congress on Evolutionary Computation, Rio de Janeiro, Brazil, 8-13 July 2018
339. Ye Tian, Xiaoshu Xiang, Xingyi Zhang, Ran Cheng and Yaochu Jin. Sampling reference points on the Pareto fronts of multi-objective optimization problems. Congress on Evolutionary Computation, Rio de Janeiro, Brazil, 8-13 July 2018
340.
Xingyi Zhang, Ye Tian, Ran Cheng
and Yaochu Jin. A decision variable clustering-based evolutionary algorithm for
large-scale many-objective optimization. IEEE Transactions on
Evolutionary Computation, 22(1):97-112, 2018 (“2020
IEEE TEVC Outstanding Paper Award”)
A draft here
Matlab code
for testing LMEA on LSMOP test suite.
MATLAB code for
tree-based ENS (T-ENS)
341. Tinkle Chugh, Yaochu Jin, Kaisa Miettinen, Jussi Hakanen, and Karthink Sindhya. A surrogate-assisted reference vector guided evolutionary algorithm for computationally expensive many-objective optimization. IEEE Transactions on Evolutionary Computation, 21(1): 129-142, 2018
A draft here.
342. Hyondong Oh, Ataollah R. Shiraz, Yaochu Jin. Morphogen diffusion algorithms for tracking and herding using a swarm of Kilobots. Soft Computing, 22(6): 1833-1844, 2018
343. Shenkai Gu, Ran Cheng, Yaochu Jin. Feature selection for high dimensional classification using a competitive swarm optimizer. Soft Computing, 22(3): 811-822, 2018
Java code here.
344. Xingyi Zhang, Xiutao Zheng, Ran Cheng, Jianfeng Qiu, and Yaochu Jin. A competitive mechanism based multi-objective particle swarm optimizer with fast convergence. Information Sciences, 427:63-76,2018
Matlab code here.
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345.
Ran Cheng, Yaochu Jin,
Markus Olhofer and Bernhard Sendhoff. Test
problems for large-scale multiobjective and many-objective optimization.
IEEE Transactions on Cybernetics, 7(12): 4108-4121, 2017
A draft here
Source code
for the proposed test problems. Supplimentary materials
346. Ataollah Ramezan Shirazi and Yaochu Jin. A strategy for self-organized coordinated motion of a swarm of minimalist robots. IEEE Transactions on Emerging Topics in Computational Intelligence, 1(5): 326 – 338, 2017
347. Ye Tian, Ran Cheng, Xingyi Zhang, and Yaochu Jin. PlatEMO: A MATLAB platform for evolutionary multi-objective optimization. IEEE Computational Intelligence Magazine, 12(4): 73-87, 2017 (“2019 IEEE CIM Outstanding Paper Award”)
348. Handing Wang, Markus Olhofer and Yaochu Jin. Mini-review on preference modeling and articulation in multi-objective optimization: Current status and challenges. Complex & Intelligent Systems, 3(4): 233–245, 2017
349. Ye Tian, Handing Wang, Xingyi Zhang, and Yaochu Jin. Effectiveness and efficiency of non-dominated sorting for evolutionary multi- and many-objective optimization. Complex & Intelligent Systems, 3(4): 247–263, 2017
350. Xin Ye, Sihao Liu, Yanli Yin and Yaochu Jin. User-oriented many-objective cloud workflow scheduling based on an improved knee point driven evolutionary algorithm. Knowledge Based Systems, 135: 113-124, 2017
351. Tinkle Chugh, Nirupam Chakraborti, Karthik Sindhya, and Yaochu Jin. A data-driven surrogate-assisted evolutionary algorithm applied to a many-objective blast furnace optimization problem. Materials and Manufacturing Processes, 32(1): 1172-1178, 2017
352. Guangshun Yao,Yongsheng Ding, Yaochu Jin, Kuangrong Hao. Endocrine-based coevolutionary multi-swarm for multi-objective workflow scheduling in a cloud system. Soft Computing, 21(15): 4309–4322, 2017
353. Murillo G. Carneiro, Thiago H. Cupertino, Ran Cheng, Yaochu Jin and Liang Zhao. Nature-inspired graph optimization for dimensionality reduction. The Annual IEEE International Conference on Tools with Artificial Intelligence, November 6-7, 2017, Boston, MA, USA
354. Cheng He, Ye Tian, Yaochu Jin, Xingyi Zhang, and Linqiang Pan. A radial space division based evolutionary algorithm for many-objective optimization. Applied Soft Computing, 61:603-621, 2017
355. Handing Wang, Yaochu Jin, and John Doherty. Committee-based active learning for surrogate-assisted particle swarm optimization of expensive problems. IEEE Transactions on Cybernetics, 47(9): 2664-2677, 2017
Matlab code in GitHub
356. Yiping Liu, Dunwei Gong, Jing Sun, and Yaochu Jin. A many-objective evolutionary algorithm using a one-by-one selection strategy. IEEE Transactions on Cybernetics, 47(9): 2689-2702, 2017
357. Spencer Thomas, Yaochu Jin, Josephine Bunch and Ian Gilmore. Enhancing classification of mass spectrometry imaging data with deep neural networks. IEEE Symposium Series on Computational Intelligence, November 27-December 1, 2017, Hawaii, USA
358. Nitin Naik, Paul Jenkins, Roger Cooke, David Ball, Arthur Foster, Yaochu Jin. Augmented windows fuzzy firewall for preventing denial of service attack. FUZZ-IEEE 2017: 1-6
359. Jie Tian, Chaoli Sun, Haibo Yu, Ying Tan, Jianchao Zeng and Yaochu Jin. Comparisons of different kernels in Kriging-assisted evolutionary expensive optimization. IEEE Symposium Series on Computational Intelligence, November 27-December 1, 2017, Hawaii, USA
360. Chaoli Sun, Yaochu Jin, Ran Cheng, Jinliang Ding and Jianchao Zeng. Surrogate-assisted cooperative swarm optimization of high-dimensional expensive problems. IEEE Transactions on Evolutionary Computation, 21(4):644-660, 2017
361. Joseph Chrol-Cannon, Yaochu Jin and Andre Gruning. An efficient method for online detection of polychronous patterns in spiking neural networks. Neurocomputing, 267:644-650, 2017
362. Xingyi Zhang, Fuchen Duan, Lei Zhang, Fan Cheng, Yaochu Jin, Ke Tang. Pattern recommendation in task oriented applications: A multi-objective perspective. IEEE Computational Intelligence Magazine, 12(3):43-53, 2017
363. Cuie Yang, Jinliang Ding, Kay Chen Tan, and Yaochu Jin. Two-stage assortative mating for multi-objective multifactorial evolutionary optimization. The 56th IEEE Conference on Decision and Control, December 12-15, 2017, Melbourne, Australia
364.
Tinkle Chugh, Karthik
Sindhya, Kaisa Miettinen, Yaochu Jin, Tomas Kratky, and Pekka Makkonen. Surrogate-assisted
evolutionary multiobjective shape optimization of an air intake ventilation
system. Congress on Evolutionary Computation, 1541-1548, June
2017 ("2017 CEC Best Student Paper Award")
A draft here.
365.
Handing Wang, Yaochu Jin
and Xin Yao. Diversity assessment in many-objective optimization. IEEE
Transactions on Cybernetics, 40(6):1510-1522, 2017
A draft of the paper here.
Matlab code
in GitHub.
366. Ran Cheng, Miqing Li, Ye Tian, Xingyi Zhang, Shengxiang Yang, Yaochu Jin and Xin Yao. A benchmark test suite for evolutionary many-objective optimization. Complex & Intelligent Systems , 3(1):67-81, 2017
367. Shenkai Gu and Yaochu Jin. Multi-train: A semi-supervised heterogeneous ensemble classifier. Neurocomputing, 249:202-211, 2017
368. Jing Liu, Yaxiong Chi, Chen Zhu and Yaochu Jin. A time series driven decomposed evolutionary optimization approach for reconstructing large-scale gene regulatory networks based on fuzzy cognitive maps. BMC Bioinformatics, 18:241, 2017. DOI: 10.1186/s12859-017-1657-1
369. Ran Cheng, Tobias Rodemann, Michael Fischer, Markus Olhofer, and Yaochu Jin. Evolutionary many-objective optimization of hybrid electric vehicle control: From general optimization to preference articulation. IEEE Transactions on Emerging Topics in Computational Intelligence, 1(2):97-111, 2017
370. Hyondong Oh, Ataollah Ramezan Shirazi, Chaoli Sun, and Yaochu Jin. Bio-inspired self-organising multi-robot pattern formation: A review. Robotics and Autonomous Systems, 91:83-100, 2017
371.
Wissam A. Albukhanajer, Yaochu
Jin, Johann A. Briffa. Classifier ensembles for image identification using multi-objective
Pareto features. Neurocomputing, 238:316-327, 2017.
A draft here.
372. Yuanjun Huang, Yongsheng Ding, Kuangrong Hao, Yaochu Jin. A multi-objective approach to robust optimization over time considering switching cost. Information Sciences, 394:183-197, 2017
373. Du-Juan Wang, Feng Liu and Yaochu Jin. A multi-objective evolutionary algorithm guided by directed search for dynamic scheduling. Computers & Operations Research, 79: 279-290, 2017
374. Richard Allmendinger, Michael T. M. Emmerich, Jussi Hakanen, Yaochu Jin, and Enrico Rigoni. Surrogate-assisted multicriteria optimization: Complexities, prospective solutions, and business case. Journal of Multi-Criteria Decision Analysis, 24(1/2):5-24, 2017
375. Nitin Naik, Paul Jenkins, Roger Cooke, David Ball, Arthur Foster, Yaochu Jin. Augmented windows fuzzy firewall for preventing denial of service attack. FUZZ-IEEE 2017: 1-6
376. Handing Wang and Yaochu Jin. Efficient nonlinear correlation detection for decomposed search in evolutionary multi-objective optimization. Congress on Evolutionary Computation, 649-656, June 2017
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377. Ricardo Cerri, Rodrigo Coelho Barros, Andre Carlos Ponce de Leon Ferreira Carvalho and Yaochu Jin. Reduction strategies for hierarchical multi-label classification in protein function prediction. BMC Bioinformatics, 17:373, 2016. DOI: 10.1186/s12859-016-1232-1.
378. Xingguang Peng, Kun Liu and Yaochu Jin. A dynamic optimization approach to the design of cooperative coevolutionary algorithms. Knowledge-Based Systems, 109: 174-186, 2016
379.
Handing Wang, Yaochu Jin
and Jan O. Jansen. Data-driven surrogate-assisted multi-objective evolutionary
optimization of a trauma system. IEEE Transactions on
Evolutionary Computation, 20(6): 939-952, 2016
A draft of the paper here
380.
Craig Brown, Yaochu Jin,
Matthew Leach and Martin Hodgson. \mu JADE: Adaptive differential evolution with a small population.
Soft Computing, 20(10): 4111-4120, 2016
A draft here.
381.
Xingyi Zhang, Ye Tian, Yaochu
Jin. Approximate non-dominated sorting for evolutionary many-objective
optimization. Information Sciences, 369:14-33, 2016
Source code of the aproximate sorting algorithm (A-ENS) here, and the code of KnEA using A-ENS and ENS
382.
Ran Cheng, Yaochu Jin,
Markus Olhofer and Bernhard Sendhoff. A reference
vector guided evolutionary algorithm for many-objective optimization.
IEEE Transactions on Evolutionary Computation, 20(5):773-791, 2016
A draft of the paper is here; MATLAB code for non-constrained optimization here and MATLAB code
for RVEA for constrained optimization here, and Java code implemented by third party here.
383. Dan Guo, Tianyou Chai, Jinliang Ding, and Yaochu Jin. Small data driven evolutionary multi-objective optimization of fused magnesium furnaces. IEEE Symposium on Computational Intelligence, Athens, Greece, December 2016
384. Jussi Hakanen, Tinkle Chugh, Karthik Sindhya, Yaochu Jin, Kaisa Miettinen. Connections of reference vectors and different types of preference information in interactive multiobjective evolutionary algorithms. IEEE Symposium on Computational Intelligence, Athens, Greece, December 2016
385. Jie Tian, Yin Tan, Chaoli Sun, Jianchao Zeng, and Yaochu Jin. A self-adaptive similarity-based fitness approximation for evolutionary optimization. IEEE Symposium on Computational Intelligence, Athens, Greece, December 2016
386. Ufuk Yolcu, Yaochu Jin and Erol Egrioglu. An ensemble of single multiplicative neuron models for probabilistic prediction. IEEE Symposium on Computational Intelligence, Athens, Greece, December 2016
387. Xingyi Zhang, Ye Tian, Ran Cheng, and Yaochu Jin. Empirical analysis of a tree-based efficient non-dominated sorting approach for many-objective optimization. IEEE Symposium on Computational Intelligence, Athens, Greece, December 2016
388. Haibo Yu, Chaoli Sun, Jianchao Zeng, Ying Tan and Yaochu Jin. An adaptive model selection strategy for surrogate-assisted particle swarm optimization algorithm. IEEE Symposium on Computational Intelligence, Athens, Greece, December 2016
389.
Yaochu Jin. Data Driven Evolutionary Optimization of Complex Systems: Big Data
Versus Small Data. Invited talk, Workshop on Surrogte-Assisted
Evolutionary Optimisation. Genetic and Evolutionary Computation Conference
(GECCO), July 20-24 2016, Denver, CO, USA
Also a Plenary Speech
at 2016 World Congress on Computational Intelligence (WCCI 2016), July 24-29,
Vancouver, Canada
390. Shi Cheng, Bin Liu, Yuhui Shi, Yaochu Jin and Bin Li. Evolutionary Computation and Big Data: Key Challenges and Future Directions. DMBD 2016, LNCS 9714, pp. 3-14, 2016
391.
Mohd-Hanif Yusoff, Joseph
Chrol-Cannon and Yaochu Jin. Modeling neural plasticity in echo state networks for classification
and regression. Information Sciences, 364-365:184-196, 2016
A draft here.
392. Tinkle Chugh, Karthik Sindhya, Kaisa Miettinen, Jussi Hakanen and Yaochu Jin. On constraint handling in surrogate-assisted evolutionary many-objective optimization. Parallel Problem Solving from Nature (PPSN), September 2016, Edinburgh, Scotland
393. Murillo Carneiro, Liang Zhao, Ran Cheng and Yaochu Jin. Network structural optimization based on swarm intelligence for highlevel classification. International Joint Conference on Neural Networks, July 2016, Vancouver, Canada
394. Cuie Yang, Jinliang Ding, Tianyou Chai and Yaochu Jin. Reference point based prediction for evolutionary dynamic multiobjective optimization. Congress on Evolutionary Computation, July 2016, Vancouver, Canada
395. Ye Tian, Xingyi Zhang, Ran Cheng and Yaochu Jin. A multi-objective evolutionary algorithm based on an enhanced inverted generational distance metric. Congress on Evolutionary Computation, July 2016, Vancouver, Canada
396. Yuyan Han, Dunwei Gong, Yaochu Jin, Quan-ke Pan. Evolutionary multi-objective blocking lot-streaming flow shopscheduling with interval processing time. Applied Soft Computing, 42:229-245, 2016
397. Yongsheng Ding, Tao Zhang, Lihong Ren, Yaochu Jin, Kuangrong Hao and Lei Chen. Immune-inspired self-adaptive collaborative control allocation for multi-level stretching processes. Information Sciences, 342:81-95, 2016
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398.
Xingyi Zhang, Ye Tian and Yaochu
Jin. A knee point driven evolutionary algorithm for many-objective
optimization. IEEE Transactions on Evolutionary Computation,
19(6):761-776, 2015.
A draft of the paper can be downloaded here and MATLAB
code here.
399.
Ran Cheng, Yaochu Jin,
Kaname Narukawa and Bernhard Sendhoff. A
multiobjective evolutionary algorithm using Gaussian process based inverse
modeling. IEEE Transactions on Evolutionary Computation,
19(6):761-856, 2015.
A draft of the paper is here
and the MATLAB code here.
400. Wissam A. Albukhanajer, Johann A. Briffa and Yaochu Jin. Evolutionary multi-objective image feature extraction in the presence of noise. IEEE Transactions on Cybernetics, 45(9):1757-1768, 2015.
401.
Du-Juan Wang, Feng Liu, Yan-Zhang
Wang and Yaochu Jin. A
knowledge-based evolutionary proactive scheduling approach in the presence of
machine breakdown and deterioration effect. Knowledge-Based
Systems. 90:70-80, 2015.
Also a draft here.
402.
Joseph Chrol-Cannon and Yaochu
Jin. Learning structure of sensory inputs with synaptic plasticity leads
to interference. Frontiers in Computational Neuroscience,
2015.doi: 10.3389/fncom.2015.00103
A draft here
403.
Yan Wu, Yaochu Jin
and Xiaoxiong Liu. A directed search strategy for evolutionary dynamic multiobjective
optimization. Soft Computing, 19(11):3221-3235, 2015.
A draft here
404.
Bin Yang, Yongsheng Ding, Yaochu
Jin, Kuangrong Hao.Self-organized swarm robot for target search and trapping inspired by
bacterial chemotaxis. Robotics and Autonomous Systems , 72:
83-92, 2015.
A draft here.
405. Shenkai Gu, Ran Cheng and Yaochu Jin. Multi-objective ensemble generation. WIREs Data Mining and Knowledge Discovery, 5(5): 234-245, 2015
406.
Xingyi Zhang, Ye Tian, Ran Cheng,
and Yaochu Jin. An efficient approach to non-dominated sorting for evolutionary
multi-objective optimization. IEEE Transactions on Evolutionary
Computation, 19(2):201-213, 2015 (“2017 IEEE TEVC
Outstanding Paper Award")
See also here,
Matlab code ENS_SS, ENS_BS and the NSGA-II with ENS.
407. Tameera Rahman, Mana Mahapatra, Emma Laing and Yaochu Jin. Evolutionary non-linear modelling for selecting vaccines against antigenically-variable viruses. Bioinformatics, 31(6):834-840, 2015
408.
Ran Cheng and Yaochu Jin. A competitive swarm optimizer for large scale optimization.
IEEE Transactions on Cybernetics, 45(2):191-205, 2015
See also here.
Download the (updated) MATLAB code here or C code here.
409.
Ran Cheng and Yaochu Jin. A social learning particle swarm optimization algorithm for scalable
optimization. Information Sciences, 291:43-60, 2015
See also here.
Download the Matlab code here
or C code here.
410.
Chaoli Sun, Yaochu Jin,
Jianchao Zeng and Yang Yu. A two-layer surrogate-assisted particle swarm optimization algorithm.
Soft Computing, 19(6):1461-1475, 2015.
Also here
411. Tan Zhang, Yaochu Jin, Yongsheng Ding and Kuangrong Hao. A cytokine network inspired cooperative control system for multi-stage stretching processes in fiber production. Soft Computing, 19(6):1523-1540, 2015
412. Ran Cheng, Markus Olhofer and Yaochu Jin. Reference vector based a posteriori preference articulation for evolutionary multiobjective optimization. Congress on Evolutionary Computation (CEC 2015). May 24-28, 2015, Sendai, Japan
413. Yanling Jin, Yongsheng Ding, Kuangrong Hao and Yaochu Jin. An endocrine-based intelligent distributed cooperative algorithm for target tracking in wireless sensor networks. Soft Computing, 19(5):1427-1441, 2015
414.
Yuanjun Huang, Yaochu Jin
and Yongsheng Ding. New performance indicators for robust optimization over time.
Congress on Evolutionary Computation (CEC 2015). May 24-28, 2015,
Sendai, Japan
A draft here.
415. Wissam A. Albukhanajer, Yaochu Jin and Johann Briffa. Trade-off between computational complexity and accuracy in evolutionary image feature extraction. Congress on Evolutionary Computation (CEC 2015). May 24-28, 2015, Sendai, Japan
416.
Ran Cheng, Yaochu Jin
and Kaname Narukawa. Adaptive reference vector generation for inverse model based
evolutionary multiobjective optimization with degenerate and disconnected
Pareto fronts. The 8th Int. Conf. on Evolutionary Multi-Criterion
Optimization (EMO'2015), pp.127-140, Guimar?es, Portugal.
A draft here.
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417. Zhi-Hua Zhou, Nitesh V. Chawla, Yaochu Jin, and Graham J. Williams. Big data opportunities and challenges: Discussions from data analytics perspectives. IEEE Computational Intelligence Magazine, 9(4):62-74, 2014 A draft here ("2016 IEEE CIM Outstanding Paper Award".)
418. Shenkai Gu and Yaochu Jin. Generating diverse and accurate classifier ensembles using multi-objective optimization. IEEE Symposium Series on Computational Intelligence, December 9-12, 2014, Orlando, Florida, USA
419. Joseph Chrol-Cannon and Yaochu Jin. Computational modeling of neural plasticity for self-organization of neural networks. BioSystems, 125:43-54, 2014 Also here
420. Christopher Smith and Yaochu Jin. Evolutionary multi-objective generation of recurrent neural network ensembles for time series prediction. Neurocomputing, 143:302-311, 2014. Also here
421. Christopher Smith, John Doherty, and Yaochu Jin. Convergence based prediction surrogates for high-lift CFD optimization. In: Royal Aeronautical Society - Applied Aerodynamics Conference, Bristol, UK, 2014
422. Mohd-Hanif Yusoff and Yaochu Jin. Modeling neural plasticity in Echo State Networks for time series prediction. 2014 UK Workshop on Computational Intelligence, Bradford, UK, 8 - 10 September 2014
423. Chao Qian, Yang Yu, Yaochu Jin and Zhi-Hua Zhou. On the effectiveness of sampling for evolutionary optimization in noisy environments. Parallel Problem Solving from Nature, September 13-17, 2014 Ljubljana, Slovenia
424. Ataollah Ramezan Shirazi, Hyondong Oh and Yaochu Jin. Morphogenetic self-organization of collective movement without directional sensing. Advances in Autonomous Robotics Systems, Lecture Notes in Computer Science, Volume 8717, pp 139-150, 2014
425. Hyondong Oh and Yaochu Jin. Adaptive swarm robot region coverage using gene regulatory networks. Advances in Autonomous Robotics Systems, Lecture Notes in Computer Science, Volume 8717, pp 197-208, 2014
426. Joseph Chrol-Cannon and Yaochu Jin. On the correlation between reservoir metrics and performance for time series classification under the influence of synaptic plasticity. PLOS ONE, DOI: 10.1371/journal.pone.0101792, July 10, 2014.
427. Spencer A. Thomas and Yaochu Jin. Reconstructing gene regulatory networks: Where optimization meets big data. Evolutionary Intelligence, 7(1):29-47, 2014
428. Aimin Zhou, Yaochu Jin and Qingfu Zhang. A population prediction strategy for evolutionary dynamic multiobjective optimization. IEEE Transactions on Cybernetics, 44(1): 40-53, 2014
C++ code here.
429. Tong Liu, Chaoli Sun, Jianchao Zeng and Yaochu Jin. Similarity- and reliability-assisted fitness estimation for particle swarm optimization of expensive problems. IEEE Congress on Evolutionary Computation, July 2014, Beijing, China
430. Ran Cheng and Yaochu Jin. Demonstrator selection in a social learning particle swarm optimizer. IEEE Congress on Evolutionary Computation, July 2014, Beijing, China
431. Hyondong Oh and Yaochu Jin. Evolving hierarchical gene regulatory networks for morphogenetic pattern formation of swarm robotics. IEEE Congress on Evolutionary Computation, July 2014, Beijing, China
432. Wissam A. Albukhanajer, Yaochu Jin and Johann A. Briffa. Neural network ensembles for image identification using Pareto-optimal features. IEEE Congress on Evolutionary Computation, July 2014, Beijing, China
433.
Christopher Smith, John
Doherty and Yaochu Jin. Multi-objective
evolutionary recurrent neural network ensemble for prediction of computational
fluid dynamic simulations. IEEE Congress on Evolutionary
Computation, July 2014, Beijing, China ( "Runner-up
for the 2014 CEC Best Student Paper Award".)
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434. Jiajia Chen, Yongsheng Ding, Yaochu Jin, and Kuangrong Hao. A synergetic immune clonal selection algorithm based multi-objective optimization method for carbon fiber drawing process. Fibers and Polymers, 14(10): 1722-1730, 2013
435. Lili Zhuang, Ke Tang and Yaochu Jin. Metamodel assisted mixed-integer evolution strategies based on Kendall rank correlation coefficient. The 14th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL'2013). October 20-23, 2013, Hefei, China
436. Ran Cheng and Yaochu Jin. On the competition mechanism of the competitive particle swarm optimizer. UK Workshop on Computational Intelligence, September 9-11, 2013
437. Spencer A. Thomas, Yaochu Jin, Emma Laing and Colin P. Smith. Reconstructing regulatory networks in Streptomyces using evolutionary algorithms. UK Workshop on Computational Intelligence, September 9-11, 2013
438. Xiaoyan Sun, Dunwei Gong, Yaochu Jin, and Shanshan Chen. A new surrogate-assisted interactive genetic algorithm with weighted semi-supervised learning. IEEE Transactions on Cybernetics, 43(2):685-698, 2013
439. Spencer A. Thomas and Yaochu Jin. Evolving connectivity between genetic oscillators and switches using evolutionary algorithms. Journal of Bioinformatics and Computational Biology, Vol. 11, No. 3 (2013) 1341001 (15 pages)
440. Benjamin Inden, Yaochu Jin, Robert Haschke, Helger Ritter, Bernhard Sendhoff. An examination of different fitness and novelty based selection methods for the evolution of neural networks. Soft Computing. 17(5): 753-767, 2013.
441. Yaochu Jin, Ke Tang, Xin Yu, Bernhard Sendhoff and Xin Yao. A framework for finding robust optimal solutions over time. Memetic Computing, 5(1):3-18, 2013. A preprint here.
442. Mingh Nhgia Le, Yew Soon Ong, Stefan Menzel, Yaochu Jin, and Bernhard Sendhoff. Evolution by adapting surrogates. Evolutionary Computation, 21(2):313-340, 2013
443. Ran Cheng, Chaoli Sun and Yaochu Jin. A multi-swarm evolutionary framework based on a feedback mechanism. In: IEEE Congress on Evolutionary Computation (CEC'2013), Cancun, Mexico, June 20-23 2013
444. Ayang Xiao, Benli Wang and Yaochu Jin. Evolutionary truss layout optimization using the vectorized structure approach. In: IEEE Congress on Evolutionary Computation (CEC'2013), Cancun, Mexico, June 20-23 2013
445. Jianfeng Lu, Bin Li, and Yaochu Jin. An evolution strategy assisted by an ensemble of local Gaussian process models. In: Genetic and Evolutionary Computation Conference (GECCO'2013), Amsterdam, The Netherlands, 6-10 July 2013
446. Christopher Smith, John Doherty, and Yaochu Jin. Recurrent neural network ensembles for convergence prediction in surrogate-assisted evolutionary optimisation. IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments, part of the IEEE Symposium Series on Computational Intelligence, Singapore, 16-19 April 2013
447. Chaoli Sun, Jianchao Zeng, Jengshyang Pan and Yaochu Jin. Similarity based evolution control for fitness estimation in particle swarm optimisation. IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments, part of the IEEE Symposium Series on Computational Intelligence, Singapore, 16-19 April 2013
448. Guanbo Jia, Yong Wang, Zixin Cai, and Yaochu Jin. An improved (mu+lambda)-constrained differential evolution for constrained optimization. Information Sciences, 222:302-322, 2013
449. Yan Meng, Hongliang Guo and Yaochu Jin. A morphogenetic approach to flexible and robust shape formation for swarm robotic systems. Robotics and Autonomous Systems, 61(1):25-38, 2013
450. Chaoli Sun, Jianchao Zeng, Jengshyang Pan, Songdong Xue, Yaochu Jin. A new fitness estimation strategy for particle swarm optimization. Information Sciences, 221:355-370, 2013
451. Spencer A. Thomas and Yaochu Jin. Single and multi-objective in silico evolution of tunable genetic oscillators. The 7th Int. Conf. on Evolutionary Multi-Criterion Optimization (EMO 2013), Sheffield, UK, March 2013. Also here.
452. Wissen A. Albukhanajer, Yaochu Jin, Johann A. Briffa, and Godfried Williams. A comparative study of multi-objective evolutionary Trace Transform algorithms for robust feature extraction. The 7th Int. Conf. on Evolutionary Multi-Criterion Optimization (EMO 2013), 19-22 March 2013, Sheffield, UK
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453. Jun Yin, Yan Meng and Yaochu Jin. A developmental approach to structural self-organization in reservoir computing. IEEE Transactions on Autonomous Mental Development, 4(4):273-289, 2012
454. Lisa Schramm, Yaochu Jin, and Bernhard Sendhoff. Evolutionary Synthesis and Analysis of a Gene Regulatory Network for Dynamically Stable Growth and Regeneration. Artificial Life, 18(4):425-444, 2012. Also here
455. Daniel Bush and Yaochu Jin. Calcium control of hippocampal STDP. Journal of Computational Neuroscience. 33(3):495-514, 2012
456. Shenkai Gu and Yaochu Jin. Heterogeneous classifier ensembles for EEG-based motor imaginary detection. 2012 UK Workshop on Computational Intelligence. Edinburgh, September 2012
457. Yaochu Jin, Hongliang Guo, and Yan Meng. A hierarchical gene regulatory network for adaptive multi-robot pattern formation. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics, 42(3):805-816, 2012. See also here for a draft.
458. Hongliang Guo, Yaochu Jin, and Yan Meng. A morphogenetic framework for self-organized multi-robot pattern formation and boundary coverage. ACM Transactions on Autonomous and Adaptive Systems, Volume 7 Issue 1, Article No. 15, April 2012. Doi:10.1145/2168260.2168275
459. Benjamin Inden, Yaochu Jin, Robert Haschke, Helge Ritter. Evolving neural fields for problems with large input and output spaces. Neural Networks, 28:24-39, 2012
460. Wissam Albukhanajer, Yaochu Jin, Johann Briffa and Godfried Williams. Evolutionary multi-objective optimization of Trace transform for invariant feature extraction. 2012 IEEE Congress on Evolutionary Computation, Brisbane, Australia, June 2012
461. Joseph Chrol-Cannon, Andre Gruning and Yaochu Jin. The emergence of polychronous groups under varying input patterns, plasticity rules and network connectivities. 2012 International Joint Conference on Neural Networks (IJCNN), Brisbane, Australia, June 2012
462. Spencer A. Thomas and Yaochu Jin. Combining genetic oscillators and switches using evolutionary algorithms. 2012 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, San Diego, USA, May 2012
463. Lisa Schramm, Yaochu Jin and Bernhard Sendhoff. Quantitative analysis of redundancy in evolution of developmental systems. 2012 IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, San Diego, USA, May 2012
464. Minh Nghia Le, Yew Soon Ong, Yaochu Jin and Bernhard Sendhoff. A unified framework for symbiosis of evolutionary mechanisms with application to water clusters potential model design. IEEE Computational Intelligence Magazine, 7(1): 20-35, 2012 (“2014 IEEE CIM Outstanding Paper Award".)
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465. Yan Meng, Yaochu Jin and Jun Yin. Modeling activity-dependent plasticity in BCM spiking neural networks with application to human behavior recognition. IEEE Transactions on Neural Networks, 22(12):1952-1966, 2011. See also here for a preprint.
466. Eva Gehrmann, Christine Glaesser, Yaochu Jin, Bernhard Sendhoff, Barbara Drossel, and Kay Hamacher. Robustness of glycolysis in yeast to internal and external noise. Physical Review E, E 84, 021913, 2011
467. Yaochu Jin and Yan Meng. Reply and Summary: Evolutionary Developmental Robotics: The Next Step to Go? Newsletter of the Autonomous Mental Development Technical Committee, Vol. 8, No 2, pp. 9-11, October 2011
468. Yaochu Jin and Yan Meng. Evolutionary Developmental Robotics: The Next Step to Go? The Newletter of the Autonomous Mental Development Technical Committee, Vol. 8, No 1, pp. 13-14, April 2011
469. Sanghoun Oh, Yaochu Jin and Moongu Jeon. Approximate models for constraint functions in evolutionary constrained optimization. International Journal of Innovative Computing, Information and Control, 7(11):6585-6603, 2011
470. Yuhua Zheng, Yan Meng, Yaochu Jin. Object recognition using a bio-inspired neuron model with bottom-up and top-down pathways. Neurocomputing, 74(17): 3158-3169, 2011. See also a preprint here.
471. Benjamin Inden, Yaochu Jin, Robert Haschke, and Helge Ritter. Evolution of multisensory integration in large neural fields. Artificial Evolution, 24-26 October 2011, Angers, France
472. Benjamin Inden, Yaochu Jin, Robert Haschke and Helge Ritter. Exploiting inherent regularity in control of multilegged robot locomotion by evolving neural fields. Third World Congress on Nature and Biologically Inspired Computing (NaBIC2011), October 19-21, 2011, Salamanca University, Spain
473. Daniel Bush, Yaochu Jin. A unified computational model of the genetic regulatory networks underlying synaptic, intrinsic and homeostatic plasticity. BMC Neuroscience, 12(Suppl 1):P161, 2011
474. Yaochu Jin. Surrogate-assisted evolutionary computation: Recent advances and future challenges. Swarm and Evolutionary Computation, 1(2):61-70, 2011 (Invited survey paper). A preprint version here.
475. Yan Meng and Yaochu Jin (Editors). Bio-Inspired Self-Organization of Robotic Systems. Springer, 2011
476. Lilian Tang, Tunde Peto, Jonathan Goh, Yaochu Jin, C. Chuluunkhuu. Filtering Normal Diabetic Retinopathy Images through Evolutionary Computation. European Journal of Ophthalmology, 21(3):347-348, 2011
477. Meiqin Liu, Senlin Zhang and Yaochu Jin. Multi-sensor optimal H∞ fusion filters for delayed nonlinear intelligent systems based on a unified model. Neural Networks, 24(3):280-290, 2011
478. Daniel Bush and Yaochu Jin, A unified computational model of the genetic regulatory networks underlying synaptic, intrinsic and homeostatic plasticity. 2011 International Conference on Wiring the Brain: Making Connections, April 12-15, 2011, County Wicklow, Ireland (oral presentation)
479. Yaochu Jin and Yan Meng. Morphogenetic robotics: An emerging new field in developmental robotics. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 41(2):145-160, 2011. A preprint version here.
480. Yan Meng, Yuyang Zhang, and Yaochu Jin. Autonomous self-reconfiguration of modular robots by evolving a hierarchical mechanochemical model. IEEE Computational Intelligence Magazine, 6(1):43-54, 2011. See a preprint here.
481. Yaochu Jin and Yan Meng. Emergence of robust regulatory motifs from in silico evolution of sustained oscillation. BioSystems, 103(1): 38-44, 2011. A prteprint version here.
482. Lisa Schramm, Yaochu Jin and Bernhard Sendhoff. Redundancy creates opportunity in developmental representations. 2011 IEEE Symposium on Artificial Life, Paris, France, April 11-15, 2011
483. Hongliang Guo, Yan Meng, and Yaochu Jin. Swarm robot pattern formation using a morphogenetic multi-cellular based self-organization algorithm. 2011 IEEE International Conference on Robotics and Automation (ICRA 2011), Shanghai, China, May 9-13, 2011
484. Yan Meng, Yuyang Zhang, Abhay Sampath, Yaochu Jin, and Bernhard Sendhoff. Cross-ball: A new morphogenetic self-reconfigurable modular robot. 2011 IEEE International Conference on Robotics and Automation (ICRA 2011), Shanghai, China, May 9-13, 2011
485. Jonanthan Goh, Lilian Tang, L. Al Turk, Yaochu Jin, Saleh, G., A combined particle swarm optimisation and genetic algorithm for context analysis of medical images. In: 4th International Conference on Health Informatics. Rome, Italy, 26-29 January, 2011
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486. Yaochu Jin, Yan Meng, Hongliang Guo. A Morphogenetic Self-Organization Algorithm for Swarm Robotic Systems using Relative Position Information. UK Workshop on Computational Intelligence. Colchester, September 8-10, 2010
487. Yan Meng and Yaochu Jin. Distributed multi-agent systems for a collective construction task based on virtual swarm intelligence. International Journal of Swarm Intelligence Research, 1(2), 58-79, 2010
488. Lisa Schramm, Vander Valente Martins, Yaochu Jin, Bernhard Sendhoff. Analysis of gene regulatory network motifs in evolutionary development of multi-cellular organisms. Artificial Life XII, pp. 133-140, Odense, Denmark, August 2010
489. Yan Meng, Yuyang Zheng and Yaochu Jin. A Morphogenetic Approach to Self-Reconfigurable Modular Robots using a Hybrid Hierarchical Gene Regulatory Network. Artificial Life XII, pp. 765-772, Odense, Denmark, August 2010
490. Ben Jones, Yaochu Jin, Bernhard Sendhoff, and Xin Yao. Emerged optimal distribution of computational workload in the evolution of an undulatory animat. The 11th International Conference on Simulation of Adaptive Behaviors (SAB 2010), August 24-28, 2010
491. Yaochu Jin, Sanghoun Oh and Moongu Jeon. Incremental approximation of nonlinear constraint functions for evolutionary constrained optimization. Congress on Evolutionary Computation, pp.2966-2973, Barcelona, July 2010
492. Xin Yu, Yaochu Jin, Ke Tang, and Xin Yao. Robust optimization over time -- A new perspective on dynamic optimization problems. Congress on Evolutionary Computation, pp. 3998-4003, Barcelona, July 2010
493. Yan Meng, Yaochu Jin, Jun Yin, and Matthew Conforth. Human activity detection using spiking neural networks regulated by a gene regulatory network. International Joint Conference on Neural Networks (IJCNN), pp.2232-2237, Barcelona, July 2010
494. Hongliang Guo, Yan Meng, and Yaochu Jin. Analysis of local communication load in shape formation of a distributed morphogenetic swarm robotic system. Congress on Evolutionary Computation (CEC), pp.1117-1124, Barcelona, July 2010
495. Yuhua Zheng, Yan Meng and Yaochu Jin. Fusing bottom-up and top-down pathways in neural networks for visual object recognition. International Joint Conference on Neural Networks (IJCNN), pp. 2064-2031, Barcelona, July 2010
496. Till Steiner, Bernhard Sendhoff, and Yaochu Jin. Evolving heterochrony for cellular differentiation using vector field embryogeny. Genetic and Evolutionary Computation Conference (GECCO), pp.571-578, Portland, July 2010
497. Benjamin Inden, Yaochu Jin, Robert Haschke, Helge Ritter. NEATfields: Evolution of neural fields for visual discrimination and multiple pole balancing tasks. Genetic and Evolutionary Computation Conference (GECCO), pp.645-646, Portland, 2010
498. Heiko Lex, Matthias Weigelt, Yaochu Jin, and Thomas Schack. Visuo-motor adaptation relies on kinesthetic representation of movement directions. North American Society for Psychology of Sport and Physical Activity (NASPSPA) Conference, Tucson, AZ, June 10-12, 2010 (abstract only)
499. Dudy Lim, Yaochu Jin, Yew-Soon Ong, and Bernhard Sendhoff. Generalizing surrogate-assisted evolutionary computation. IEEE Transactions on Evolutionary Computation, 14(3):329 - 355, 2010. A preprint version here.
500. Yaochu Jin and Jens Trommler. A fitness-independent evolvability measure for evolutionary developmental systems. IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, pp.69-76, Montreal, Canada, May 2-5 2010 PDF ( “2010 CIBCB Best Paper Award”)
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501. Till Steiner, Yaochu Jin, and Bernhard Sendhoff. Vector field embryogeny. PLoS ONE, 4(12): e8177. doi:10.1371/journal.pone.0008177, 2009
502. Ben Jones, Yaochu Jin, Bernhard Sendhoff, and Xin Yao. The effect of proprioceptive feedback on the distribution of sensory information in a model of an undulating organism. 10th European Conference on Artificial Life, Budapest, September 2009 (accepted)
503. Lisa Schramm, Yaochu Jin, Bernhard Sendhoff. Emerged coupling of motor control and morphological development in evolution of multi-cellular animates. 10th European Conference on Artificial Life, Budapest, September 2009 (accepted)
504. Andrea Finke, Yaochu Jin, Helge Ritter. A P300 based brain-robot interface for shaping human-robot interaction. Frontiers in Computational Neuroscience, Conference Abstract:Bernstein Conference on Computational Neuroscience, doi: 10.3389/conf.neuro.10.2009.14.108, 2009 (oral presentation)
505. Ben Jones, Yaochu Jin, Bernhard Sendhoff, and Xin Yao. The evolutionary emergence of neural organization in a hydra-like animat. Frontiers in Computational Neuroscience, Conference Abstract:Bernstein Conference on Computational Neuroscience, doi: 10.3389/conf.neuro.10.2009.14.057, 2009
506. Hongliang Guo, Yan Meng, and Yaochu Jin. A cellular mechanism for multi-robot construction via evolutionary multi-objective optimization of a gene regulatory network. BioSystems, 98(3):193-203, 2009
507. Till Steiner, Yaochu Jin, Lisa Schramm, and Bernhard Sendhoff. Dynamic links and evolutionary history in simulated gene regulatory networks. In: S. Das et al (eds.), Computational Methodologies in Gene Regulatory Networks, Chapter 21, pp. 498-522, 2009
508. Minh Nghia Le, Yew Soon Ong, Yaochu Jin, and Bernhard Sendhoff. Lamarkian memetic algorithms: Local optimum and connectivity structure analysis. Memetic Computing, 1(3):175-190, 2009
509. Aimin Zhou, Qingfu Zhang, Yaochu Jin. Approximating the set of Pareto-optimal solutions in both decision and objective spaces by an estimation of distribution algorithm. IEEE Transactions on Evolutionary Computation, 13(5):1167-1189, 2009
510. Yaochu Jin, Yan Meng, and Bernhard Sendhoff. Evolvability and robustness of in silico evolution of gene regulatory dynamics. In: Foundations of Systems Biology in Engineering. Omnipress, pages 68--71, 2009
511. Yaochu Jin, Hongliang Guo and Yan Meng. Robustness analysis and failure recovery of a bio-inspired self-organizing multi-robot system. In: Third IEEE International Conference on Self-Adaptive and Self-organizing Systems. IEEE Press, pages 154--164, 2009
512. Yaochu Jin and Bernhard Sendhoff. A systems approach to evolutionary multi-objective structural optimization and beyond. IEEE Computational Intelligence Magazine, 4(3):62-76, 2009. Also available here
513. Yaochu Jin and Lipo Wang (editors), Fuzzy Systems in Bioinformatics and Computational Biology. Springer, 2009
514. Ingo Paenke, Yaochu Jin, Juergen Branke. Balancing population and individual level of adaptation in changing environments. Adaptive Behavior, 17(2):153--174, 2009
515. Yaochu Jin, Robin Gruna, Bernhard Sendhoff. Pareto analysis of evolutionary and learning systems. Frontiers of Computer Science in China, 3(1):4-17, 2009
516. Martijn Meeter, Rob Veldkamp, Yaochu Jin. Multiple memory stores and operant conditioning: A rationale for memory's complexity. Brain and Cognition, 69(1):200-208, 2009
517. Till Steiner, Jens Trommler, Martin Brenn, Yaochu Jin, and Bernhard Sendhoff. Global shape with morphogen gradients and motile polarized cells. Congress on Evolutionary Computation, pp.2225-2232, May 2009, Trondheim, Norway
518. Yaochu Jin and Bernhard Sendhoff. Fuzzy logic in evolving in silico oscillatory dynamics for gene regulatory networks. In: Y. Jin and L. Wang (eds.). Fuzzy Systems in Bioinformatics and Computational Biology, pp.315-327, Springer, 2009
519. Tatsuya Okabe, Yaochu Jin, Bernhard Sendhoff. Combination of genetic algorithms and evolution strategies with self-adaptive switching. In: Goh, Chi-Keong; Ong, Yew-Soon; Tan, Kay Chen (Eds.), Multi-Objective Memetic Algorithms. pp. 281-307, Springer, 2009
520. Yaochu Jin, Yan Meng, Bernhard Sendhoff. Influence of regulation logic on the easiness of evolving sustained oscillation for gene regulatory networks. IEEE Symposium on Artificial Life (IEEE-ALIFE), pp.61-68, March 30 - April 1, 2009, Nashville, TN, USA
521. Yaochu Jin, Robin Gruna, Ingo Paenke, and Bernhard Sendhoff. Multi-objective optimization of robustness and innovation in redundant genetic representations. IEEE Symposium on Multi-Criteria Decision-Making, pp.38-45, March 30 - April 1, 2009, Nashville, TN, USA
522. Hongliang Guo, Yan Meng, Yaochu Jin. Self-adaptive multi-robot construction using gene regulatory networks. IEEE Symposium on Artificial Life (IEEE-ALIFE), pp. 53-60, March 30 - April 1, 2009, Nashville, TN, USA
523. Yaochu Jin, Lisa Schramm, and Bernhard Sendhoff. A gene regulatory model for the development of primitive nervous systems. INNS-NNN Symposia on Modeling the Brain and Nervous Systems, November 2008, Auckland, New Zealand, LNCS 5506, pp.48-55, 2009
524. Ben Jones, Yaochu Jin, Xin Yao, and Bernhard Sendhoff. Evolution of neural organization in a Hydra-like animat. 15th Int. Conf. on Neural Information Processing of the Asia-Pacific Neural Network Assembly (ICONIP'08), November 2008, Auckland, New Zealand, LNCS 5506, pp. 216-223, 2009
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525. Yaochu Jin, Bernhard Sendhoff. Pareto-based multi-objective machine learning: An overview and case studies. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 38(3):397-415, 2008. Also here.
526. Qingfu Zhang, Aimin Zhou, Yaochu Jin. RM-MEDA: A regularity model based multiobjective estimation of distribution algorithm. IEEE Transactions on Evolutionary Computation, 12(1):41--63, 2008. Also here. ( Errata: Correction of Fig.20 )
527. Dudy Lim, Yew-Soon Ong, Yaochu Jin, and Bernhard Sendhoff. Evolutionary optimization with dynamic fidelity computational models. International Conference on Intelligent Computing, pp.235-242, LNAI 5227, September 15-18, 2008, Shanghai, China
528. Ben Jones, Yaochu Jin, Bernhard Sendhoff, and Xin Yao. Evolving functional symmetry in a three dimensional model of an elongated organism. Artificial Life XI, pp.305-312, 2008 PDF
529. Till Steiner, Yaochu Jin and Bernhard Sendhoff. A cellular model for evolutionary development of lightweight materials with an inner structure. Genetic and Evolutionary Computation Conference (GECCO), pp.851-858, 2008 ( “Shortlisted for Best Paper Award”)
530. Yi Cao, Yaochu Jin, Michal Kowalczykiewicz and Bernhard Sendhoff. Prediction of convergence dynamics of design performance using differential recurrent neural networks. International Joint Conference on Neural Networks, pp.529-534, 2008, Hong Kong, China
531. Aimin Zhou, Qingfu Zhang, Yaochu Jin and Bernhard Sendhoff. Combination of EDA and DE for continuous biobjective optimization. Congress on Evolutionary Computation, pp.1447-1454, 2008, Hong Kong, China
532. Neale Samways, Yaochu Jin, Xin Yao, and Bernhard Sendhoff. Toward a gene regulatory network model for evolving chemotaxis behaviour. Congress on Evolutionary Computation, pp.2574-2581, 2008, Hong Kong, China
533. Yaochu Jin, Bernhard Sendhoff. Evolving in silico bistable and oscillatory dynamics for gene regulatory network motifs. Congress on Evolutionary Computation , pp.386-391, 2008, Hong Kong, China
534. Yaochu Jin, Bernhard Sendhoff, Edgar Körner. Rule extraction from compact Pareto-optimal neural networks. In: Multi-objective Evolutionary Algorithms for Knowledge Discovery from Databases, A. Ghosh et al (eds.), pp. 71-90, Springer, 2008
535. Yaochu Jin, Aimin Zhou, Qingfu Zhang, Bernhard Sendhoff, and Edward Tsang. Modeling regularity to improve scalability of model-based multi-objective optimization algorithms. In: J. Knowles, D. Corne, K. Deb (eds.), Multi-Objective Problem Solving from Nature, pp. 331-356, Springer, 2008
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536. Shengxiang Yang, Yew-Soon Ong, and Yaochu Jin (editors) Evolutionary Computation in Dynamic and Uncertain Environments , Springer, 2007
537. Dudy Lim, Yew-Soon Ong, Yaochu Jin, Bernhard Sendhoff, Bu-Sung Lee. Efficient hierarchical parallel genetic algorithms using grid computing. Future Generation Computer Systems -- The International Journal of Grid Computing: Theory, Methods and Applications. 23(4):658--670, 2007 PDF
538. Aimin Zhou, Qingfu Zhang, Yaochu Jin, Bernhard Sendhoff. Adaptive modeling strategy for continuous multi-objective optimization. Congress on Evolutionary Computation, pp.431--437, Singapore, September 2007 PDF
539.
Till Steiner, Lisa Schramm, Yaochu
Jin, Bernhard Sendhoff. Emergence of feedback in artificial gene regulatory
networks. Congress on Evolutionary Computation, pp.867--874, Singapore,
September 2007 ( 10
finalist for best paper award)
Available upon request.
540. Yaochu Jin, Ruojing Wen, and Bernhard Sendhoff. Evolutionary multi-objective optimization of spiking neural networks. International Conference on Neural Networks, LNCS 4668, 1:370--379, 2007 PDF
541. Dudy Lim, Yew-Soon Ong, Yaochu Jin, Bernhard Sendhoff. A study on metamodeling techniques, ensembles, and multi-surrogates in evolutionary computation. Genetic and Evolutionary Computation Conference (GECCO), pp.1288--1295, July 8-11, 2007, London PDF
542. Aimin Zhou, Qingfu Zhang, Yaochu Jin, Bernhard Sendhoff and Edward Tsang. Global multi-objective optimization via estimation of distribution algorithm with biased initialization and crossover. Genetic and Evolutionary Computation Conference (GECCO), pp.617--623, July 8-11, 2007, London PDF
543. Ingo Paenke, Juergen Branke, and Yaochu Jin. On the influence of phenotype plasticity on genotype diversity. 2007 IEEE Symposium on Foundations of Computational Intelligence (FOCI) , pp. 33-40, April 1-4, 2007, Honolulu, Hawaii PDF ( “Best Student Paper Award”)
544. Aimin Zhou, Yaochu Jin, Qingfu Zhang, Bernhard Sendhoff, Edward Tsang. Prediction-based population re-initialization for evolutionary dynamic multi-objective optimization. The Fourth International Conference on Evolutionary Multi-Criterion Optimization, LNCS 4403, pp. 832--846, March 5-8, 2007, Matsushima, Japan. PDF
545. Dudy Lim, Yew-Soon Ong, Meng-Hiot Lim, and Yaochu Jin. Single/multi-objective inverse robust evolutionary design methodology in the presence of uncertainty. In: S. Yang, Y.S. Ong, and Y. Jin (eds.), Evolutionary Computation in Dynamic and Uncertain Environments, pp.437-456, Springer, 2007
546. Lars Graenling, Yaochu Jin, Bernhard Sendhoff. Individual-based management of meta-models for evolutionary optimization with applications to three-dimensional blade optimization. In: S. Yang, Y.S. Ong, and Y. Jin (eds.), Evolutionary Computation in Dynamic and Uncertain Environments, pp.225-250, Springer, 2007
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547. Yaochu Jin (editor). Multi-Objective Machine Learning. Springer, Berlin Heidelberg. 2006
548. Dudy Lim, Yew-Soon Ong, Yaochu Jin, Bernhard Sendhoff, and Bu Sung Lee. Inverse multi-objective robust evolutionary optimization. Genetic Programming and Evolvable Machines. 7(4):383--404, 2006 Also here
549. Ingo Paenke, Juergen Branke, and Yaochu Jin. Efficient search for robust solutions by means of evolutionary algorithms and fitness approximation. IEEE Transactions on Evolutionary Computation . 10(4):405-420, 2006 ( Authors contributed equally.) Also here.
550. Kwasi Foli, Tatsuya Okabe, Markus Olhofer, Yaochu Jin, and Bernhard Sendhoff. Optimization of micro heat exchanger: CFD, analytical approaches and multi-objective evolutionary algorithms. International Journal of Heat and Mass Transfer. 49:1090-1099, 2006
551. Aimin Zhou, Qingfu Zhang, Yaochu Jin, Bernhard Sendhoff, Edward Tsang. Modeling the population distribution in multi-objective optimization by generative topographic mapping. Parallel Problem Solving from Nature IX, LNCS 4193, pp.443-452, 2006, Reykjavik, Iceland PDF
552. Dudy Lim, Yew-Soon Ong, Yaochu Jin, Bernhard Sendhoff. Trusted evolutionary algorithms. IEEE Congress on Evolutionary Computation, pp.456-463, July 2006, Vancouver
553. Lars Gräning, Yaochu Jin, Bernhard Sendhoff. Generalization improvement in multi-objective learning. International Joint Conference on Neural Networks, pp.9893-9900, July 2006, Vancouver
554. Yaochu Jin, Bernhard Sendhoff. Alleviating catastrophic forgetting via multi-objective learning. International Joint Conference on Neural Networks, pp.6367-6374, July 2006, Vancouver
555. Aimin Zhou, Yaochu Jin, Qingfu Zhang, Bernhard Sendhoff, Edward Tsang. Combining model-based and genetics-based offspring generation for multi-objective optimization using a convergence criterion. IEEE Congress on Evolutionary Computation, pp.3234-3240, July 2006, Vancouver
556. Yaochu Jin, Bernhard Sendhoff, Edgar Körner. Simultaneous generation of accurate and interpretable neural network classifiers. In: Multi-Objective Machine Learning, Y. Jin (ed.), pp.281-300, Springer, Berlin Heidelberg, 2006
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557. Lipo Wang and Yaochu Jin (editors), 2005 International Conference on Fuzzy Systems and Knowledge Discovery. Part I and Part II, LNAI 3613 and 3614, Springer, August 2005
558. Rothlauf, F., Branke, J., Codnoni, S., Corne, D.W., Drechsler, R., Jin, Y., Machado, P., Marchiori, E., Romerero, J., Smith, G.D., Squillero, G. (editors). Applications of Evolutionary Computing. LNCS 3449, Springer, March 2005
559. Yaochu Jin (editor). Knowledge Incorporation in Evolutionary Computation. Springer, Berlin Heidelberg, 2005 Table of Contents(PDF file)
560.
Yaochu Jin and Juergen
Branke. Evolutionary optimization in uncertain environments - A survey.
IEEE Transactions on Evolutionary Computation, 9(3), 303-317, 2005. Also
here.
Citations according to Google Scholar
561. Hanli Wang, Sam Kwong, Yaochu Jin, Wei Wei and K. Man. Agent-based evolutionary approach to interpretable rule-based knowledge extraction. IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews, 35(2), 143-155, 2005
562.
Hanli Wang, Sam Kwong, Yaochu
Jin, Wei Wei and K. Man. A
multi-objective hierarchical genetic algorithm for interpretable rule-based
knowledge extraction. Fuzzy Sets and Systems, 149(1),
149-186, 2005
Citations according to Google Scholar
563.
Yaochu Jin. A comprehensive survey of fitness
approximation in evolutionary computation. Soft Computing,
9(1), 3-12, 2005, Springer
Citations according to Google Scholar
564. Michael Huesken, Yaochu Jin and Bernhard Sendhoff. Structure optimization of neural networks for evolutionary design optimization. Soft Computing, 9(1), 21-28, 2005
565. Aimin Zhou, Qingfu Zhang, Yaochu Jin, Edward Tsang, Tatsuya Okabe. A model-based evolutionary algorithm for bi-objective optimization. Congress on Evolutionary Computation, pp.2568-2575, Edinburgh, September 2005
566. Vineet Khare, Xin Yao, Bernhard Sendhoff, Yaochu Jin, and Heiko Wersing. Co-evolutionary modular neural networks for automatic problem decomposition. Congress on Evolutionary Computation, pp.2691-2698, Edinburgh, September 2005
567. Tatsuya Okabe, Yaochu Jin, and Bernhard Sendhoff. Theoretical comparisons of search dynamics of genetic algorithms and evolution strategies. Congress on Evolutionary Computation, pp.382-389, Edinburgh, September 2005
568. Tatsuya Okabe, Yaochu Jin, and Bernhard Sendhoff. A new approach to dynamics analysis of genetic algorithms without selection. Congress on Evolutionary Computation, pp.374-381, Edinburgh, September 2005
569. Yaochu Jin, Markus Olhofer, and Bernhard Sendhoff. On evolutionary optimization of large problems with small populations. Int. Conf. on Natural Computation. LNCS, 3611, pp.1145-1154, Springer, Changsha, China
570. Lars Gräning, Yaochu Jin, Bernhard Sendhoff. Efficient evolutionary optimization using individual-based evolution control and neural networks: A comparative study. European Symposium on Artificial Neural Networks (ESANN'2005). pp.273-278, Bruges, April 2005
571. Yaochu Jin, Bernhard Sendhoff, and Edgar Körner. Evolutionary multi-objective optimization for simultaneous generation of signal-type and symbol-type representations. The Third International Conference on Evolutionary Multi-Criterion Optimization. LNCS 3410, pp.752-766, Springer, Guanajuato, Mexico, March 9-11, 2005
572. Yaochu Jin, Michael Huesken, Markus Olhofer and Bendhard Sendhoff. Neural networks for fitness approximation in evolutionary optimization. In: Y. Jin (ed.), Knowledge Incorporation in Evolutionary Computation,, pp.281-306, Springer, Berlin Heidelberg, 2005
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573. Raidl, G., Cagnoni, S., Branke, J., Corne, D.W., Drechsler, R., Jin, Y., Johnson, C.G., Machado, P., Marchiori, E., Rothlauf, F., Smith, G.D., Squillero, G. (editors). Applications of Evolutionary Computing. LNCS 3005, Springer, April 2004
574. Yaochu Jin, Bernhard Sendhoff, and Edgar Körner. Evolutionary multi-objective model selection: A step towards smooth transitions between signal-type and symbol-type representations? Workshop on "Soft Computing for Information Mining" within KI 2004, Ulm, September 20-21, 2004 (not peer reviewed)
575. Tatsuya Okabe, Yaochu Jin, Markus Olhofer, and Bernhard Sendhoff. On test functions for evolutionary multi-objective optimization. Parallel Problem Solving from Nature, VIII, LNCS 3242, Springer, pp.792-802, September 2004
576. Tatsuya Okabe, Yaochu Jin, Bernhard Sendhoff and Markus Olhofer. Voronoi-based estimation of distribution algorithm for multi-objective optimization. CEC'04, pp. 1594-1602, Portland, 2004
577.
Yaochu Jin, Tatsuya Okabe
and Bernhard Sendhoff. Neural network
regularization and ensembling using multi-objective evolutionary algorithms.
Congress on Evolutionary Computation, pp.1-8, Portland, 2004
Citations according to Google Scholar
578.
Yaochu Jin and Bernhard
Sendhoff. Reducing fitness
evaluations using clustering techniques and neural network ensembles.(draft)
Genetic and Evolutionary Computation Conference. LNCS
3102, Springer, pp. 688-699, Seattle, 2004
Citations according to Google Scholar
579. Yaochu Jin and Bernhard Sendhoff. Constructing dynamic test problems using the multi-objective optimization concept. In: Applications of Evolutionary Computing. LNCS 3005, Raidl, G.R.; Cagnoni, S.; Branke, J.; Corne, D.W.; Drechsler, R.; Jin, Y.; Johnson, C.G.; Machado, P.; Marchiori, E.; Rothlauf, F.; Smith, G.D.; Squillero, G. (eds.) pp.525-536, Springer, 2004
580. Yaochu Jin, Tatsuya Okabe and Bernhard Sendhoff. Evolutionary multi-objective approach to constructing neural network ensembles for regression. In: C. Coello Coello (ed.), Applications of Evolutionary Multi-objective Optimization, pp. 653-672. World Scientific, 2004
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581. Yaochu Jin. Advanced Fuzzy Systems Design and Applications . Physica-Verlag/Springer-Verlag, Heidelberg, 2003 (ISBN: 3-7908-1537-3)Table of Contents (PDF file).
582.
Yaochu Jin and Bernhard
Sendhoff, Extracting interpretable fuzzy
rules from RBF networks. Neural Processing Letters, 17(2),
149-164, 2003
Citations according to Google Scholar
583. Yaochu Jin and Bernhard Sendhoff. Connectedness, regularity and the success of local search in evolutionary multi-objective optimization. In: Proceedings of the IEEE Congress on Evolutionary Computation, Vol.3, pp.1910-1917, 2003
584. Lars Willmes, Thomas Bäck,Yaochu Jin and Bernhard Sendhoff. Comparing neural networks and kriging in fitness approximation in evolutionary optimization. In: Proceedings of the IEEE Congress on Evolutionary Computation, Vol.1, pp.663-670, 2003
585.
Tatsuya Okabe, Yaochu Jin
and Bernhard Sendhoff. A
critical survey of performance indices for multi-objective optimization.In:
Proceedings of the IEEE Congress on Evolutionary Computation, Vol.2,
pp.878-885, 2003
Citations according to Google Scholar
586. Tatsuya Okabe, Kwasi Foli, Markus Olhofer, Yaochu Jin and Bernhard Sendhoff. Comparative studies on micro heat exchanger optimization. In: Proceedings of the IEEE Congress on Evolutionary Computation, Vol.1, pp.647-654, 2003
587. Tatsuya Okabe, Yaochu Jin and Bernhard Sendhoff. Evolutionary multi-objective optimization with a hybrid representation.In: Proceedings of the IEEE Congress on Evolutionary Computation , Vol.4, pp. 2262-2269, 2003
588. Yaochu Jin, Tatsuya Okabe and Bernhard Sendhoff. Solving three-objective optimization problems using evolutionary dynamic weighted aggregation: Results and analysis. In: Proceedings of Genetic and Evolutionary Computation Conference. pp.636, Chicago, 2003
589.
Yaochu Jin and Bernhard
Sendhoff. (Corrected version)
Trade-off between performance and robustness: An evolutionary multiobjective
approach. In: Proceedings of Second International Conference on
Evolutionary Multi-criteria Optimization. LNCS
2632, Springer, pp.237-251, Faro, April 2003
Citations according to Google Scholar
590. Yaochu Jin, Michael Huesken and Bernhard Sendhoff. Quality measures for approximate models in evolutionary computation. In: Proceedings of the GECCO Workshop on "Learning, Adaptation and Approximation in Evolutionary Computation", pp.170-174, Chicago, 2003 (not peer reviewed)
591. Yaochu Jin. Interpretability improvement of RBF-based neuro-fuzzy systems using regularized learning. In: J. Cassilas et al (eds.), Interpretability Issues in Fuzzy Modeling, Chapter 26, pp.605-620, Springer, 2003
592. Yaochu Jin. Generating distinguishable, complete, consistent and compact fuzzy systems using evolutionary algorithms. In: J. Cassilas et al (eds.), Accuracy Improvements in Fuzzy Modeling , Chapter 5, pp.100-118, Springer, 2003.
593. Yaochu Jin. Brain controlled devices - An overview. Internal Report, Honda Research Institute Europe, HRI-EU 03-13, September, 2003
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594.
Yaochu Jin, Markus Olhofer
and Bernhard Sendhoff. A framework for
evolutionary optimization with approximate fitness functions. IEEE
Transactions on Evolutionary Computation, 6(5), 481-494, 2002
Citations according to Google Scholar
595. Yaochu Jin and Bernhard Sendhoff. Fuzzy preference incorporation into evolutionary multi-objective optimization. In: Proceedings of the 4th Asia-Pacific Conference on Simulated Evolution and Learning, Vol.1, pp.26-30, Singapore, Nov. 2002
596. Tatsuya Okabe, Yaochu Jin, Bernhard Sendhoff. On the dynamics of multiobjective optimization. In: Proceedings of Genetic and Evolutionary Computation Conference, pp. 247-256, New York, July 2002. ( Best paper nomination)
597.
Yaochu Jin. Fitness approximation in evolutionary
computation - A survey. In: Proceedings of Genetic and
Evolutionary Computation Conference, pp.1105-1112, New York, July 2002.
Citations according to Google Scholar
598. Yaochu Jin and Bernhard Sendhoff. Incorporation of fuzzy preferences into evolutionary multiobjective optimization. In: Proceedings of Genetic and Evolutionary Computation Conference, pp.683, New York, July 2002.
599. Dissertation: Knowledge in evolutionary and learning systems. Institute for Neuroinformatics, Ruhr-University Bochum, Germany. Shaker Verlag, Aachen, 2002. (ISBN: 3-8265-9749-4)
600. Markus Olhofer, Toshiyuki Arima, Yaochu Jin, Toyotaka Sonoda and Bernhard Sendhoff. Optimization of transonic gas turbine blades with evolution strategies. Honda R&D Technical Review, 14(1), 203-216, 2002
601. Yaochu Jin. Knowledge in evolutionary and learning systems. Ph.D. thesis. Institute for Neuroinformatics, Ruhr-University Bochum, Germany. Shaker Verlag, Aachen, 2002. (ISBN: 3-8265-9749-4)
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602.
Yaochu Jin, Markus Olhofer
and Bernhard Sendhoff. Managing approximate models in evolutionary aerodynamic
design optimization. In: Proceedings of IEEE Congress on Evolutionary
Computation, vol.1, pp.592-599. Seoul, Korea, May 2001
Citations according to Google Scholar
603. Markus Olhofer, Yaochu Jin and Bernhard Sendhoff. Adaptive encoding for aerodynamic shape optimization using evolution strategies. In: Proceedings of IEEE Congress on Evolutionary Computation, vol.1, pp.576-583, Seoul, Korea, May 2001
604.
Yaochu Jin, Markus Olhofer
and Bernhard Sendhoff. Dynamic weighted
aggregation for evolutionary multi-objective optimization: Why does it work and
how? In: Proceedings of Genetic and Evolutionary Computation
Conference, pp.1042-1049, San Francisco, USA, 2001.
Citations according to Google Scholar
A more detailed description with applications can be
found in the unpublished manuscript:
Effectiveness of weighted sum of the objectives for evolutionary
multi-objective optimization: Methods, analysis and applications. Unpublished
manuscript. 2002
605. Yaochu Jin, Markus Olhofer and Bernhard Sendhoff. Managing approximate models in parallel evolutionary optimization. HRE-G/FTR Report 00-03, Honda R&D Europe, Offenbach/Main, 2000.
606.
Yaochu Jin, Tatsuya Okabe
and Bernhard Sendhoff. Adapting weighted
aggregation for multiobjective evolution strategies. In: Proceedings
of the First International Conference on Evolutionary Multi-criterion
Optimization. LNCS
1993, Springer, pp.96-110, Zurich, Switzerland, March 7-9, 2001.
Citations according to Google Scholar
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607.
Yaochu Jin. Fuzzy modeling of high-dimensional systems:
Complexity reduction and interpretability improvement. IEEE
Transactions on Fuzzy Systems, 8(2), 212-221, 2000.
Highly cited article (top 1% within its field) according to Essential
Science Indicators (SM) of Thomson
ISI
Citations according to Google Scholar
608. Yaochu Jin, Markus Olhofer and Bernhard Sendhoff. On evolutionary optimization with approximate fitness functions. In: Proceedings of the Genetic and Evolutionary Computation Conference GECCO, Las Vegas, Nevada, USA. pp.786- 793, July 10-12, 2000.
609. Yaochu Jin, Werner von Seelen and Bernhard Sendhoff. Extracting Interpretable Fuzzy Rules from RBF Neural Networks. Internal Report 2000-02, Institut für Neuroinformatik, Ruhr-Universität Bochum, 44780 Bochum, Germany, February 2000.
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610. Yaochu Jin and Bernhard Sendhoff. Knowledge incorporation into neural networks from fuzzy rules. Neural Processing Letters, 10(3), 231-242, 1999.
611.
Yaochu Jin, Werner von Seelen and Bernhard Sendhoff. On generating FC3(flexible, complete, consistent and compact) fuzzy rule systems from
data using evolution strategies. IEEE Transactions on Systems,
Man and Cybernetics, Part B: Cybernetics, 29(6), 829-845, 1999.
Citations according to Google Scholar
612.
Yaochu Jin and Werner von
Seelen. Evaluating flexible fuzzy controllers via evolution strategies. Fuzzy
Sets and Systems, 108, 243-252, 1999
Citations according to Google Scholar
613. Anna Buczak, Yaochu Jin, Houshang Darabi and Mohsen Jafari. Genetic algorithm based sensor network optimization for target tracking. Intelligent Engineering Systems through Artificial Neural Networks, C.H.Dagli, A. Buczak, J. Ghosh, M. Embrechs and O. Ersoy(eds.), Vol. 9, pp.349-354, 1999.
614. Richard Burne, Anna Buczak, Yaochu Jin, Vikram Jamalabad, Ivan Kadar and Eitan Eadan. A self-organizing, cooperative sensor network for remote surveillance: Current results. SPIE Proceedings, Unattended Ground Sensor Technologies and Applications., Edward Carapezza, David Law and Terry Stalker(eds.), Vol.3713, pp.238-248, 1999.
615. Yaochu Jin and Jingping Jiang. Techniques in neural network based fuzzy system identification and their applications to control of complex systems. In: Cornelius T. Leondes(ed.), Fuzzy Theory Systems: Techniques and Applications, Chapter 5, pp.112-128, Vol. 1, Academic Press, San Diego, USA, 1999.
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616.
Yaochu Jin. Decentralized adaptive fuzzy control of robot
manipulators. IEEE Transactions on Systems, Man and Cybernetics,
Part B: Cybernetics, 28(1), 47-57, 1998
Citations according to Google Scholar
617.
Yaochu Jin, Werner von
Seelen and Bernhard Sendhoff. An approach to
rule-based knowledge extraction. In: Proceedings IEEE
International Conference on Fuzzy Systems, Anchorage, Alaska, pp.1188-1193,
1998.
Citations according to Google Scholar
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618.
Yaochu Jin and Wang Jie. Intelligent
Control: Theory and Applications, Henan Science and Technology Publishing
House, Zhengzhou, China, 1997 (in Chinese) (ISBN: 7-5349-1983-5)
(This book is based mainly on the textbook I prepared for a
graduate course "Intelligent Control" at the Department of Electrical
Engineering, Zhejiang University during 1993-1994)
619. Yaochu Jin, Jingping Jiang. Performance analysis of fuzzy controllers based on genetic algorithms. Pattern Recognition and Artificial Intelligence 10(1):75-80, 1997 (in Chinese)
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620. Yaochu Jin, Jingping Jiang. Two approaches to fuzzy optimal control. Proceedings of Chinese Society of Electrical Engineering. 16(3):201-204, 1996 (in Chinese)
621. Yaochu Jin and Jingping Jiang. Optimization of fuzzy control rules by means of genetic algorithms. Control and Decision, 11(6):672-676, 1996 (in Chinese)
622. Yaochu Jin. Intelligent modeling and control of complex systems. Ph.D. thesis. Electrical Eng. Dept., Zhejiang University, Hangzhou, May 1996
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623.
Yaochu Jin, Jingping Jiang
and Jing Zhu. Neural network based fuzzy
identification and its applications to modeling and control of complex systems.
IEEE Transactions on Systems, Man and Cybernetics, 25(6),
990-997, 1995
Citations according to Google Scholar
624. Yaochu Jin, Jing Zhu and Jingping Jiang. Adaptive fuzzy identification with applications. International Journal of Systems Science,6(2), 197-212, 1995.
625. Yaochu Jin, Jing Zhu. Neural network based fuzzy modeling and its simulation techniques. Journal of Systems Simulation, 7(2):46-55, 1995 (in Chinese)
626. Yaochu Jin, Jingping Jiang. Neuro-fuzzy control of robot manipulators. Chinese Journal of Robot. 17(3):157-163, 1995 (in Chinese)
627. Yaochu Jin, Jingping Jiang. A neural network model with applications. Journal of Zhejiang University, 29(3):340-347, 1995 (in Chinese)
628. Yaochu Jin. Design and analysis of fuzzy controllers. In: J. Zhu (Ed.), Fuzzy Control, Chapter 5, pp.240-312, Mechanics Industry Press, Beijing, China, 1995 (in Chinese)
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629. Yaochu Jin, Jingping Jiang. Fuzzy logic integrated multivariable adaptive neuro-control. Information and Control, 23(4):223-228, 1994 (in Chinese)
630. Yaochu Jin, Jing Zhu. Neural network based self-learning fuzzy control. Chinese Journal of Eletronics Technology, 4:35-40, 1994 (in Chinese)
631. Yaochu Jin, Jing Zhu and Jingping Jiang. State estimation and adaptive control of multivariable systems using fuzzy logic and neural networks. AMSE Advances in Modeling and Analysis, 43(2), 1994.
632. Yaochu Jin, Xiaodong Shen. Two-level hierarchical intelligent fuzzy control of servo systems. Journal of Zhejiang University, 28(6):644-654, 1994 (in Chinese)
633. Yaochu Jin, Jing Zhu and Jingping Jiang. Fuzzy linearization of nonlinear systems. In: Proceedings IEEE International Conference on Fuzzy Systems, pp.1688-1672, Orlando, Florida, USA, 1994
634. Yaochu Jin and Jingping Jiang. A novel paradigm of nonlinear system control with applications. In :Proceedings IFAC Symposium on Robot Control, Capri, Italy, 1994
635. Yaochu Jin, Jingping Jiang. Fuzzy identification with neural networks. In: Proceedings of the Chinese National Conference on Decision and Control. Xiamen, May, 1994 (in Chinese)
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636. Yaochu Jin, Jingping Jiang. Adaptive fuzzy prediction with application to weather forecast. Pattern Recognition and Artificial Intelligence, 6(4):283-290, 1993 (in Chinese)
637. Yaochu Jin, Jingping Jiang. Neural network based non-linear feedback control. Journal of Zhejiang University, 27, 1993 (in Chinese)
638. Yaochu Jin and Jingping Jiang. Implemening self-organizing fuzzy controllers with hybrid Pi-Sigma neural networks. In: The Third International Workshop on Advanced Motion Control, Berkeley, California, USA, 1993
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639. Yaochu Jin, Jingping Jiang. Fuzzy logic intergrated variable structure control of a class of nonlinear systems. Control and Decision, 7(1):36-40, 1992 (in Chinese)
640. Yaochu Jin, Jingping Jiang. Artificial neural networks in robot control- A survey. Robot, 14(6):54-58, 1992 (in Chinese)
641. Yaochu Jin, Jingping Jiang. Neural network as fuzzy membership functions in neural fuzzy systems. In: Proceedings of the Chinese National Youth Conference on Robotics and Automation. Harbin, August, 1992 (in Chinese)
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642. Yaochu Jin, Jingping Jiang. A novel robust adaptive control of robot manipulators. In: Proceedings of the Chinese National Conference on Robotics and Automation, Harbin, Oct., 1990 (in Chinese)
643. Yaochu Jin Dynamic control of robot manipulators. Master thesis. Electrical Eng. Dept., Zhejiang University, Hangzhou, December 1990
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