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 04.08.2023:
Orcid: https://orcid.org/0000-0003-1100-0631 Guide2Research
Profile
Google
Scholar: h-index: 101, i10-index: 364, citations:
41,768
Web of Science, h-index:
77, citations: 22,595
Scopus
Author Profile: h-index=81, citations = 26,034
Research
Gate: h-index: 94, citations: 35,744
DBLP Computer Science Bibliography.
PlatEMO, a Single-, Multi-
and Many-objective Optimization Tool
1.
Xi Zhang, Yaochu
Jin, and Feng Qian. A self-adaptive dynamic multi-objective optimization
algorithm based on transfer learning and elitism-based mutation. Neurocomputing,
2023 (accepted)
2.
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, 2023 (accepted)
3.
Xueming Yan, Zhihang Fang
and Yaochu Jin. An adaptive n-gram transformer for multi-scale scene
text recognition. Knowledge-Based Systems, 2023 (accepted)
4.
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, 2023
(accepted)
5.
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, 2023 (accepted)
6. 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, 2023 (accepted)
7.
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, 2023 (accepted)
8.
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, 2023 (accepted)
9.
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, 2023 (accepted)
10.
Qiqi Liu, Felix Lanfermann, Tobias Rodemann, Markus Olhofer, and Yaochu Jin.
Surrogate-assisted many-objective optimization of building energy management. IEEE
Computational Intelligence Magazine, 2023 (accepted)
11.
Leming Wu, Yaochu Jin, Kuangrong
Hao. Optimized compressed sensing for
communication efficient federated learning. Knowledge-Based Systems, 2023
(accepted)
12. Zhun Fan, Zhaojun Wang, Wenji Li,
Xiaomin Zhu, Bingliang Hu, An-Min Zou, Weidong Bao,
Minqiang Gu, Zhifeng Hao,
Yaochu Jin. Automated pattern generation for swarm robots using constrained
multi-objective genetic programming. Swarm and Evolutionary Computation, 81, 2023
13. 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, 2023 (accepted)
14.
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, 2023 (accepted)
15.
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, 2023 (accepted)
16.
Yuping Yan, Mohammed B.M.
Kamel, Marcell Zoltay, Marcell Gal, Roland Hollos, Yaochu
Jin, Peter Ligeti and Akos Tenyi.
FedlabX: A practical and privaxy-preserving framework for federated learning. Complex &
Intelligent Systems, 2023 (accepted)
17.
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, 2023 (accepted)
18.
Zhenshou SongHanding Wang
19.
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, 2023
(accepted)
20. 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, 2023 (accepted)
21. Hangyu Zhu, Xilu Wang, and Yaochu Jin. Federated many-task Bayesian optimization. IEEE Transactions on Evolutionary Computation, 2023 (accepted)
22. 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, 2023 (accepted)
23. 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, 2023 (accepted)
24. 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, 2023 (accepted)
25. 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, 2023 (accepted)
26. 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, 2023 (accepted)
27. 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, 2023 (accepted)
28. 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, 2023 (accepted)
29. 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, 2023 (accepted)
30. 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, 2023 (accepted)
31. Cheng He, Lianghao Li, Ran Cheng and Yaochu Jin. Evolutionary multiobjective optimization via efficient sampling-based offspring generation. Complex & Intelligent Systems, 2023 (accepted)
32. Xilu Wang and Yaochu Jin. Personalized Bayesian optimization for noisy problems. Complex & Intelligent Systems, 2023 (accepted)
33. 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, 2022 (accepted)
34. 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)
35.
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, 2022 (accepted)
36.
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, 2022
(accepted)
37.
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, 2022 (accepted)
38.
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, 2022
39. 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, 2022 (accepted)
40. 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, 2022 (accepted)
41.
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,
2022 (accepted)
42.
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, 2022 (accepted)
43. 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, 2022 (accepted)
44. 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, 2022 (accepted)
45.
Hangyu Zhu, Rui Wang, Yaochu Jin, and Kaitai
Liang. PIVODL:
Privacy-preserving vertical federated learning over distributed labels. IEEE
Transactions on Artificial Intelligence, 2021 (accepted)
46. Yaochu Jin. Computational evolution of neural and morphological systems. Springer, 2023
47. 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
48. 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
49. 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
50. 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
51. 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
52. 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
53.
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)
54. 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
55. Xilu Wang, Yaochu Jin, Sebastian Schmitt and Markus Olhofer. Recent advances in Bayesian Optimization. ACM Computing Surveys, 55:287, 2023
56. 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
57.
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
58. 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
59. 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)
60. 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
61. 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
62. Jia
Liu, Ran Cheng, and Yaochu Jin. Bi-fidelity evolutionary multiobjective
search for adversarially robust deep neural architectures. Neurocomputing, 550: 126465, 2023
63. 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
64. 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
65. 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
66. 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
67. 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
68. 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
69. 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
70. Shuangming Yang, Yanwei Oang, Tao Lei, and Yaochu Jin. Spike-driven multi-scale learning with hybrid mechanisms of spiking dendrites. Neurocomputing, 542:120246, 2023
71. 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
72.
Hui
Bai, Ran Cheng, and Yaochu Jin. Evolutionary reinforcement learning: A survey. Intelligent Computing,
0025, April 2023. DOI: 10.34133/icomputing.0025
73.
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
74. 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
75. 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
76. Ye
Tian, Weijian Zhu, Xingyi
Zhang, and Yaochu Jin. A
practical tutorial on solving optimization problems via PlatEMO. Neurocomputing,
518: 190-205, 2023
77. 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
78. 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
79. 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
80.
Yaochu Jin, Hangyu Zhu, Jinjin
Xu, and Yang Chen. Federated Learning: Fundamentals and
Advances. Springer. 2022
81. 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
82. 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
83.
Shiqing Liu, Haoyu
Zhang, and Yaochu Jin. A survey on computationally efficient neural
architecture search. Journal of Automation and Intelligence,
1(1): 100002,
2022
84.
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
85.
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
86. 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
87. 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
88. 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
89.
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
90.
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
91.
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
92. 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
93. 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
94. 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
95. 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
96. 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
97. 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
98. 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
99. 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
100.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
101.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
102.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
103.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
104.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
105.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
106.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
107.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
108.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
109.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
110.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
111.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
112.Hangyu
Zhu and Yaochu Jin. Real-time
federated evolutionary neural architecture search. IEEE Transactions on Evolutionary Computation, 26(2): 364-378, 2022
113.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
114.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
115.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
116.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
117.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
118.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
119.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
120.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
121.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
122.Xiaojun Zhou, Jianpeng
Long, Yaochu Jin, Guo Yu, Chunhua
Yang. A
fast constrained state transition algorithm. Neurocomputing, 470:29-39, 2022
123.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
124.Yaochu Jin, Handing Wang, Chaoli Sun. Data-Driven Evolutionary Optimization. Springer, June 2021 (Monograph)
125.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
126.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
127.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
128.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
129.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
130.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
131.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
132.Hangyu Zhu, Jinjin Xu, Shiqing Liu and Yaochu Jin. Federated
learning on non-iid data: A survey. Neurocomputing, 465: 371-390, 2021
133.Jinjin Xu, Yaochu
Jin, Wenli Du, and Sai Gu. A
federated data-driven evolutionary algorithm. Knowledge-Based Systems,
233:107532, December 2021
134.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
135.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
136.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
137.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
138.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
139.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
140.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
141.Jia Liu and Yaochu Jin. Multi-objective
search of robust neural architectures against multiple types of adversarial
attacks. Neurocomputing, 453:
73-84, 2021
142.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
143.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
144.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
145.Xinjie Wang, Yaochu Jin, and Kuangrong Hao. Synergies
between synaptic and intrinsic plasticity in echo state networks. Neurocomputing, 432: 32-43, 2021
146.Hangyu Zhu, Haoyu Zhang, and Yaochu
Jin. From
federated learning to federated neural architecture search: A survey. Complex & Intelligent Systems,
7:639–657, 2021
147.Pengfei Huang, Handing Wang, and Yaochu Jin. Offline
data-driven evolutionary optimization based on tri-training. Swarm and Evolutionary Computation,
60:100800, 2021
148.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
149.Qian Zhang, Jie Lu, and Yaochu Jin. Artificial
intelligence in recommender systems. Complex
& Intelligent Systems, 7:439–457, 2021
150.Sampo Kuutti,
151.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
152.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
153.Peng Liao,
Chaoli Sun, Guochen Zhang and Yaochu Jin. Multi-surrogate
multi-tasking optimization of expensive problems. Knowledge-Based Systems, 551: 23-38, 2021
154.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
155.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
156.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
157.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
158.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
159.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
160.Dujuan Wang, Yunqiang Yin,
and Yaochu Jin. Rescheduling Under
Disruptions in Manufacturing Systems. Springer, Singapore, 2020 (Monograph)
161.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
162.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
163.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.
164.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
165.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
166.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
167.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
168.Yan Zhou, Yaochu Jin, and Jinliang
Ding. Surrogate-assisted
evolutionary search of spiking neural architectures in liquid state machines.
Neurocomputing, 406: 12-23, 2020
169.Yuanjun Huang, Yaochu
Jin, Kuangrong Hao. Decision-making
and multi-objectivization for cost sensitive robust optimization over time.
Knowledge-Based Systems, 199: 105857,
2020
170.Yang Chen, Yaochu Jin, Xiaoyan
Sun. Language
model based interactive estimation of distribution algorithm. Knowledge-Based Systems, 200: 105980, 2020
171.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
172.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
173.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
174.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
175.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
176.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
177.Hangyu Zhu
and Yaochu Jin. Multi-objective
evolutionary federated learning. IEEE
Transactions on Neural Networks and Learning Systems, 31(4): 1310-1322,
2020
178.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
179.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
180.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
181.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
182.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
183.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
184.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
185.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
186.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
187.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)
188.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
189.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
190.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
191.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
192.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
193.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
194.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
195.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
196.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
197.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
198.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.
199.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
200.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
201.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
202.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
203.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
204.Xinjie Wang, Yaochu
Jin, and Kuangrong Hao. Echo
state networks regulated by local intrinsic plasticity rules for regression.
Neurocomputing, 351: 111-122, 2019
205.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
206.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
207.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
208.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
209.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.
210.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
211.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
212.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
213.Murillo.
G. Carneiro, Ran Cheng, Liang Zhao, Yaochu
Jin. Particle
swarm optimization for network-based data classification. Neural Networks, 110: 243-255, 2019
214.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
215.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
216.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
217.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
218.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
219.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
220.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
221.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
222.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
223.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
224.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
225.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
226.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
227.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
228.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
229.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
230.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
231.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
232.Ran Cheng, Cheng He, Yaochu Jin, and Xin Yao. Model-based
evolutionary algorithms – A short survey. Complex & Intelligent Systems, 4:283-292, 2018
233.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
234.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
235.Haibo Yu, Ying Tan, Jianchao
Zeng, Chaoli Sun and Yaochu Jin. Surrogate-assisted
hierarchical particle swarm optimization. Information Sciences, 454-455: 59-72, 2018
236.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
237.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
238.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
239.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.
240.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
241.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
242.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
243.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
244.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)
245.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.
246.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
247.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.
248.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.
249.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
250.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
251.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”)
252.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
253.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
254.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
255.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
256.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
257.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
258.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
259.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
260.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
261.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
262.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
263.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
264.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
265.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
266.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
267.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
268.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.
269.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.
270.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
271.Shenkai Gu and Yaochu Jin. Multi-train:
A semi-supervised heterogeneous ensemble classifier. Neurocomputing,
249:202-211, 2017
272.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
273.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
274.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
275.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.
276.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
277.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
278.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
279.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
280.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
281.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.
282.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
283.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
284.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.
285.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
286.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.
287.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
288.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
289.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
290.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
291.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
292.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
293.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
294.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
295.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.
296.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
297.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
298.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
299.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
300.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
301.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
302.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.
303.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.
304.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.
305.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.
306.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
307.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
308.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.
309.Shenkai Gu, Ran Cheng and Yaochu Jin. Multi-objective ensemble generation. WIREs Data Mining and Knowledge Discovery, 5(5): 234-245, 2015
310.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.
311.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
312.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.
313.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.
314.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
315.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
316.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
317.Yanling Jin, Yongsheng Ding, Kuangrong Hao and Yaochu Jin.
318.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.
319.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
320.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.
321.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".)
322.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
323.Joseph Chrol-Cannon and Yaochu
Jin. Computational modeling of neural plasticity for self-organization
of neural networks. BioSystems, 125:43-54, 2014 Also here
324.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
325.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
326.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
327.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
328.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
329.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
330.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.
331.Spencer A. Thomas and Yaochu Jin. Reconstructing gene regulatory networks: Where
optimization meets big data. Evolutionary
Intelligence,
7(1):29-47, 2014
332.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.
333.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
334.Ran Cheng and Yaochu Jin. Demonstrator selection in a
social learning particle swarm optimizer. IEEE Congress on Evolutionary Computation, July 2014, Beijing, China
335.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
336.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
337.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".) here
338.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
339.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
340.Ran Cheng and Yaochu Jin. On the competition
mechanism of the competitive particle swarm optimizer. UK Workshop on Computational Intelligence, September 9-11, 2013
341.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
342.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
343.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)
344.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.
345.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.
346.Mingh Nhgia Le, Yew Soon Ong,
Stefan Menzel, Yaochu Jin, and Bernhard Sendhoff. Evolution
by adapting surrogates. Evolutionary
Computation,
21(2):313-340, 2013
347.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
348.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
349.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
350.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
351.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
352.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
353.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
354.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
355.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.
356.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
357.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
358.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
359.Daniel Bush and Yaochu Jin. Calcium control
of hippocampal STDP. Journal of Computational
Neuroscience.
33(3):495-514, 2012
360.Shenkai Gu and Yaochu Jin. Heterogeneous classifier
ensembles for EEG-based motor imaginary detection. 2012 UK Workshop on Computational Intelligence. Edinburgh, September 2012
361.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.
362.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
363.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
364.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
365.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
366.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
367.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
368.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".)
369.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.
370.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
371.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
372.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
373.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
374.Yuyang Zhang, 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.
375.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
376.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
377.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
378.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.
379.Yan Meng and Yaochu Jin (Editors). Bio-Inspired Self-Organization of Robotic Systems. Springer, 2011
380.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
381.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
382.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)
383.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.
384.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.
385.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.
386.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
387.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
388.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
389.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
390.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
391.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
392.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
393.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
394.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
395.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
396.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
397.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
398.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
399.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
400.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
401.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
402.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)
403.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.
404.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”)
405.Till Steiner, Yaochu Jin, and Bernhard Sendhoff. Vector field embryogeny. PLoS ONE, 4(12): e8177. doi:10.1371/journal.pone.0008177,
2009
406.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)
407.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)
408.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)
409.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
410.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
411.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
412.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
413.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
414.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
415.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
416.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
417.Yaochu Jin and Lipo Wang (editors), Fuzzy Systems in Bioinformatics and Computational Biology. Springer, 2009
418.Ingo Paenke, Yaochu Jin, Juergen Branke. Balancing
population and individual level of adaptation in changing environments. Adaptive Behavior,
17(2):153--174, 2009
419.Yaochu Jin, Robin Gruna, Bernhard Sendhoff. Pareto
analysis of evolutionary and learning systems. Frontiers of Computer Science in China, 3(1):4-17, 2009
420.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
421.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
422.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
423.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
424.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
425.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
426.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
427.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
428.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
429.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.
430.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 )
431.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
432.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
433.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”)
434.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
435.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
436.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
437.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
438.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
439.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
440.Shengxiang Yang, Yew-Soon Ong, and Yaochu Jin
(editors) Evolutionary
Computation in Dynamic and Uncertain Environments , Springer, 2007
441.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
442.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
443.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.
444.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
445.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
446.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
447.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”)
448.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
449.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
450.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
451.Yaochu Jin (editor). Multi-Objective
Machine Learning. Springer, Berlin Heidelberg. 2006
452.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
453.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.
454.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
455.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
456.Dudy Lim, Yew-Soon Ong, Yaochu Jin, Bernhard
Sendhoff. Trusted evolutionary algorithms. IEEE Congress on Evolutionary Computation, pp.456-463, July 2006, Vancouver
457.Lars Gräning, Yaochu Jin,
Bernhard Sendhoff. Generalization improvement in
multi-objective learning. International
Joint Conference on Neural Networks, pp.9893-9900, July 2006, Vancouver
458.Yaochu Jin, Bernhard Sendhoff. Alleviating catastrophic
forgetting via multi-objective learning. International Joint Conference on Neural Networks, pp.6367-6374, July 2006, Vancouver
459.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
460.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
461.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
462.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
463.Yaochu Jin (editor). Knowledge Incorporation in Evolutionary Computation.
Springer, Berlin Heidelberg, 2005 Table of Contents(PDF file)
464.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
465.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
466.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
467.Yaochu Jin. A comprehensive survey of fitness approximation
in evolutionary computation. Soft
Computing,
9(1), 3-12, 2005, Springer
Citations
according to Google
Scholar
468.Michael Huesken, Yaochu
Jin and Bernhard Sendhoff. Structure optimization of
neural networks for evolutionary design optimization. Soft Computing,
9(1), 21-28, 2005
469.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
470.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
471.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
472.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
473.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
474.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
475.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
476.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
477.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
478.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)
479.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
480.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
481.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
482.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
483.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
484.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
485.Yaochu Jin. Advanced Fuzzy Systems Design and Applications . Physica-Verlag/Springer-Verlag, Heidelberg, 2003 (ISBN: 3-7908-1537-3)Table of Contents (PDF file).
486.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
487.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
488.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
489.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
490.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
491.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
492.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
493.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
494.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)
495.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
496.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.
497.Yaochu Jin. Brain controlled devices - An overview. Internal Report, Honda
Research Institute Europe, HRI-EU 03-13, September,
2003
498.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
499.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
500.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)
501.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
502.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.
503.Dissertation: Knowledge in evolutionary and learning systems. Institute for Neuroinformatics, Ruhr-University Bochum, Germany. Shaker
Verlag, Aachen, 2002. (ISBN: 3-8265-9749-4)
504.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
505.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)
506.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
507.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
508.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
509.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.
510.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
511.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
512.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.
513.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.
514.Yaochu Jin and Bernhard Sendhoff. Knowledge incorporation
into neural networks from fuzzy rules. Neural
Processing Letters,
10(3), 231-242, 1999.
515.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
516.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
517.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.
518.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.
519.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.
520.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
521.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
522.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)
523.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)
524.Yaochu Jin, Jingping Jiang. Two approaches to fuzzy
optimal control. Proceedings of Chinese Society of
Electrical Engineering.
16(3):201-204, 1996 (in Chinese)
525.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)
526.Yaochu Jin. Intelligent modeling and control of complex systems. Ph.D. thesis.
Electrical Eng. Dept., Zhejiang University, Hangzhou, May 1996
527.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
528.Yaochu Jin, Jing Zhu and Jingping Jiang. Adaptive fuzzy
identification with applications. International
Journal of Systems Science,6(2), 197-212, 1995.
529.Yaochu Jin, Jing Zhu. Neural network based fuzzy modeling and its simulation
techniques. Journal of Systems Simulation, 7(2):46-55, 1995 (in Chinese)
530.Yaochu Jin, Jingping Jiang. Neuro-fuzzy control of robot
manipulators. Chinese Journal of Robot. 17(3):157-163, 1995 (in Chinese)
531.Yaochu Jin, Jingping Jiang. A neural network model with
applications. Journal of Zhejiang University, 29(3):340-347, 1995 (in Chinese)
532.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)
533.Yaochu Jin, Jingping Jiang. Fuzzy logic integrated
multivariable adaptive neuro-control. Information
and Control,
23(4):223-228, 1994 (in Chinese)
534.Yaochu Jin, Jing Zhu. Neural network based self-learning fuzzy control. Chinese Journal of Eletronics Technology, 4:35-40, 1994 (in Chinese)
535.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.
536.Yaochu Jin, Xiaodong Shen. Two-level hierarchical
intelligent fuzzy control of servo systems. Journal
of Zhejiang University,
28(6):644-654, 1994 (in Chinese)
537.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
538.Yaochu Jin and Jingping Jiang. A novel paradigm of
nonlinear system control with applications. In :Proceedings IFAC Symposium on Robot Control, Capri, Italy, 1994
539.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)
540.Yaochu Jin, Jingping Jiang. Adaptive fuzzy prediction
with application to weather forecast. Pattern
Recognition and Artificial Intelligence, 6(4):283-290, 1993 (in Chinese)
541.Yaochu Jin, Jingping Jiang. Neural network based
non-linear feedback control. Journal
of Zhejiang University, 27,
1993 (in Chinese)
542.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
543.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)
544.Yaochu Jin, Jingping Jiang. Artificial neural networks
in robot control- A survey. Robot, 14(6):54-58, 1992 (in Chinese)
545.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)
546.</