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 01.10.2021:

Google Scholar: h-index: 80, i10-index: 287, citations: 27,765.

Publon, h-index: 57, citations: 13,527. Scopus Author Profile: h-index=63, citations = 16,012;

Research Gate: RG Score: 47.29, h-index: 74, citations: 23,068.

DBLP Computer Science Bibliography.

IEEE Xplore Author Profile.

Computer Scientist National and World Ranking according to Guide2Research.

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

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In Press / Accepted / Under Review

1. Qing Chen, Yaochu Jin, and Y. D. Song. Fault-tolerant adaptive tracking control of Euler-Lagrange systems: An echo state network approach driven by reinforcement learning. Neurocomputing, 2021 (accepted)

2. 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, 2021 (accepted)

3. 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, 2021 (accepted)

4. 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, 2021 (accepted)

5. Jinjin Xu, Yaochu Jin, and Wenli Du. A federated data-driven evolutionary algorithm for expensive multi/many-objective optimization. Complex & Intelligent Systems, 2021 (accepted)

6. 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, 2021 (accepted)

7. Hangyu Zhu and Yaochu Jin. Real-time federated evolutionary neural architecture search. IEEE Transactions on Evolutionary Computation, 2021 (accepted)

8. Hangyu Zhu, Jinjin Xu, Shiqing Liu and Yaochu Jin. Federated learning on non-iid data: A survey. Neurocomputing, 2021 (accepted)

9. 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, 2021 (accepted)

10. Wei Du, Wenjiang Song, Yang Tang, Yaochu Jin, and Feng Qian. Searching for robustness intervals in evolutionary robust optimization. IEEE Transactions on Evolutionary Computation, 2021 (accepted)

11. 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, 2021 (accepted)

12. 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, 2021 (accepted)

13. 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, 2021 (accepted)

14. 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, 2021 (accepted)

15. Xiaojun Zhou, Jianpeng Long, Yaochu Jin, Guo Yu, Chunhua Yang. A fast constrained state transition algorithm. Neurocomputing, 2021 (accepted)

16. Tonghao Wang, Xingguang Peng, Yaochu Jin and Demin Xu. Experience sharing based memetic transfer learning for multiagent reinforcement learning. Memetic Computing, 2021 (accepted)

17. 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, 2021 (accepted)

18. 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, 2021 (accepted)

19. 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, 2021 (accepted)

20. Xinjie Wang, Yaochu Jin and Kuangrong Hao. Computational modeling of structural synaptic plasticity in echo state networks. IEEE Transactions on Cybernetics, 2021 (accepted)

21. 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, 2021 (accepted)

22. 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, 2021 (accepted)

23. 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, 2020 (Accepted)

Matlab code on GitHub

24. 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, 2020 (accepted)

25. 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, 2020 (accepted)

26. 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, 2020 (accepted)

27. Ataollah Ramezan Shirazi and Yaochu Jin. Regulated morphogen gradients for target surrounding and adaptive shape formation. IEEE Transactions on Cognitive and Developmental Systems, 2020 (accepted)

28. 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, 2020 (accepted)

2021

29. Jinjin Xu, Yaochu Jin, Wenli Du, and Sai Gu. A federated data-driven evolutionary algorithm. Knowledge-Based Systems, 233, 107532, December 2021

30. 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

31. 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

32. 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

33. 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

34. Yaochu Jin, Handing Wang, Chaoli Sun. Data-driven evolutionary optimization. Springer, June 2021

35. 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

36. 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

37. 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

38. Jia Liu and Yaochu Jin. Multi-objective search of robust neural architectures against multiple types of adversarial attacks. Neurocomputing, 453: 73-84, 2021

39. 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

40. 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, 51(6): 3115-3128, 2021

41. 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, 5(6): 3129-3142, 2021

42. 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

43. Xinjie Wang, Yaochu Jin, and Kuangrong Hao. Synergies between synaptic and intrinsic plasticity in echo state networks. Neurocomputing, 432: 32-43, 2021

44. Hangyu Zhu, Haoyu Zhang, and Yaochu Jin. From federated learning to federated neural architecture search: A survey. Complex & Intelligent Systems, 7:639–657, 2021

45. Pengfei Huang, Handing Wang, and Yaochu Jin. Offline data-driven evolutionary optimization based on tri-training. Swarm and Evolutionary Computation, 60:100800, 2021

46. 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

47. Qian Zhang, Jie Lu, and Yaochu Jin. Artificial intelligence in recommender systems. Complex & Intelligent Systems, 7:439–457, 2021

48. Sampo Kuutti, Richard Bowden, Yaochu Jin, Phil Barber, and Saber Fallah. A survey of deep learning applications to autonomous vehicle control. IEEE Transactions on Intelligent Transportation Systems, 22(2): 712 – 733, 2021

49. 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

50. 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

51. Peng Liao, Chaoli Sun, Guochen Zhang and Yaochu Jin. Multi-surrogate multi-tasking optimization of expensive problems. Knowledge-Based Systems, 551: 23-38, 2021

52. 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

53. 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

54. 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

55. 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

56. 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

57. 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

2020

58. 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

59. 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

60. 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.

61. 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

62. 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

63. 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

64. 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

65. Yan Zhou, Yaochu Jin, and Jinliang Ding. Surrogate-assisted evolutionary search of spiking neural architectures in liquid state machines. Neurocomputing, 406: 12-23, 2020

66. Yuanjun Huang, Yaochu Jin, Kuangrong Hao. Decision-making and multi-objectivization for cost sensitive robust optimization over time. Knowledge-Based Systems, 199: 105857, 2020

67. Yang Chen, Yaochu Jin, Xiaoyan Sun. Language model based interactive estimation of distribution algorithm. Knowledge-Based Systems, 200: 105980, 2020

68. 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

69. 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

70. 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

71. 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

72. 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

73. 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

74. Dujuan Wang, Yunqiang Yin, and Yaochu Jin. Rescheduling Under Disruptions in Manufacturing Systems. Springer, Singapore, 2020

75. Hangyu Zhu and Yaochu Jin. Multi-objective evolutionary federated learning. IEEE Transactions on Neural Networks and Learning Systems, 31(4): 1310-1322, 2020

76. 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

77. 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

78. 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

79. 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

80. 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

81. 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

82. 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

83. 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

84. 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

85. 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)

86. 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

87. 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

88. 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

89. Ye Tian, Ran Cheng, Xingyi Zhang and Yaochu Jin. Techniques for accelerating multi-objective evolutionary algorithms in PlatEMO. Congress on Evolutionary Computation (CEC 2020), Glasgow, UK, July 2020

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2019

90. 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

91. 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

92. 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

93. 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

94. 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

95. 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

96. 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.

97. 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

98. 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

99. 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

100.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

101.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

102.Xinjie Wang, Yaochu Jin, and Kuangrong Hao. Echo state networks regulated by local intrinsic plasticity rules for regression. Neurocomputing, 351: 111-122, 2019

103.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

104.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

105.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

106.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

107.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.

108.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

109.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

110.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

111.Murillo. G. Carneiro, Ran Cheng, Liang Zhao, Yaochu Jin. Particle swarm optimization for network-based data classification. Neural Networks, 110: 243-255, 2019

112.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

113.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

114.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

115.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

116.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

117.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

118.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

119.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

120.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

121.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

122.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

123.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

124.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

125.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

126.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

127.Ruwang Jiao, Sanyou Zeng, Changhe Li, Yuhong Jiang and Yaochu Jin. A complete expected improvement criterion for Gaussian process assisted highly constrained expensive optimization. Information Sciences, 471, 80-96, 2019

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2018

128.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

129.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

130.Ran Cheng, Cheng He, Yaochu Jin, and Xin Yao. Model-based evolutionary algorithms – A short survey. Complex & Intelligent Systems, 4:283-292, 2018

131.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

132.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

133.Haibo Yu, Ying Tan, Jianchao Zeng, Chaoli Sun and Yaochu Jin. Surrogate-assisted hierarchical particle swarm optimization. Information Sciences, 454-455: 59-72, 2018

134.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

135.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

136.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

137.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.

138.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

139.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

140.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

141.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

142.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)

143.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.

144.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

145.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.

146.Xingyi Zhang, Xiutao Zheng, Ran Cheng, Jianfeng Qiu, and Yaochu Jin. A competitive mechanism based multi-objective particle swarm optimizer with fast convergence. Information Sciences, 427:63-76,2018

Matlab code here.

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2017

147.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

148.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

149.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”)

150.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

151.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

152.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

153.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

154.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

155.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

156.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

157.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

158.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

159.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

160.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

161.Tian Jie, Tan Ying, Sun Chaoli, Zeng Jianchao, Yu Haibo 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

162.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

163.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

164.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

165.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

166.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.

167.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.

168.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

169.Shenkai Gu and Yaochu Jin. Multi-train: A semi-supervised heterogeneous ensemble classifier. Neurocomputing, 249:202-211, 2017

170.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

171.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

172.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

173.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.

174.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

175.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

176.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

177.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

178.Handing Wang and Yaochu Jin. Efficient nonlinear correlation detection for decomposed search in evolutionary multi-objective optimization. Congress on Evolutionary Computation, 649-656, June 2017

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2016

179.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.

180.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

181.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

182.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.

183.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

184.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.

185.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

186.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

187.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

188.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

189.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

190.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

191.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

192.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

193.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.

194.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

195.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

196.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

197.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

198.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

199.Yongsheng Ding, Tao Zhang, Lihong Ren, Yaochu Jin, Kuangrong Hao and Lei Chen. Immune-inspired self-adaptive collaborative control allocation for multi-level stretching processes. Information Sciences, 342:81-95, 2016

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2015

200.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.

201.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.

202.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.

203.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.

204.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

205.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

206.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.

207.Shenkai Gu, Ran Cheng and Yaochu Jin. Multi-objective ensemble generation. WIREs Data Mining and Knowledge Discovery, 5(5): 234-245, 2015

208.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.

209.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

210.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.

211.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.

212.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

213.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

214.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

215.Yanling Jin, Yongsheng Ding, Kuangrong Hao and Yaochu Jin. An endocrine-based intelligent distributed cooperative algorithm for target tracking in wireless sensor networks. Soft Computing, 19(5):1427-1441, 2015

216.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.

217.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

218.Ran Cheng, Yaochu Jin and Kaname Narukawa. Adaptive reference vector generation for inverse model based evolutionary multiobjective optimization with degenerate and disconnected Pareto fronts. The 8th Int. Conf. on Evolutionary Multi-Criterion Optimization (EMO'2015), pp.127-140, Guimar?es, Portugal. A draft here.

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2014

219.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".)

220.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

221.Joseph Chrol-Cannon and Yaochu Jin. Computational modeling of neural plasticity for self-organization of neural networks. BioSystems, 125:43-54, 2014 Also here

222.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

223.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

224.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

225.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

226.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

227.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

228.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.

229.Spencer A. Thomas and Yaochu Jin. Reconstructing gene regulatory networks: Where optimization meets big data. Evolutionary Intelligence, 7(1):29-47, 2014

230.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.

231.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

232.Ran Cheng and Yaochu Jin. Demonstrator selection in a social learning particle swarm optimizer. IEEE Congress on Evolutionary Computation, July 2014, Beijing, China

233.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

234.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

235.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

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2013

236.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

237.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

238.Ran Cheng and Yaochu Jin. On the competition mechanism of the competitive particle swarm optimizer. UK Workshop on Computational Intelligence, September 9-11, 2013

239.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

240.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

241.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)

242.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.

243.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.

244.Mingh Nhgia Le, Yew Soon Ong, Stefan Menzel, Yaochu Jin, and Bernhard Sendhoff. Evolution by adapting surrogates. Evolutionary Computation, 21(2):313-340, 2013

245.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

246.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

247.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

248.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

249.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

250.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

251.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

252.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

253.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.

254.Wissen A. Albukhanajer, Yaochu Jin, Johann A. Briffa, and Godfried Williams. A comparative study of multi-objective evolutionary Trace Transform algorithms for robust feature extraction. The 7th Int. Conf. on Evolutionary Multi-Criterion Optimization (EMO 2013), 19-22 March 2013, Sheffield, UK

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2012

255.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

256.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

257.Daniel Bush and Yaochu Jin. Calcium control of hippocampal STDP. Journal of Computational Neuroscience. 33(3):495-514, 2012

258.Shenkai Gu and Yaochu Jin. Heterogeneous classifier ensembles for EEG-based motor imaginary detection. 2012 UK Workshop on Computational Intelligence. Edinburgh, September 2012

259.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.

260.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

261.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

262.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

263.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

264.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

265.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

266.Minh Nghia Le, Yew Soon Ong, Yaochu Jin and Bernhard Sendhoff. A unified framework for symbiosis of evolutionary mechanisms with application to water clusters potential model design. IEEE Computational Intelligence Magazine, 7(1): 20-35, 2012 (“2014 IEEE CIM Outstanding Paper Award".)

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2011

267.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.

268.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

269.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

270.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

271.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

272.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.

273.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

274.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

275.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

276.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.

277.Yan Meng and Yaochu Jin (Editors). Bio-Inspired Self-Organization of Robotic Systems. Springer, 2011

278.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

279.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

280.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)

281.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.

282.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.

283.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.

284.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

285.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

286.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

287.Jonanthan Goh, Lilian Tang, L. Al Turk, Yaochu Jin, Saleh, G., A combined particle swarm optimisation and genetic algorithm for context analysis of medical images. In: 4th International Conference on Health Informatics. Rome, Italy, 26-29 January, 2011

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2010

288.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

289.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

290.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

291.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

292.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

293.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

294.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

295.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

296.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

297.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

298.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

299.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

300.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)

301.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.

302.Yaochu Jin and Jens Trommler. A fitness-independent evolvability measure for evolutionary developmental systems. IEEE Symposium on Computational Intelligence in Bioinformatics and Computational Biology, pp.69-76, Montreal, Canada, May 2-5 2010 PDF ( “2010 CIBCB Best Paper Award”)

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2009

303.Till Steiner, Yaochu Jin, and Bernhard Sendhoff. Vector field embryogeny. PLoS ONE, 4(12): e8177. doi:10.1371/journal.pone.0008177, 2009

304.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)

305.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)

306.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)

307.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

308.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

309.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

310.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

311.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

312.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

313.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

314.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

315.Yaochu Jin and Lipo Wang (editors), Fuzzy Systems in Bioinformatics and Computational Biology. Springer, 2009

316.Ingo Paenke, Yaochu Jin, Juergen Branke. Balancing population and individual level of adaptation in changing environments. Adaptive Behavior, 17(2):153--174, 2009

317.Yaochu Jin, Robin Gruna, Bernhard Sendhoff. Pareto analysis of evolutionary and learning systems. Frontiers of Computer Science in China, 3(1):4-17, 2009

318.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

319.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

320.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

321.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

322.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

323.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

324.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

325.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

326.Ben Jones, Yaochu Jin, Xin Yao, and Bernhard Sendhoff. Evolution of neural organization in a Hydra-like animat. 15th Int. Conf. on Neural Information Processing of the Asia-Pacific Neural Network Assembly (ICONIP'08), November 2008, Auckland, New Zealand, LNCS 5506, pp. 216-223, 2009

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2008

327.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.

328.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 )

329.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

330.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

331.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”)

332.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

333.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

334.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

335.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

336.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

337.Yaochu Jin, Aimin Zhou, Qingfu Zhang, Bernhard Sendhoff, and Edward Tsang. Modeling regularity to improve scalability of model-based multi-objective optimization algorithms. In: J. Knowles, D. Corne, K. Deb (eds.), Multi-Objective Problem Solving from Nature, pp. 331-356, Springer, 2008

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2007

338.Shengxiang Yang, Yew-Soon Ong, and Yaochu Jin (editors) Evolutionary Computation in Dynamic and Uncertain Environments , Springer, 2007

339.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

340.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

341.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.

342.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

343.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

344.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

345.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”)

346.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

347.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

348.Lars Graenling, Yaochu Jin, Bernhard Sendhoff. Individual-based management of meta-models for evolutionary optimization with applications to three-dimensional blade optimization. In: S. Yang, Y.S. Ong, and Y. Jin (eds.), Evolutionary Computation in Dynamic and Uncertain Environments, pp.225-250, Springer, 2007

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2006

349.Yaochu Jin (editor). Multi-Objective Machine Learning. Springer, Berlin Heidelberg. 2006

350.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

351.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.

352.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

353.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

354.Dudy Lim, Yew-Soon Ong, Yaochu Jin, Bernhard Sendhoff. Trusted evolutionary algorithms. IEEE Congress on Evolutionary Computation, pp.456-463, July 2006, Vancouver

355.Lars Gräning, Yaochu Jin, Bernhard Sendhoff. Generalization improvement in multi-objective learning. International Joint Conference on Neural Networks, pp.9893-9900, July 2006, Vancouver

356.Yaochu Jin, Bernhard Sendhoff. Alleviating catastrophic forgetting via multi-objective learning. International Joint Conference on Neural Networks, pp.6367-6374, July 2006, Vancouver

357.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

358.Yaochu Jin, Bernhard Sendhoff, Edgar Körner. Simultaneous generation of accurate and interpretable neural network classifiers. In: Multi-Objective Machine Learning, Y. Jin (ed.), pp.281-300, Springer, Berlin Heidelberg, 2006

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2005

359.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

360.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

361.Yaochu Jin (editor). Knowledge Incorporation in Evolutionary Computation. Springer, Berlin Heidelberg, 2005 Table of Contents(PDF file)

362.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

363.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

364.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

365.Yaochu Jin. A comprehensive survey of fitness approximation in evolutionary computation. Soft Computing, 9(1), 3-12, 2005, Springer
Citations according to Google Scholar

366.Michael Huesken, Yaochu Jin and Bernhard Sendhoff. Structure optimization of neural networks for evolutionary design optimization. Soft Computing, 9(1), 21-28, 2005

367.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

368.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

369.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

370.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

371.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

372.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

373.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

374.Yaochu Jin, Michael Huesken, Markus Olhofer and Bendhard Sendhoff. Neural networks for fitness approximation in evolutionary optimization. In: Y. Jin (ed.), Knowledge Incorporation in Evolutionary Computation,, pp.281-306, Springer, Berlin Heidelberg, 2005

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2004

375.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

376.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)

377.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

378.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

379.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

380.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

381.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

382.Yaochu Jin, Tatsuya Okabe and Bernhard Sendhoff. Evolutionary multi-objective approach to constructing neural network ensembles for regression. In: C. Coello Coello (ed.), Applications of Evolutionary Multi-objective Optimization, pp. 653-672. World Scientific, 2004

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2003

383.Yaochu Jin. Advanced Fuzzy Systems Design and Applications . Physica-Verlag/Springer-Verlag, Heidelberg, 2003 (ISBN: 3-7908-1537-3)Table of Contents (PDF file).

384.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

385.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

386.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

387.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

388.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

389.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

390.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

391.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

392.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)

393.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

394.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.

395.Yaochu Jin. Brain controlled devices - An overview. Internal Report, Honda Research Institute Europe, HRI-EU 03-13, September, 2003

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2002

396.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

397.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

398.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)

399.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

400.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.

401.Dissertation: Knowledge in evolutionary and learning systems. Institute for Neuroinformatics, Ruhr-University Bochum, Germany. Shaker Verlag, Aachen, 2002. (ISBN: 3-8265-9749-4)

402.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

403.Yaochu Jin. Knowledge in evolutionary and learning systems. Ph.D. thesis. Institute for Neuroinformatics, Ruhr-University Bochum, Germany. Shaker Verlag, Aachen, 2002. (ISBN: 3-8265-9749-4)

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2001

404.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

405.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

406.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

407.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.

408.Yaochu Jin, Tatsuya Okabe and Bernhard Sendhoff. Adapting weighted aggregation for multiobjective evolution strategies. In: Proceedings of the First International Conference on Evolutionary Multi-criterion Optimization. LNCS 1993, Springer, pp.96-110, Zurich, Switzerland, March 7-9, 2001.
Citations according to Google Scholar

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2000

409.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

410.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.

411.Yaochu Jin, Werner von Seelen and Bernhard Sendhoff. Extracting Interpretable Fuzzy Rules from RBF Neural Networks. Internal Report 2000-02, Institut für Neuroinformatik, Ruhr-Universität Bochum, 44780 Bochum, Germany, February 2000.

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1999

412.Yaochu Jin and Bernhard Sendhoff. Knowledge incorporation into neural networks from fuzzy rules. Neural Processing Letters, 10(3), 231-242, 1999.

413.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

414.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

415.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.

416.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.

417.Yaochu Jin and Jingping Jiang. Techniques in neural network based fuzzy system identification and their applications to control of complex systems. In: Cornelius T. Leondes(ed.), Fuzzy Theory Systems: Techniques and Applications, Chapter 5, pp.112-128, Vol. 1, Academic Press, San Diego, USA, 1999.

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1998

418.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

419.Yaochu Jin, Werner von Seelen and Bernhard Sendhoff. An approach to rule-based knowledge extraction. In: Proceedings IEEE International Conference on Fuzzy Systems, Anchorage, Alaska, pp.1188-1193, 1998.
Citations according to Google Scholar

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1997

420.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)

421.Yaochu Jin, Jingping Jiang. Performance analysis of fuzzy controllers based on genetic algorithms. Pattern Recognition and Artificial Intelligence 10(1):75-80, 1997 (in Chinese)

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1996

422.Yaochu Jin, Jingping Jiang. Two approaches to fuzzy optimal control. Proceedings of Chinese Society of Electrical Engineering. 16(3):201-204, 1996 (in Chinese)

423.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)

424.Yaochu Jin. Intelligent modeling and control of complex systems. Ph.D. thesis. Electrical Eng. Dept., Zhejiang University, Hangzhou, May 1996

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1995

425.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

426.Yaochu Jin, Jing Zhu and Jingping Jiang. Adaptive fuzzy identification with applications. International Journal of Systems Science,6(2), 197-212, 1995.

427.Yaochu Jin, Jing Zhu. Neural network based fuzzy modeling and its simulation techniques. Journal of Systems Simulation, 7(2):46-55, 1995 (in Chinese)

428.Yaochu Jin, Jingping Jiang. Neuro-fuzzy control of robot manipulators. Chinese Journal of Robot. 17(3):157-163, 1995 (in Chinese)

429.Yaochu Jin, Jingping Jiang. A neural network model with applications. Journal of Zhejiang University, 29(3):340-347, 1995 (in Chinese)

430.Yaochu Jin. Design and analysis of fuzzy controllers. In: J. Zhu (Ed.), Fuzzy Control, Chapter 5, pp.240-312, Mechanics Industry Press, Beijing, China, 1995 (in Chinese)

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1994

431.Yaochu Jin, Jingping Jiang. Fuzzy logic integrated multivariable adaptive neuro-control. Information and Control, 23(4):223-228, 1994 (in Chinese)

432.Yaochu Jin, Jing Zhu. Neural network based self-learning fuzzy control. Chinese Journal of Eletronics Technology, 4:35-40, 1994 (in Chinese)

433.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.

434.Yaochu Jin, Xiaodong Shen. Two-level hierarchical intelligent fuzzy control of servo systems. Journal of Zhejiang University, 28(6):644-654, 1994 (in Chinese)

435.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

436.Yaochu Jin and Jingping Jiang. A novel paradigm of nonlinear system control with applications. In :Proceedings IFAC Symposium on Robot Control, Capri, Italy, 1994

437.Yaochu Jin, Jingping Jiang. Fuzzy identification with neural networks. In: Proceedings of the Chinese National Conference on Decision and Control. Xiamen, May, 1994 (in Chinese)

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1993

438.Yaochu Jin, Jingping Jiang. Adaptive fuzzy prediction with application to weather forecast. Pattern Recognition and Artificial Intelligence, 6(4):283-290, 1993 (in Chinese)

439.Yaochu Jin, Jingping Jiang. Neural network based non-linear feedback control. Journal of Zhejiang University, 27, 1993 (in Chinese)

440.Yaochu Jin and Jingping Jiang. Implemening self-organizing fuzzy controllers with hybrid Pi-Sigma neural networks. In: The Third International Workshop on Advanced Motion Control, Berkeley, California, USA, 1993

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1992

441.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)

442.Yaochu Jin, Jingping Jiang. Artificial neural networks in robot control- A survey. Robot, 14(6):54-58, 1992 (in Chinese)

443.Yaochu Jin, Jingping Jiang. Neural network as fuzzy membership functions in neural fuzzy systems. In: Proceedings of the Chinese National Youth Conference on Robotics and Automation. Harbin, August, 1992 (in Chinese)

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1990

444.Yaochu Jin, Jingping Jiang. A novel robust adaptive control of robot manipulators. In: Proceedings of the Chinese National Conference on Robotics and Automation, Harbin, Oct., 1990 (in Chinese)

445.Yaochu Jin Dynamic control of robot manipulators. Master thesis. Electrical Eng. Dept., Zhejiang University, Hangzhou, December 1990

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Last update in June, 2021. Please pay attention to the copyrights. For enquiries, contact Yaochu Jin.