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 01.07.2021:
Google
Scholar: h-index: 77, i10-index: 279, citations:
26,226.
Publon, h-index:
54, citations: 12,464. Scopus
Author Profile: h-index=61, citations = 14,954;
Research
Gate: RG Score: 46.75, h-index: 72, citations: 21,721.
DBLP Computer Science Bibliography.
Computer Scientist National
and World Ranking according to Guide2Research.
PlatEMO, a Single-, Multi-
and Many-objective Optimization Tool
1.
Hangyu
Zhu and Yaochu Jin. Real-time federated evolutionary neural architecture search.
IEEE Transactions on Evolutionary
Computation, 2021 (accepted)
2.
Hangyu
Zhu, Jinjin Xu, Shiqing Liu and Yaochu
Jin. Federated learning on non-iid data: A survey. Neurocomputing, 2021 (accepted)
3.
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)
4.
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)
5.
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)
6.
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)
7.
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)
8.
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)
9.
Xiaojun Zhou, Jianpeng Long, Yaochu Jin, Guo Yu, Chunhua Yang. A fast
constrained state transition algorithm. Neurocomputing,
2021 (accepted)
10.
Tonghao
Wang, Xingguang Peng, Yaochu Jin and
Demin Xu. Experience
sharing based memetic transfer learning for multiagent reinforcement learning.
Memetic Computing, 2021 (accepted)
11.
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)
12. 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)
13. 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, 2021 (accepted)
Matlab code here
14.
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)
15.
Xinjie Wang, Yaochu Jin and Kuangrong Hao. Computational
modeling of structural synaptic plasticity in echo state networks. IEEE Transactions on Cybernetics, 2021
(accepted)
16.
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, 2021 (accepted)
17.
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, 2021 (accepted)
18.
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)
19.
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)
20.
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
21. 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)
22.
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)
23.
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)
24. 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)
25. 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)
26. Yaochu Jin, Handing Wang, Chaoli Sun. Data-driven evolutionary optimization. Springer, June 2021
27. 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
28. 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
29. 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
30.
Jia Liu and Yaochu
Jin. Multi-objective
search of robust neural architectures against multiple types of adversarial
attacks. Neurocomputing, 453:
73-84, 2021
31. 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
32.
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
33. 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
34. 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
35.
Xinjie Wang, Yaochu Jin, and Kuangrong Hao. Synergies
between synaptic and intrinsic plasticity in echo state networks. Neurocomputing, 432: 32-43, 2021
36.
Hangyu Zhu, Haoyu Zhang, and Yaochu Jin. From
federated learning to federated neural architecture search: A survey. Complex & Intelligent Systems,
7:639–657, 2021
37.
Pengfei Huang, Handing Wang, and Yaochu Jin. Offline
data-driven evolutionary optimization based on tri-training. Swarm and Evolutionary Computation,
60:100800, 2021
38.
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
39.
Qian Zhang, Jie Lu, and Yaochu Jin. Artificial
intelligence in recommender systems. Complex
& Intelligent Systems, 7:439–457, 2021
40. Sampo Kuutti,
41. 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
42. 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
43. Peng Liao, Chaoli Sun, Guochen Zhang and Yaochu Jin. Multi-surrogate
multi-tasking optimization of expensive problems. Knowledge-Based Systems, 551: 23-38, 2021
44.
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
45. 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
46. 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
47. 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
48.
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
49.
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
50. 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
51.
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
52. 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.
53. 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
54. 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
55. 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
56.
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
57. Yan Zhou, Yaochu Jin,
and Jinliang Ding. Surrogate-assisted
evolutionary search of spiking neural architectures in liquid state machines.
Neurocomputing, 406: 12-23, 2020
58. Yuanjun Huang, Yaochu
Jin, Kuangrong Hao. Decision-making
and multi-objectivization for cost sensitive robust optimization over time.
Knowledge-Based Systems, 199: 105857,
2020
59. Yang Chen, Yaochu Jin,
Xiaoyan Sun. Language
model based interactive estimation of distribution algorithm. Knowledge-Based Systems, 200: 105980, 2020
60. 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
61. 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
62. 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
63. 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
64. 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
65. 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
66. Dujuan Wang, Yunqiang Yin, and Yaochu Jin. Rescheduling
Under Disruptions in Manufacturing Systems. Springer, Singapore, 2020
67. Hangyu Zhu and Yaochu
Jin. Multi-objective
evolutionary federated learning. IEEE
Transactions on Neural Networks and Learning Systems, 31(4): 1310-1322,
2020
68. 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
69. 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
70. 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
71.
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
72. 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
73.
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
74.
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
75.
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
76. 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
77. 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)
78. 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
79. 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
80. 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
81. 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
82.
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
83.
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
84.
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
85. 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
86. 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
87. 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
88.
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.
89. 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
90. 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
91.
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
92. 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
93.
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
94.
Xinjie Wang, Yaochu Jin, and Kuangrong Hao. Echo
state networks regulated by local intrinsic plasticity rules for regression.
Neurocomputing, 351: 111-122, 2019
95.
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
96.
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
97.
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
98.
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
99.
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.
100.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
101.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
102.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
103.Murillo. G. Carneiro, Ran Cheng, Liang Zhao, Yaochu Jin. Particle
swarm optimization for network-based data classification. Neural Networks, 110: 243-255, 2019
104.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
105.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
106.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
107.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
108.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
109.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
110.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
111.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
112.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
113.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
114.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
115.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
116.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
117.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
118.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
119.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
120.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
121.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
122.Ran
Cheng, Cheng He, Yaochu Jin, and Xin
Yao. Model-based
evolutionary algorithms – A short survey. Complex & Intelligent Systems, 4:283-292, 2018
123.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
124.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
125.Haibo
Yu, Ying Tan, Jianchao Zeng, Chaoli Sun and Yaochu Jin. Surrogate-assisted
hierarchical particle swarm optimization. Information Sciences, 454-455: 59-72, 2018
126.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
127.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
128.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
129.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.
130.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
131.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
132.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
133.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
134.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)
135.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.
136.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
137.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.
138.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.
139.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
140.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
141.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”)
142.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
143.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
144.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
145.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
146.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
147.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
148.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
149.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
150.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
151.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
152.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
153.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
154.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
155.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
156.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
157.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
158.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.
159.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.
160.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
161.Shenkai
Gu and Yaochu Jin. Multi-train:
A semi-supervised heterogeneous ensemble classifier. Neurocomputing,
249:202-211, 2017
162.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
163.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
164.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
165.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.
166.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
167.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
168.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
169.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
170.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
171.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.
172.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
173.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
174.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.
175.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
176.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.
177.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
178.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
179.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
180.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
181.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
182.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
183.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
184.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
185.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.
186.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
187.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
188.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
189.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
190.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
191.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
192.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.
193.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.
194.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.
195.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.
196.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
197.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
198.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.
199.Shenkai
Gu, Ran Cheng and Yaochu Jin. Multi-objective ensemble generation. WIREs Data Mining and
Knowledge Discovery, 5(5): 234-245, 2015
200.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.
201.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
202.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.
203.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.
204.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
205.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
206.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
207.Yanling
Jin, Yongsheng Ding, Kuangrong Hao and Yaochu Jin.
208.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.
209.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
210.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.
211.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".)
212.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
213.Joseph
Chrol-Cannon and Yaochu Jin. Computational modeling of neural plasticity for self-organization
of neural networks. BioSystems, 125:43-54, 2014 Also here
214.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
215.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
216.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
217.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
218.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
219.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
220.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.
221.Spencer
A. Thomas and Yaochu Jin. Reconstructing
gene regulatory networks: Where optimization meets big data. Evolutionary Intelligence,
7(1):29-47, 2014
222.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.
223.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
224.Ran
Cheng and Yaochu Jin. Demonstrator selection in a
social learning particle swarm optimizer. IEEE Congress on Evolutionary
Computation, July 2014, Beijing, China
225.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
226.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
227.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
228.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
229.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
230.Ran
Cheng and Yaochu Jin. On the competition mechanism of the competitive
particle swarm optimizer. UK Workshop on Computational Intelligence,
September 9-11, 2013
231.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
232.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
233.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)
234.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.
235.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.
236.Mingh
Nhgia Le, Yew Soon Ong, Stefan Menzel, Yaochu Jin, and Bernhard
Sendhoff. Evolution
by adapting surrogates. Evolutionary Computation,
21(2):313-340, 2013
237.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
238.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
239.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
240.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
241.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
242.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
243.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
244.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
245.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.
246.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
247.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
248.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
249.Daniel
Bush and Yaochu Jin. Calcium control
of hippocampal STDP. Journal of Computational Neuroscience.
33(3):495-514, 2012
250.Shenkai
Gu and Yaochu Jin. Heterogeneous classifier ensembles for EEG-based
motor imaginary detection. 2012 UK Workshop on Computational Intelligence.
Edinburgh, September 2012
251.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.
252.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
253.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
254.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
255.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
256.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
257.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
258.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".)
259.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.
260.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
261.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
262.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
263.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
264.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.
265.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
266.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
267.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
268.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.
269.Yan
Meng and Yaochu Jin (Editors). Bio-Inspired Self-Organization of Robotic Systems.
Springer, 2011
270.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
271.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
272.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)
273.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.
274.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.
275.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.
276.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
277.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
278.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
279.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
280.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
281.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
282.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
283.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
284.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
285.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
286.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
287.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
288.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
289.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
290.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
291.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
292.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)
293.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.
294.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”)
295.Till Steiner, Yaochu Jin, and Bernhard Sendhoff. Vector field embryogeny. PLoS ONE,
4(12): e8177. doi:10.1371/journal.pone.0008177, 2009
296.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)
297.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)
298.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)
299.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
300.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
301.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
302.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
303.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
304.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
305.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
306.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
307.Yaochu
Jin and Lipo Wang (editors), Fuzzy
Systems in Bioinformatics and Computational Biology.
Springer, 2009
308.Ingo Paenke, Yaochu Jin, Juergen Branke. Balancing
population and individual level of adaptation in changing environments. Adaptive Behavior,
17(2):153--174, 2009
309.Yaochu Jin, Robin Gruna, Bernhard Sendhoff. Pareto
analysis of evolutionary and learning systems. Frontiers of Computer Science
in China, 3(1):4-17, 2009
310.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
311.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
312.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
313.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
314.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
315.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
316.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
317.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
318.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
319.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.
320.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 )
321.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
322.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
323.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”)
324.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
325.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
326.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
327.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
328.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
329.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
330.Shengxiang
Yang, Yew-Soon Ong, and Yaochu Jin (editors) Evolutionary
Computation in Dynamic and Uncertain Environments ,
Springer, 2007
331.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
332.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
333.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.
334.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
335.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
336.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
337.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”)
338.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
339.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
340.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
341.Yaochu
Jin (editor). Multi-Objective
Machine Learning. Springer, Berlin Heidelberg. 2006
342.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
343.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.
344.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
345.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
346.Dudy
Lim, Yew-Soon Ong, Yaochu Jin, Bernhard Sendhoff. Trusted
evolutionary algorithms. IEEE Congress on Evolutionary Computation,
pp.456-463, July 2006, Vancouver
347.Lars
Gräning, Yaochu Jin, Bernhard Sendhoff. Generalization
improvement in multi-objective learning. International Joint
Conference on Neural Networks, pp.9893-9900, July 2006,
Vancouver
348.Yaochu
Jin, Bernhard Sendhoff. Alleviating
catastrophic forgetting via multi-objective learning. International Joint
Conference on Neural Networks, pp.6367-6374, July 2006,
Vancouver
349.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
350.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
351.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
352.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
353.Yaochu
Jin (editor). Knowledge Incorporation in Evolutionary Computation.
Springer, Berlin Heidelberg, 2005 Table of
Contents(PDF file)
354.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
355.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
356.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
357.Yaochu
Jin. A comprehensive survey of fitness
approximation in evolutionary computation. Soft Computing,
9(1), 3-12, 2005, Springer
Citations according to Google
Scholar
358.Michael
Huesken, Yaochu Jin and Bernhard Sendhoff.
Structure optimization of neural networks for evolutionary design optimization.
Soft
Computing, 9(1), 21-28, 2005
359.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
360.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
361.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
362.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
363.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
364.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
365.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
366.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
367.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
368.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)
369.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
370.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
371.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
372.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
373.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
374.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
375.Yaochu
Jin. Advanced Fuzzy Systems Design and Applications . Physica-Verlag/Springer-Verlag, Heidelberg, 2003 (ISBN:
3-7908-1537-3)Table of Contents (PDF file).
376.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
377.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
378.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
379.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
380.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
381.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
382.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
383.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
384.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)
385.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
386.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.
387.Yaochu
Jin. Brain controlled devices - An overview. Internal Report,
Honda Research Institute Europe, HRI-EU 03-13, September, 2003
388.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
389.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
390.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)
391.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
392.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.
393.Dissertation:
Knowledge in evolutionary and learning systems. Institute for Neuroinformatics,
Ruhr-University Bochum, Germany. Shaker Verlag, Aachen, 2002. (ISBN:
3-8265-9749-4)
394.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
395.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)
396.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
397.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
398.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
399.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.
400.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
401.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
402.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.
403.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.
404.Yaochu
Jin and Bernhard Sendhoff. Knowledge
incorporation into neural networks from fuzzy rules. Neural Processing Letters,
10(3), 231-242, 1999.
405.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
406.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
407.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.
408.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.
409.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.
410.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
411.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
412.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)
413.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)
414.Yaochu
Jin, Jingping Jiang. Two approaches to fuzzy optimal control. Proceedings of Chinese
Society of Electrical Engineering. 16(3):201-204, 1996 (in
Chinese)
415.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)
416.Yaochu
Jin. Intelligent modeling and control of complex systems. Ph.D.
thesis. Electrical Eng. Dept., Zhejiang University, Hangzhou, May 1996
417.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
418.Yaochu
Jin, Jing Zhu and Jingping Jiang. Adaptive fuzzy identification
with applications. International
Journal of Systems Science,6(2), 197-212, 1995.
419.Yaochu
Jin, Jing Zhu. Neural network based fuzzy modeling and its
simulation techniques. Journal of Systems Simulation,
7(2):46-55, 1995 (in Chinese)
420.Yaochu
Jin, Jingping Jiang. Neuro-fuzzy control of robot manipulators.
Chinese
Journal of Robot. 17(3):157-163, 1995 (in Chinese)
421.Yaochu
Jin, Jingping Jiang. A neural network model with applications. Journal of Zhejiang University,
29(3):340-347, 1995 (in Chinese)
422.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)
423.Yaochu
Jin, Jingping Jiang. Fuzzy logic integrated multivariable
adaptive neuro-control. Information and Control, 23(4):223-228, 1994 (in
Chinese)
424.Yaochu
Jin, Jing Zhu. Neural network based self-learning fuzzy
control. Chinese
Journal of Eletronics Technology, 4:35-40, 1994 (in Chinese)
425.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.
426.Yaochu
Jin, Xiaodong Shen. Two-level hierarchical intelligent fuzzy
control of servo systems. Journal of Zhejiang University,
28(6):644-654, 1994 (in Chinese)
427.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
428.Yaochu
Jin and Jingping Jiang. A novel paradigm of nonlinear system
control with applications. In :Proceedings IFAC Symposium on Robot Control,
Capri, Italy, 1994
429.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)
430.Yaochu
Jin, Jingping Jiang. Adaptive fuzzy prediction with application
to weather forecast. Pattern Recognition and Artificial Intelligence,
6(4):283-290, 1993 (in Chinese)
431.Yaochu
Jin, Jingping Jiang. Neural network based non-linear feedback
control. Journal
of Zhejiang University, 27, 1993 (in Chinese)
432.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
433.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)
434.Yaochu
Jin, Jingping Jiang. Artificial neural networks in robot control-
A survey. Robot,
14(6):54-58, 1992 (in Chinese)
435.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)
436.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)
437.Yaochu
Jin Dynamic control of robot manipulators. Master thesis.
Electrical Eng. Dept., Zhejiang University, Hangzhou, December 1990
Last update in June, 2021. Please pay attention to the copyrights. For
enquiries, contact Yaochu Jin.