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 02/2019: Google
Scholar: h-index: 60, i10-index: 202, citations:
16008.
ISI Web of
Science (journal publications only), h-index: 32, number of
articles: 108, citations: 5173.
Scopus
Author Profile: h-index=43, citations = 8343;
Research
Gate: RG Score: 44.22, h-index: 53, citations: 11,968.
DBLP Computer Science Bibliography.
Computer Scientist National and World Ranking according to Guide2Research.
In Presss 2019 2018 2017 2016 2015 2014 2013 2012 2011 2010 2009 2008 2007 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 1990
1. 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, 2019
(accepted)
2.
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, 2019 (accepted)
3.
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, 2019 (accepted)
4.
Murillo. G. Carneiro, Ran Cheng,
Liang Zhao, Yaochu Jin. Particle
swarm optimization for network-based data classification. Neural Networks, 2018 (accepted)
5.
Ye Tian, Xinyi
Zhang, Ran Cheng, Cheng He, and Yaochu
Jin. Guiding
evolutionary multi-objective optimization with generic front modeling. IEEE Transactions on Cybernetics, 2018
(accepted)
6.
Lei Zhang, Hebin
Pan, Xingyi Zhang, Xiangxiang Zeng and Yaochu Jin. A network reduction based
multi-objective evolutionary algorithm for community detection in large-scale
complex networks. IEEE Transactions
on Cybernetics, 2018 (accepted)
7.
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, 2018 (accepted)
8.
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, 2018 (accepted)
9.
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, 2018 (accepted)
10.
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, 2018 (accepted)
11.
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, 2018 (accepted)
12.
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, 2018 (accepted).
13.
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, 2018 (accepted)
14.
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, 2018
(accepted)
15.
Xingguang Peng, Yaochu Jin, and
Handing Wang. Multi-modal
optimization enhanced cooperative coevolution for large-scale optimization.
IEEE Transactions on Cybernetics,
2018 (accepted)
16.
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, 2018
(accepted)
17.
Handing Wang, Yaochu Jin, Chaoli Sun and John Doherty. Offline data-driven
evolutionary optimization using selective surrogate ensembles. IEEE Transactions on Evolutionary
Computation, 2018 (accepted)
Matlab code in GitHub
18.
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, 2018 (accepted)
19. 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, 2018 (accepted)
20. Du-Juan Wang, Feng Liu and Yaochu Jin. A proactive scheduling approach to steel rolling process with
stochastic machine breakdown. Natural Computing. 2016 (accepted)
21. Xin Ye, Jia Li, Sihao Liu, Jiwei Liang and Yaochu
Jin. A hybrid instance-intensive workflow scheduling method in private
cloud environment. Natural Computing. 2016 (accepted)
22. Shufen Qin, Chaoli
Sun, Yaochu Jin, Lier
Lan and Ying Tan. A new
selection strategy for decomposition-based evolutionary many-objective
optimization. EEE Congress on
Evolutionary Computation, Wellington, New Zealand, June 2019
23. 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
24. 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
25. 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
26. 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
27. 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
28. 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
29. 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
30. Jingliang 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
31. 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
32.
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
33.
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
34. 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
35.
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
36. 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
37. 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
38. 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
39. 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
40. 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
41. Haibo Yu, Ying
Tan, Jianchao Zeng, Chaoli Sun and Yaochu Jin. Surrogate-assisted
hierarchical particle swarm optimization. Information Sciences, 454-455: 59-72, 2018
42. 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
43. 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
44. 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
45. 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.
46. 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
47. 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
48. 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
49. 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
50. 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
A draft here
Matlab code for testing LMEA on
LSMOP test suite.
MATLAB code for tree-based ENS (T-ENS)
51. 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.
52. 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
53. Shenkai Gu, Ran Cheng, Yaochu Jin. Feature selection for high dimensional classification using a
competitive swarm optimizer. Soft Computing, 22(3): 811-822, 2018
54. 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.
55. 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
56. 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
57. 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
58. 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
59. 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
60. 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
61. 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
62. 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
63. 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
64. 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
65. 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
66. 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
67. 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
68. 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
69. 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
70. 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
71. 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
72. 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
73. 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
74. 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
A draft here.
(This paper won the
"2017 CEC Best Student Paper Award".)
75. 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.
76. 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
77. Shenkai Gu and Yaochu Jin. Multi-train:
A semi-supervised heterogeneous ensemble classifier. Neurocomputing,
249:202-211, 2017
78. 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
79. 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
80. 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
81. 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.
82. 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
83. 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
84. 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, 14(1/2):5-25,
2017
85. 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
86. 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
87. 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.
88. 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
89. 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
90. 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.
91. 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
92. 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.
93. 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
94. 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
95. 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
96. 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
97. 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
98. 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
99. 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
100.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
101.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.
102.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
103.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
104.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
105.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
106.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
107.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
108.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.
109.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.
110.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.
111.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.
112.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
113.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
114.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.
115.Shenkai Gu, Ran Cheng and Yaochu Jin. Multi-objective ensemble generation. WIREs Data Mining and
Knowledge Discovery, 5(5): 234-245, 2015
116.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
See also here, Matlab
code ENS_SS, ENS_BS
and the NSGA-II with ENS.
(This paper won the 2017
"IEEE Transactions on Evolutionary Computation Outstanding Paper
Award".)
117.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
118.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.
119.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.
120.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
121.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
122.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
123.Yanling Jin, Yongsheng Ding, Kuangrong Hao and Yaochu Jin.
124.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.
125.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
126.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.
127.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
(This paper won the
"2016 IEEE Computational Intelligence Outstanding Paper Award".)
128.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
129.Joseph Chrol-Cannon
and Yaochu Jin. Computational modeling of neural plasticity for self-organization
of neural networks. BioSystems,
125:43-54, 2014 Also here
130.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
131.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
132.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
133.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
134.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
135.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
136.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.
137.Spencer A. Thomas
and Yaochu Jin. Reconstructing gene
regulatory networks: Where optimization meets big data. Evolutionary
Intelligence, 7(1):29-47, 2014
138.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.
139.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
140.Ran Cheng and Yaochu
Jin. Demonstrator
selection in a social learning particle swarm optimizer. IEEE Congress
on Evolutionary Computation, July 2014, Beijing, China
141.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
142.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
143.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 ( This paper won the "Runner-up for the 2014 CEC Best Student
Paper Award".) here
144.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
145.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
146.Ran Cheng and Yaochu
Jin. On the competition mechanism of the competitive particle swarm
optimizer. UK Workshop on Computational Intelligence, September 9-11,
2013
147.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
148.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
149.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)
150.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.
151.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.
152.Mingh Nhgia Le, Yew Soon Ong, Stefan Menzel, Yaochu Jin,
and Bernhard Sendhoff. Evolution
by adapting surrogates. Evolutionary Computation, 21(2):313-340,
2013
153.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
154.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
155.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
156.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
157.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
158.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
159.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
160.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
161.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.
162.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
163.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
164.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
165.Daniel Bush and Yaochu
Jin. Calcium
control of hippocampal STDP. Journal of Computational Neuroscience.
33(3):495-514, 2012
166.Shenkai Gu and Yaochu Jin. Heterogeneous classifier ensembles
for EEG-based motor imaginary detection. 2012 UK Workshop on Computational
Intelligence. Edinburgh, September 2012
167.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.
168.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
169.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
170.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
171.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
172.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
173.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
174.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 (This paper won the 2014 "IEEE Computational Intelligence
Magazine Outstanding Paper Award".)
175.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.
176.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
177.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
178.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
179.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
180.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.
181.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
182.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
183.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
184.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.
185.Yan Meng and Yaochu
Jin (Editors). Bio-Inspired Self-Organization of Robotic Systems.
Springer, 2011
186.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
187.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
188.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)
189.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.
190.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.
191.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.
192.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
193.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
194.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
195.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
196.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
197.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
198.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
199.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
200.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
201.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
202.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
203.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
204.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
205.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
206.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
207.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
208.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)
209.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.
210.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 ( Best Paper Award )
211.Till Steiner, Yaochu Jin, and Bernhard Sendhoff. Vector field embryogeny. PLoS
ONE, 4(12): e8177. doi:10.1371/journal.pone.0008177, 2009
212.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)
213.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)
214.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)
215.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
216.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
217.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
218.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
219.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
220.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
221.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
222.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 (Invited feature article) Also available here
223.Yaochu Jin and Lipo Wang
(editors), Fuzzy
Systems in Bioinformatics and Computational Biology. Springer, 2009
224.Ingo Paenke, Yaochu Jin, Juergen Branke. Balancing
population and individual level of adaptation in changing environments. Adaptive
Behavior, 17(2):153--174, 2009
225.Yaochu Jin, Robin Gruna, Bernhard Sendhoff. Pareto
analysis of evolutionary and learning systems. Frontiers of Computer
Science in China, 3(1):4-17, 2009
226.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
227.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
228.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
229.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
230.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
231.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
232.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
233.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
234.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
235.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.
236.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 )
237.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
238.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
239.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 ( Best paper nomination)
240.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
241.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
242.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
243.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
244.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
245.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
246.Shengxiang Yang,
Yew-Soon Ong, and Yaochu Jin (editors) Evolutionary
Computation in Dynamic and Uncertain Environments , Springer, 2007
247.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
248.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
249.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.
250.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
251.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
252.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
253.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)
254.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
255.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
256.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
257.Yaochu Jin (editor). Multi-Objective
Machine Learning. Springer, Berlin Heidelberg. 2006
258.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
259.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.
260.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
261.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
262.Dudy Lim, Yew-Soon
Ong, Yaochu Jin, Bernhard Sendhoff. Trusted evolutionary algorithms. IEEE Congress on
Evolutionary Computation, pp.456-463, July 2006, Vancouver
263.Lars Gräning, Yaochu Jin, Bernhard Sendhoff.
Generalization improvement in multi-objective learning.
International Joint Conference on Neural Networks, pp.9893-9900, July
2006, Vancouver
264.Yaochu Jin, Bernhard Sendhoff. Alleviating catastrophic
forgetting via multi-objective learning. International Joint Conference
on Neural Networks, pp.6367-6374, July 2006, Vancouver
265.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
266.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
267.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
268.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
269.Yaochu Jin (editor). Knowledge Incorporation in Evolutionary Computation.
Springer, Berlin Heidelberg, 2005 Table of
Contents(PDF file)
270.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
271.Hanli Wang, Sam Kwong, Yaochu Jin, Wei Wei and K. Man. Agent-based evolutionary approach to interpretable
rule-based knowledge extraction. IEEE Transactions Systems, Man, and
Cybernetics, Part C: Applications and Reviews, 35(2), 143-155, 2005
272.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
273.Yaochu Jin. A comprehensive survey of fitness approximation in
evolutionary computation. Soft Computing, 9(1), 3-12, 2005,
Springer
Citations according to Google
Scholar
274.Michael Huesken, Yaochu Jin and Bernhard Sendhoff. Structure optimization of neural networks for evolutionary
design optimization. Soft Computing, 9(1), 21-28, 2005
275.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
276.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
277.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
278.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
279.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
280.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
281.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
282.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
283.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
284.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)
285.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
286.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
287.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
288.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
289.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
290.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
291.Yaochu Jin. Advanced Fuzzy Systems Design and Applications . Physica-Verlag/Springer-Verlag, Heidelberg, 2003 (ISBN: 3-7908-1537-3)Table of Contents (PDF
file).
292.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
293.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
294.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
295.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
296.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
297.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
298.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
299.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
300.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)
301.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
302.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.
303.Yaochu Jin. Brain controlled
devices - An overview. Internal Report, Honda Research Institute Europe, HRI-EU
03-13, September, 2003
304.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
305.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
306.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)
307.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
308.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.
309.Dissertation: Knowledge in evolutionary and learning systems. Institute for Neuroinformatics, Ruhr-University Bochum, Germany. Shaker Verlag, Aachen, 2002. (ISBN: 3-8265-9749-4)
310.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
311.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)
312.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
313.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
314.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
315.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.
316.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
317.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
318.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.
319.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.
320.Yaochu Jin and Bernhard Sendhoff. Knowledge incorporation
into neural networks from fuzzy rules. Neural Processing Letters,
10(3), 231-242, 1999.
321.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
322.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
323.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.
324.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.
325.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.
326.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
327.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
328.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)
329.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)
330.Yaochu Jin, Jingping Jiang. Two approaches to fuzzy optimal control. Proceedings
of Chinese Society of Electrical Engineering. 16(3):201-204, 1996 (in
Chinese)
331.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)
332.Yaochu Jin. Intelligent
modeling and control of complex systems. Ph.D. thesis. Electrical Eng. Dept.,
Zhejiang University, Hangzhou, May 1996
333.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
334.Yaochu Jin, Jing Zhu and Jingping Jiang. Adaptive fuzzy identification with
applications. International Journal of Systems Science,6(2), 197-212, 1995.
335.Yaochu Jin, Jing Zhu. Neural
network based fuzzy modeling and its simulation techniques. Journal of
Systems Simulation, 7(2):46-55, 1995 (in Chinese)
336.Yaochu Jin, Jingping Jiang. Neuro-fuzzy
control of robot manipulators. Chinese Journal of Robot.
17(3):157-163, 1995 (in Chinese)
337.Yaochu Jin, Jingping Jiang. A neural network model with applications. Journal
of Zhejiang University, 29(3):340-347, 1995 (in Chinese)
338.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)
339.Yaochu Jin, Jingping Jiang. Fuzzy logic integrated multivariable
adaptive neuro-control. Information and Control,
23(4):223-228, 1994 (in Chinese)
340.Yaochu Jin, Jing Zhu. Neural
network based self-learning fuzzy control. Chinese Journal of Eletronics Technology, 4:35-40, 1994 (in Chinese)
341.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.
342.Yaochu Jin, Xiaodong Shen.
Two-level hierarchical intelligent fuzzy control of servo systems. Journal
of Zhejiang University, 28(6):644-654, 1994 (in Chinese)
343.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
344.Yaochu Jin and Jingping Jiang. A novel paradigm of nonlinear system
control with applications. In :Proceedings IFAC Symposium on Robot Control,
Capri, Italy, 1994
345.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)
346.Yaochu Jin, Jingping Jiang. Adaptive fuzzy prediction with application
to weather forecast. Pattern Recognition and Artificial Intelligence,
6(4):283-290, 1993 (in Chinese)
347.Yaochu Jin, Jingping Jiang. Neural network based non-linear feedback
control. Journal of Zhejiang University, 27, 1993 (in Chinese)
348.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
349.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)
350.Yaochu Jin, Jingping Jiang. Artificial neural networks in robot
control- A survey. Robot, 14(6):54-58, 1992 (in Chinese)
351.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)
352.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)
353.Yaochu Jin Dynamic control
of robot manipulators. Master thesis. Electrical Eng. Dept., Zhejiang
University, Hangzhou, December 1990
Last update in January, 2016. Please pay attention to the copyrights. For enquiries, contact Yaochu Jin.