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 31.05.2022:
Google
Scholar: h-index: 88, i10-index: 319, citations:
32,036.
Publon, h-index: 63, citations: 15,997. Scopus
Author Profile: h-index=67, citations = 18,838;
Research
Gate: RG Score: 47.76, h-index: 80, citations: 26,186.
DBLP Computer Science Bibliography.
PlatEMO, a Single-, Multi-
and Many-objective Optimization Tool
1. Xinjie Wang, Yaochu Jin, Wenli Du, and Jun Wang. Evolving dual-threshold Bienenstock-Cooper-Munro learning rules in Echo State Networks. IEEE Transactions on Neural Networks and Learning Systems, 2022 (accepted)
2. Tuo Zhang, Handing Wang, Bo Yuan, Yaochu Jin, and Xin Yao. Surrogate-assisted evolutionary Q-learning for black-box dynamic time-linkage optimization problems. IEEE Transactions on Evolutionary Computation, 2022 (accepted)
3. Yapei Wu, Xingguang
Peng, Handing Wang, Yaochu Jin, and Demin Xu. Cooperative coevolutionary
CMA-ES with landscape-aware grouping in
noisy environments. IEEE
Transactions on Evolutionary Computation, 2022 (accepted)
4. Zhihua Liu, Lei Tong, Long Chen, Zheheng Jiang, Feixiang Zhou, Qianni Zhang, Xiangrong Zhang, Yaochu Jin, and Huiyu Zhou. Deep
Learning Based Brain Tumor Segmentation: A Survey. Complex
& Intelligent Systems, 2022 (accepted)
5. Foivos Ntelemis, Yaochu Jin, and Spencer A.
Thomas. Information
maximization clustering via multi-view self-labelling. Knowledge-Based Systems, 2022
(accepted)
Code uploaded in GitHub
6. Ye Tian, Haowen
Chen, Haiping Ma, Xingyi
Zhang, Kay Chen Tan and Yaochu Jin. Integrating conjugate
gradients into evolutionary algorithms for large-scale continuous
multi-objective optimization. IEEE/CAA Journal of Automatica
Sinica, 2022 (accepted)
7. Zhening Liu, Handing Wang and Yaochu Jin. Performance indicator
based adaptive model selection for offline data-driven multi-objective
evolutionary optimization. IEEE Transactions on
Cybernetics, 2022 (accepted)
8. Xiangyu Wang, Bingran Zhang, Jian Wang, Kai Zhang, and Yaochu
Jin. A
cluster-based competitive particle swarm optimizer with a sparse truncation
operator for multi-objective optimization. Swarm
and Evolutionary Computation, 2022 (accepted)
9. Ye Tian, Jingwen
Pan, Shangshang Yang, Xingyi
Zhang, Shuping He, and Yaochu Jin. Imperceptible and sparse adversarial attacks
via a dual-population based constrained evolutionary
algorithm. IEEE
Transactions on Artificial Intelligence, 2022 (accepted)
10. Hui
Bai, Ran Cheng, Danial Yazdani, Kay Chen Tan, and Yaochu Jin. Evolutionary large-scale
dynamic optimization using bi-level variable grouping. IEEE
Transactions on Cybernetics, 2022 (accepted)
11. Qiqi Liu, Ran Cheng, Yaochu Jin,
Martin Heiderich, and Tobias Rodemann.
Reference rector assisted adaptive
model management for surrogate-assisted many-objective optimization. IEEE Transactions on Systems,
Man, and Cybernetics – Systems, 2022 (accepted)
12. Patrick Brosnan,
Guohong Tian, Hongguang
Zhang, Zhong Wu, and Yaochu Jin. Non-linear and multi-domain modelling
of a permanent magnet linear synchronous machine for free piston engine
generators. Energy Conversion and Management: X, 100195, 2022
(accepted)
13. Guo Yu, Lianbo
Ma, Yaochu Jin, Wenli Du, Qiqi Liu, and Hengmin Zhang. A survey on knee-oriented
multi-objective evolutionary optimization. IEEE Transactions on
Evolutionary Computation, 2022 (accepted)
14. Ye Tian, Yuandong
Feng, Chao Wang, Ruifen Cao, Xingyi
Zhang, Xi Pei, Kay Chen Tan, and Yaochu Jin. A large-scale combinatorial
many-objective evolutionary algorithm for intensity-modulated radiotherapy
planning. IEEE
Transactions on Evolutionary Computation, 2022 (accepted)
15. Ye Tian, Xiaopeng
Li, Haiping Ma, Xingyi
Zhang, Kay Chen Tan, and Yaochu Jin. Deep reinforcement learning
based adaptive operator selection for evolutionary multi-objective optimization. IEEE Transactions on Emerging
Topics in Computational Intelligence, 2022 (accepted)
16. Qiqi Liu, Yaochu Jin, Martin Martin Heiderich, and Tobias Rodemann. Surrogate-assisted
evolutionary optimization of expensive many-objective irregular problems. Knowledge-Based Systems, 2022
(accepted)
17.
Haoyu Zhang,
Yaochu Jin, and Kuangrong Hao. Evolutionary search for
complete neural network architectures with partial weight sharing. IEEE
Transactions on Evolutionary Computation, 2022 (accepted)
18.
Hangyu Zhu, Rui Wang, Yaochu Jin, and Kaitai Liang. PIVODL: Privacy-preserving
vertical federated learning over distributed labels. IEEE Transactions
on Artificial Intelligence, 2021 (accepted)
19.
Guo Yu,
Yaochu Jin, Markus Olhofer, Qiqi Liu, and Wenli
Du. Solution set
augmentation for knee identification in multiobjective
decision analysis. IEEE Transactions on Cybernetics, 2021 (accepted)
20.
Xilu Wang, Yaochu Jin, Sebastian Schmitt, and
Markus Olhofer. Transfer
learning based co-surrogate assisted evolutionary
bi-objective optimization for objectives with non-uniform evaluation times.
Evolutionary Computation, 2021 (accepted)
21.
Xiangyu Wang, Kai
Zhang, Jian Wang, and Yaochu Jin. An Enhanced competitive
swarm optimizer with strongly convex sparse operator for large-scale
multi-objective optimization. IEEE Transactions on
Evolutionary Computation, 2021 (accepted)
22. Yan Xiao, Yaochu Jin, and Kuangrong Hao. Adaptive prototypical
networks with label words and joint representation learning for few-shot
relation classification. IEEE
Transactions on Neural Networks and Learning Systems, 2021 (accepted)
23.
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)
24.
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)
25.
Tonghao Wang, Xingguang Peng, Yaochu
Jin and Demin Xu. Experience
sharing based memetic transfer learning for multiagent reinforcement learning.
Memetic Computing, 2021 (accepted)
26.
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)
27.
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)
28. Xinjie Wang, Yaochu Jin and Kuangrong
Hao. Computational modeling
of structural synaptic plasticity in echo state networks.
IEEE Transactions on Cybernetics,
2021 (accepted)
29.
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)
30.
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)
31.
Xiaoshu Xiang, Ye Tian, Xingyi
Zhang, Jianhua Xiao and Yaochu Jin. A pairwise proximity learning-based
ant colony algorithm for dynamic vehicle routing problems. IEEE Transactions on Intelligent
Transportation Systems, 23(6): 5275 – 5286, 2022
32. Jianchang Liu, Yuanchao
Liu, Yaochu Jin, and Fei Li. A decision
variable assortment based evolutionary algorithm for dominance robust
multi-objective optimization. IEEE Transactions on Systems, Man
and Cybernetics: Systems, 52(5): 3360 – 3375, 2022
33. Hangyu
Zhu and Yaochu Jin. Real-time
federated evolutionary neural architecture search. IEEE Transactions on Evolutionary Computation, 26(2): 364-378, 2022
34.
Qing
Chen, Yaochu Jin and Yongduan Song. Fault-tolerant
adaptive tracking control of Euler-Lagrange systems — An echo state network
approach driven by reinforcement learning. Neurocomputing,
481:109-116, 2022
35.
Yan
Xiao, Yaochu Jin, Ran Cheng, and Kuangrong
Hao. Hybrid
attention-based transformer block model for distant supervision relation
extraction. Neurocomputing, 470: 29-39, 2022
36. Jinjin Xu, Wenli
Du, Yaochu Jin, Wangli
He, and Ran Cheng. Ternary
compression for communication-efficient federated learning. IEEE Transactions on Neural Networks and
Learning Systems, 33(3): 1162-1176, 2022
37.
Dan Guo, Xilu Wang, Kailai Gao, Yaochu
Jin, Jinliang Ding, and Tianyou Chai. Evolutionary optimization
of high-dimensional multi- and many-objective expensive problems assisted by a
dropout neural network. IEEE
Transactions on Systems, Man and Cybernetics: Systems, 52(4): 2084-2097,
2022
Matlab
code on GitHub
38. Yuanchao Liu, Jianchang Liu, and Yaochu
Jin. Surrogate-assisted
multi-population particle swarm optimizer for high-dimensional expensive
optimization. IEEE Transactions on Systems, Man and Cybernetics: Systems, 52(4): 2084-2097, 2022
39.
Yajun Ru, Xihe Qiu, Xiaoyu Tan, Bin Chen, Yongbin Gao, and Yaochu Jin. Sparse-attentive
meta temporal point process for clinical decision support, Neurocomputing,
485: 114-123, 2022
40.
Dong Han, Wenli Du, Yaochu Jin, Wei Du, and Guo
Yu. A
fuzzy constraint handling technique for decomposition-based constrained multi-
and many-objective optimization. Information Science, 597:318-340,
2022
41.
Wei Du, Wenjiang Song, Yang Tang, Yaochu Jin, and Feng Qian. Searching for robustness
intervals in evolutionary robust optimization. IEEE Transactions on Evolutionary Computation, 26(1): 58-72, 2022
42.
Ye Tian, Langchun Si, Xingyi Zhang, Ran Cheng, Cheng He, Kay Chen Tan, and Yaochu Jin. Evolutionary large-scale multi-objective
optimization: A survey. ACM Computing
Surveys, 54(8): 174,
2022
43.
Xiaojun Zhou, Jianpeng Long,
Yaochu Jin, Guo Yu, Chunhua Yang. A
fast constrained state transition algorithm. Neurocomputing, 470:29-39, 2022
44.
Xihe Qiu, Xiaoyu Tan, Qiong Li, Shaotao Chen, Yajun Ru, and Yaochu
Jin. A
latent batch-constrained deep reinforcement learning approach for precision
dosing clinical decision support. Knowledge-Based Systems, 237,
107689, 2022
45. Ye Tian, Chang Lu, Xingyi Zhang, and Yaochu Jin. Solving large-scale multiobjective optimization problems with sparse optimal solutions via unsupervised neural networks. IEEE Transactions on Cybernetics, 51(6): 3115 – 3128, 2021
46.
Ruochen Liu,
Jianxia Li, Yaochu Jin and Licheng
Jiao. A self-adaptive response strategy
for dynamic multi-objective evolutionary optimization based on objective space
decomposition. Evolutionary
Computation, 29 (4): 491–519, 2021
47. Jinjin Xu, Yaochu Jin, and Wenli Du. A
federated data-driven evolutionary algorithm for expensive multi/many-objective
optimization. Complex &
Intelligent Systems, 7:3093–3109, 2021
48. Ataollah Ramezan Shirazi and Yaochu Jin. Regulated morphogen gradients for target surrounding and adaptive shape formation. IEEE Transactions on Cognitive and Developmental Systems, 13(4): 818-826, 2021
49.
Xilu Wang, Yaochu
Jin, Sebastian Schmitt, Markus Olhofer, and Richard Allmendinger. Transfer
learning based surrogate assisted evolutionary
bi-objective optimization for objectives with different evaluation times. Knowledge-Based Systems, 227, 107190,
2021
50.
Zhenshou
Song, Handing Wang, Cheng He, and Yaochu
Jin. A
Kriging-assisted two-archive evolutionary algorithm for expensive
many-objective optimization. IEEE Transactions
on Evolutionary Computation, 25(6):1013-1027, 2021
51.
Sutong Wang, Yunqiang Yin, Dujuan Wang, Zehui Lv,
Yanzhang Wang, and Yaochu Jin. An
interpretable deep neural network for colorectal polyp diagnosis under
colonoscopy. Knowledge-Based Systems, 234:107568, 2021
52.
Hangyu Zhu, Jinjin Xu,
Shiqing Liu and Yaochu Jin. Federated
learning on non-iid data: A survey. Neurocomputing, 465: 371-390, 2021
53.
Jinjin Xu, Yaochu Jin, Wenli Du, and Sai Gu. A
federated data-driven evolutionary algorithm. Knowledge-Based Systems,
233:107532, December 2021
54. Hangyu Zhu, Rui Wang, Yaochu Jin,
Kaitai Liang, and Jianting
Ning. Distributed
additive encryption and quantization for privacy preserving federated deep
learning. Neurocomputing, 463: 309-327, 2021
55. Shufen Qin, Chaoli Sun, Yaochu
Jin, Ying Tan and Jonathan Fieldsend. Large-scale
evolutionary multi-objective optimization assisted by directed sampling. IEEE Transactions on Evolutionary
Computation, 25(4): 724 – 738, 2021
Matlab code
here
56.
Danial Yazdani, Ran Cheng, Donya
Yazdani, Juergen Branke, Yaochu Jin,
and Xin Yao. A survey of
evolutionary continuous dynamic optimization over two decades – Part A. IEEE Transactions on Evolutionary
Computation, 25(4): 609
– 629, 2021
57.
Danial Yazdani, Ran Cheng, Donya
Yazdani, Juergen Branke, Yaochu Jin,
and Xin Yao. A survey of
evolutionary continuous dynamic optimization over two decades – Part B. IEEE Transactions on Evolutionary
Computation, 25(4): 630 – 650,
2021
58.
Yaochu Jin, Handing Wang, Chaoli Sun. Data-driven evolutionary
optimization. Springer, June 2021
59.
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
60.
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
61.
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
62.
Jia
Liu and Yaochu Jin. Multi-objective
search of robust neural architectures against multiple types of adversarial
attacks. Neurocomputing, 453:
73-84, 2021
63. 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
64.
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
65.
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
66.
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
67.
Xinjie Wang, Yaochu
Jin, and Kuangrong Hao. Synergies
between synaptic and intrinsic plasticity in echo state networks. Neurocomputing, 432: 32-43, 2021
68.
Hangyu
Zhu, Haoyu Zhang, and Yaochu Jin. From
federated learning to federated neural architecture search: A survey. Complex & Intelligent Systems,
7:639–657, 2021
69.
Pengfei Huang, Handing Wang, and Yaochu Jin. Offline
data-driven evolutionary optimization based on tri-training. Swarm and Evolutionary Computation,
60:100800, 2021
70.
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
71.
Qian
Zhang, Jie Lu, and Yaochu Jin. Artificial
intelligence in recommender systems. Complex
& Intelligent Systems, 7:439–457, 2021
72. Sampo Kuutti,
73. 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
74. 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
75. Peng Liao,
Chaoli Sun, Guochen Zhang and Yaochu Jin. Multi-surrogate
multi-tasking optimization of expensive problems. Knowledge-Based Systems, 551: 23-38, 2021
76. 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
77. 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
78. 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
79. 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
80. 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
81. 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
82. 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
83. 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
84. 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.
85. 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
86. 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
87. 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
88. 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
89. Yan Zhou, Yaochu Jin, and Jinliang
Ding. Surrogate-assisted
evolutionary search of spiking neural architectures in liquid state machines.
Neurocomputing, 406: 12-23, 2020
90. Yuanjun Huang, Yaochu
Jin, Kuangrong Hao. Decision-making
and multi-objectivization for cost sensitive robust optimization over time.
Knowledge-Based Systems, 199: 105857,
2020
91. Yang Chen, Yaochu Jin, Xiaoyan
Sun. Language
model based interactive estimation of distribution algorithm. Knowledge-Based Systems, 200: 105980, 2020
92. 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
93. 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
94. 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
95. 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
96. 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
97. 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
98. Dujuan Wang, Yunqiang Yin,
and Yaochu Jin. Rescheduling Under
Disruptions in Manufacturing Systems. Springer, Singapore, 2020
99. Hangyu Zhu
and Yaochu Jin. Multi-objective
evolutionary federated learning. IEEE
Transactions on Neural Networks and Learning Systems, 31(4): 1310-1322,
2020
100.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
101.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
102.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
103.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
104.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
105.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
106.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
107.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
108.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
109.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)
110.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
111.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
112.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
113.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
114.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
115.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
116.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
117.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
118.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
119.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
120.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.
121.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
122.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
123.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
124.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
125.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
126.Xinjie Wang, Yaochu
Jin, and Kuangrong Hao. Echo
state networks regulated by local intrinsic plasticity rules for regression.
Neurocomputing, 351: 111-122, 2019
127.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
128.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
129.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
130.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
131.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.
132.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
133.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
134.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
135.Murillo.
G. Carneiro, Ran Cheng, Liang Zhao, Yaochu
Jin. Particle
swarm optimization for network-based data classification. Neural Networks, 110: 243-255, 2019
136.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
137.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
138.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
139.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
140.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
141.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
142.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
143.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
144.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
145.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
146.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
147.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
148.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
149.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
150.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
151.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
152.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
153.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
154.Ran Cheng, Cheng He, Yaochu Jin, and Xin Yao. Model-based
evolutionary algorithms – A short survey. Complex & Intelligent Systems, 4:283-292, 2018
155.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
156.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
157.Haibo Yu, Ying Tan, Jianchao
Zeng, Chaoli Sun and Yaochu Jin. Surrogate-assisted
hierarchical particle swarm optimization. Information Sciences, 454-455: 59-72, 2018
158.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
159.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
160.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
161.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.
162.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
163.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
164.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
165.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
166.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)
167.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.
168.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
169.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.
170.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.
171.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
172.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
173.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”)
174.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
175.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
176.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
177.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
178.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
179.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
180.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
181.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
182.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
183.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
184.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
185.Jie Tian, Chaoli Sun, Haibo Yu, Ying Tan, Jianchao Zeng and Yaochu Jin. Comparisons of different kernels in Kriging-assisted
evolutionary expensive optimization. IEEE Symposium
Series on Computational Intelligence, November 27-December 1, 2017, Hawaii,
USA
186.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
187.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
188.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
189.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
190.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.
191.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.
192.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
193.Shenkai Gu and Yaochu Jin. Multi-train:
A semi-supervised heterogeneous ensemble classifier. Neurocomputing,
249:202-211, 2017
194.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
195.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
196.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
197.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.
198.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
199.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
200.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
201.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
202.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
203.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.
204.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
205.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
206.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.
207.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
208.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.
209.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
210.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
211.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
212.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
213.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
214.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
215.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
216.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
217.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.
218.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
219.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
220.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
221.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
222.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
223.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
224.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.
225.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.
226.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.
227.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.
228.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
229.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
230.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.
231.Shenkai Gu, Ran Cheng and Yaochu Jin. Multi-objective ensemble generation. WIREs Data Mining and Knowledge Discovery, 5(5): 234-245, 2015
232.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.
233.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
234.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.
235.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.
236.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
237.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
238.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
239.Yanling Jin, Yongsheng Ding, Kuangrong Hao and Yaochu Jin.
240.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.
241.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
242.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.
243.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".)
244.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
245.Joseph Chrol-Cannon and Yaochu
Jin. Computational modeling of neural plasticity for self-organization
of neural networks. BioSystems, 125:43-54, 2014 Also here
246.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
247.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
248.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
249.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
250.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
251.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
252.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.
253.Spencer A. Thomas and Yaochu Jin. Reconstructing gene regulatory networks: Where
optimization meets big data. Evolutionary
Intelligence,
7(1):29-47, 2014
254.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.
255.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
256.Ran Cheng and Yaochu Jin. Demonstrator selection in a
social learning particle swarm optimizer. IEEE Congress on Evolutionary Computation, July 2014, Beijing, China
257.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
258.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
259.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
260.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
261.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
262.Ran Cheng and Yaochu Jin. On the competition
mechanism of the competitive particle swarm optimizer. UK Workshop on Computational Intelligence, September 9-11, 2013
263.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
264.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
265.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)
266.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.
267.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.
268.Mingh Nhgia Le, Yew Soon Ong,
Stefan Menzel, Yaochu Jin, and Bernhard Sendhoff.
Evolution
by adapting surrogates. Evolutionary
Computation,
21(2):313-340, 2013
269.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
270.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
271.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
272.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
273.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
274.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
275.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
276.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
277.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.
278.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
279.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
280.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
281.Daniel Bush and Yaochu Jin. Calcium control
of hippocampal STDP. Journal of Computational
Neuroscience.
33(3):495-514, 2012
282.Shenkai Gu and Yaochu Jin. Heterogeneous classifier
ensembles for EEG-based motor imaginary detection. 2012 UK Workshop on Computational Intelligence. Edinburgh, September 2012
283.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.
284.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
285.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
286.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
287.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
288.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
289.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
290.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".)
291.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.
292.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
293.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
294.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
295.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
296.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.
297.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
298.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
299.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
300.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.
301.Yan Meng and Yaochu Jin (Editors). Bio-Inspired Self-Organization of Robotic Systems. Springer, 2011
302.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
303.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
304.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)
305.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.
306.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.
307.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.
308.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
309.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
310.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
311.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
312.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
313.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
314.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
315.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
316.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
317.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
318.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
319.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
320.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
321.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
322.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
323.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
324.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)
325.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.
326.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”)
327.Till Steiner, Yaochu Jin, and Bernhard Sendhoff. Vector field embryogeny. PLoS ONE, 4(12): e8177. doi:10.1371/journal.pone.0008177,
2009
328.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)
329.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)
330.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)
331.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
332.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
333.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
334.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
335.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
336.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
337.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
338.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
339.Yaochu Jin and Lipo Wang (editors), Fuzzy Systems in Bioinformatics and Computational Biology. Springer, 2009
340.Ingo Paenke, Yaochu Jin, Juergen Branke. Balancing
population and individual level of adaptation in changing environments. Adaptive Behavior,
17(2):153--174, 2009
341.Yaochu Jin, Robin Gruna, Bernhard Sendhoff. Pareto
analysis of evolutionary and learning systems. Frontiers of Computer Science in China, 3(1):4-17, 2009
342.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
343.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
344.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
345.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
346.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
347.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
348.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
349.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
350.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
351.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.
352.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 )
353.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
354.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
355.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”)
356.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
357.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
358.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
359.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
360.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
361.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
362.Shengxiang Yang, Yew-Soon Ong, and Yaochu Jin
(editors) Evolutionary
Computation in Dynamic and Uncertain Environments , Springer, 2007
363.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
364.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
365.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.
366.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
367.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
368.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
369.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”)
370.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
371.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
372.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
373.Yaochu Jin (editor). Multi-Objective
Machine Learning. Springer, Berlin Heidelberg. 2006
374.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
375.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.
376.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
377.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
378.Dudy Lim, Yew-Soon Ong, Yaochu Jin, Bernhard Sendhoff. Trusted evolutionary
algorithms. IEEE Congress on Evolutionary
Computation,
pp.456-463, July 2006, Vancouver
379.Lars Gräning, Yaochu Jin,
Bernhard Sendhoff. Generalization
improvement in multi-objective learning. International Joint Conference on Neural Networks, pp.9893-9900, July 2006, Vancouver
380.Yaochu Jin, Bernhard Sendhoff. Alleviating
catastrophic forgetting via multi-objective learning. International Joint Conference on Neural Networks, pp.6367-6374, July 2006, Vancouver
381.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
382.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
383.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
384.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
385.Yaochu Jin (editor). Knowledge Incorporation in Evolutionary Computation.
Springer, Berlin Heidelberg, 2005 Table of Contents(PDF file)
386.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
387.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
388.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
389.Yaochu Jin. A comprehensive survey of fitness approximation
in evolutionary computation. Soft
Computing, 9(1),
3-12, 2005, Springer
Citations
according to Google
Scholar
390.Michael Huesken, Yaochu
Jin and Bernhard Sendhoff.
Structure optimization of neural networks for evolutionary design optimization.
Soft Computing, 9(1), 21-28, 2005
391.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
392.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
393.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
394.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
395.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
396.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
397.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
398.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
399.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
400.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)
401.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
402.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
403.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
404.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
405.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
406.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
407.Yaochu Jin. Advanced Fuzzy Systems Design and Applications . Physica-Verlag/Springer-Verlag, Heidelberg, 2003 (ISBN: 3-7908-1537-3)Table of Contents (PDF file).
408.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
409.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
410.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
411.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
412.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
413.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
414.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
415.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
416.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)
417.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
418.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.
419.Yaochu Jin. Brain controlled devices - An overview. Internal Report, Honda
Research Institute Europe, HRI-EU 03-13, September,
2003
420.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
421.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
422.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)
423.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
424.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.
425.Dissertation: Knowledge in evolutionary and learning systems. Institute for Neuroinformatics, Ruhr-University Bochum, Germany. Shaker
Verlag, Aachen, 2002. (ISBN: 3-8265-9749-4)
426.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
427.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)
428.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
429.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
430.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
431.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.
432.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
433.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
434.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.
435.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.
436.Yaochu Jin and Bernhard Sendhoff. Knowledge
incorporation into neural networks from fuzzy rules. Neural Processing Letters, 10(3), 231-242, 1999.
437.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
438.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
439.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.
440.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.
441.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.
442.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
443.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
444.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)
445.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)
446.Yaochu Jin, Jingping Jiang. Two approaches to fuzzy
optimal control. Proceedings of Chinese Society of
Electrical Engineering.
16(3):201-204, 1996 (in Chinese)
447.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)
448.Yaochu Jin. Intelligent modeling and control of complex systems. Ph.D. thesis.
Electrical Eng. Dept., Zhejiang University, Hangzhou, May 1996
449.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
450.Yaochu Jin, Jing Zhu and Jingping Jiang. Adaptive fuzzy
identification with applications. International
Journal of Systems Science,6(2), 197-212, 1995.
451.Yaochu Jin, Jing Zhu. Neural network based fuzzy modeling and its simulation
techniques. Journal of Systems Simulation, 7(2):46-55, 1995 (in Chinese)
452.Yaochu Jin, Jingping Jiang. Neuro-fuzzy control of robot
manipulators. Chinese Journal of Robot. 17(3):157-163, 1995 (in Chinese)
453.Yaochu Jin, Jingping Jiang. A neural network model with
applications. Journal of Zhejiang University, 29(3):340-347, 1995 (in Chinese)
454.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)
455.Yaochu Jin, Jingping Jiang. Fuzzy logic integrated
multivariable adaptive neuro-control. Information
and Control,
23(4):223-228, 1994 (in Chinese)
456.Yaochu Jin, Jing Zhu. Neural network based self-learning fuzzy control. Chinese Journal of Eletronics Technology, 4:35-40, 1994 (in Chinese)
457.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.
458.Yaochu Jin, Xiaodong Shen. Two-level hierarchical
intelligent fuzzy control of servo systems. Journal
of Zhejiang University,
28(6):644-654, 1994 (in Chinese)
459.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
460.Yaochu Jin and Jingping Jiang. A novel paradigm of
nonlinear system control with applications. In :Proceedings IFAC Symposium on Robot Control, Capri, Italy, 1994
461.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)
462.Yaochu Jin, Jingping Jiang. Adaptive fuzzy prediction
with application to weather forecast. Pattern
Recognition and Artificial Intelligence, 6(4):283-290, 1993 (in Chinese)
463.Yaochu Jin, Jingping Jiang. Neural network based
non-linear feedback control. Journal
of Zhejiang University, 27,
1993 (in Chinese)
464.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
465.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)
466.Yaochu Jin, Jingping Jiang. Artificial neural networks
in robot control- A survey. Robot, 14(6):54-58, 1992 (in Chinese)
467.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)
468.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)
469.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.