Affiliation: National University of Singapore
Research Field: Computational Intelligence Applications
Affiliation: Michigan State University, USA
Research Field: Evolutionary Multi-Objective Optimization
Affiliation: Nanyang Technological University, Singapore
Research Field: Memetic Computing
Website: https://www.ntu.edu.sg/home/asysong/
Z. Wang, Y. S. Ong, and H. Ishibuchi, “On scalable multiobjective test problems with hardly-dominated boundaries,” IEEE Trans. on Evolutionary Computation, vol. 23, no. 2, pp. 217-231, April 2019.
Affiliation: City University of Hong Kong
Research Field: Evolutionary Multi-Objective Optimization
Website: http://www.cityu.edu.hk/stfprofile/qingfu.zhang.htm
Z. Wang, Q. Zhang, H. Li, H. Ishibuchi, and L. Jiao, “On the use of two reference points in decomposition based multiobjective evolutionary algorithms,” Swarm and Evolutionary Computation, vol. 34, pp. 89-102, June 2017.
Affiliation: University of Surrey, UK
Research Field: Evolutionary Multi-Objective Optimization
Website: https://www.surrey.ac.uk/cs/people/yaochu_jin/
Y. Jin, K. Miettinen, and H. Ishibuchi, “Guest editorial evolutionary many-objective optimization,” IEEE Trans. on Evolutionary Computation, vol. 22, no. 1, pp. 1-2, February 2018.
Affiliation: Victoria University of Wellington, New Zealand
Research Field: Evolutionary Machine Learning
Website: http://homepages.ecs.vuw.ac.nz/~mengjie/
B. H. Nguyen, B. Xue, P. Andreae, H. Ishibuchi, and M. Zhang, “Multiple reference points based decomposition for multi-objective feature selection in classification: Static and dynamic mechanisms,” IEEE Trans. on Evolutionary Computation (accepted: Early Access)
Affiliation: Otto von Guericke University of Magdeburg, Germany
Research Field: Evolutionary Multi-Objective Optimization
Website: https://www.is.ovgu.de/Team/Sanaz+Mostaghim.html
H. Zille, H. Ishibuchi, S. Mostaghim and Y. Nojima, “A framework for large-scale multi-objective optimization based on problem transformation,” IEEE Trans. on Evolutionary Computation, vol. 22, no. 2, pp. 260-275, April 2018.
Affiliation: Oklahoma State University, USA
Research Field: Evolutionary Multi-Objective Optimization
Website: http://isc.okstate.edu/
Y. Liu, H. Ishibuchi, G. G. Yen, Y. Nojima, and N. Masuyama, “Handling imbalance between convergence and diversity in the decision space in evolutionary multi- modal multi-objective optimization,” IEEE Trans. on Evolutionary Computation (accepted: Early Access).
Affiliation: University of Newcastle, Australia
Research Field: Evolutionary Game
Website: https://www.newcastle.edu.au/profile/raymond-chiong
M. Chica, R. Chiong, M. Kirley, and H. Ishibuchi, “A networked N-player trust game and its evolutionary dynamics,” IEEE Trans. on Evolutionary Computation, vol. 22, no. 6, pp. 866-878, December 2018.
Affiliation: University of Granada, Spain
Research Field: University of Granada, Spain
Website: https://decsai.ugr.es/~herrera/
M. Fazzolari, R. Alcalá, Y. Nojima, H. Ishibuchi, and F. Herrera, “A review of the application of multiobjective evolutionary fuzzy systems: Current status and further directions,” IEEE Trans. on Fuzzy Systems, vol. 21, no. 1, pp. 45-65, February 2013.
Affiliation: University of Nottingham, UK
Research Field: Hyper-Heuristics
Website: https://www.nottingham.ac.uk/computerscience/people/rong.qu
B. Chen, R. Qu, R. Bai, and H. Ishibuchi, “A variable neighbourhood search algorithm with compound neighbourhoods for VRPTW,” Proc. of 2016 International Conference on Operations Research and Enterprise Systems (ICORES'16), Rome, Italy, February 23-25, 2016.
Affiliation: Jiangnan University, China
Research Field: Fuzzy Deep Learning
Website: http://dm.jiangnan.edu.cn/info/1197/2989.htm
Y. Zhang, H. Ishibuchi and S. Wang, “Deep Takagi-Sugeno-Kang fuzzy classifier with shared linguistic fuzzy rules,” IEEE Trans. on Fuzzy Systems, vol. 26, no. 3, pp. 1535-1549, June 2018.
Affiliation: National University of Defense Technology
Research Field: Evolutionary Multi-Objective Optimization
R. Wang, Z. Zhou, H. Ishibuchi, T. Liao, and T. Zhang, “Localized weighted sum method for many-objective optimization,” IEEE Trans. on Evolutionary Computation, vol. 22, no. 1, pp. 3-18, February 2018.
Affiliation: Beijing Institute of Technology, China
Research Field: Evolutionary Computation
B. Xin, L. Chen, J. Chen, H. Ishibuchi, K. Hirota, and B. Liu, “Interactive multiobjective optimization: A review of the state-of-the-art,” IEEE Access, vol. 6, no. 1, pp. 41256-41279, December 2018.
Affiliation: The University of Electro-communications, Japan
Website: http://kjk.office.uec.ac.jp/Profiles/56/0005538/prof_e.html
H. Ishibuchi and H. Sato, “Evolutionary Many-Objective Optimization,” Tutorial Talk at IEEE CEC 2018 (Brazil), IEEE CEC 2019 (New Zealand), and GECCO 2019 (Czech Republic).
Affiliation: Osaka Prefecture University, Japan