Memetic Computing (MC) represents a broad generic framework using the notion of meme(s) as units of information encoded in computational representations for the purpose of problem-solving. In the literature, MC has been successfully manifested as memetic algorithm, where meme has been typically perceived as individual learning procedures, adaptive improvement procedures or local search operators that enhance the capability of population based search algorithms. More recently, novel manifestations of meme in the forms such as knowledge building-block, decision tree, artificial neural works, fuzzy system, graphs, etc., have also been proposed for efficient problem-solving. These meme-inspired algorithms, frameworks and paradigms have demonstrated with considerable success in various real-world application.
The aim of this special session on memetic computing is to provide a forum for researchers in this field to exchange the latest advances in theories, technologies, and practice of memetic computing.
Authors are invited to submit their original and unpublished work in the areas including, but not limited to:
Single/Multi-Objective memetic algorithms for continuous or combinatorial optimization,
Theoretical studies that enhance our understandings on the behaviors of memetic computing,
Adaptive systems and meme coordination,
Novel manifestations of memes for problem-solving,
Cognitive, Brain, individual learning, and social learning inspired memetic computation,
Self-design algorithms in memetic computing,
Memetic frameworks using surrogate or approximation methods,
Memetic automaton, cognitive and brain inspired agent based memetic computing,
Data mining and knowledge learning in memetic computation paradigm,
Memetic computing for expensive and complex real-world .
Papers for IEEE CEC 2017 should be submitted electronically through the Congress website at
and will be refereed by experts in the fields and ranked based on the criteria of originality, significance, quality and clarity.
To submit your papers to the special session, please select the Special Session name in the Main Research topic.
For more submission information please visit: http://www.cec2017.org
All accepted papers will be published in the IEEE CEC 2017 electronic proceedings, included in the IEEE Xplore digital library, and indexed by EI Compendex. High quality papers will be invited to extend and submit to the Memetic Computing Journal.
Chongqing University, China.
E-mail: liangf [@] cqu.edu.cn
Liang Feng received the PhD degree from the School of Computer Engineering, Nanyang Technological University, Singapore, in 2014. He was a Postdoctoral Research Fellow at the Computational Intelligence Graduate Lab, Nanyang Technological University, Singapore. He is currently an Assistant Professor at the College of Computer Science, Chongqing University, China. His research interests include Computational and Artificial Intelligence, Memetic Computing, Big Data Optimization and Learning, as well as Transfer Learning.
Teesside University, UK.
Yifeng Zeng is a Reader at School of Computing in Teesside University, United Kingdom. He received his PhD in 2006 from National University of Singapore. Before he moved to Teesside University, Dr. Zeng was an assistant professor and an associate professor during 2006 - 2012 in Aalborg University, Denmark. His current research interests include intelligent agents, computational intelligence, big data, and computer games. Most of his publications appear in the most prestigious international academic journals and conferences including JAIR, JAAMAS, AAMAS, IJCAI and AAAI. He successfully organized the International Workshop on Agents and Data Mining Interaction (ADMI 2012 - 2016) in conjunction with AAMAS.
Shenzhen University, China
E-Mail: : zhuzx[@]szu.edu.cn
Zexuan Zhu received the BS degree in computer science and technology from Fudan University, China, in 2003, and the PhD degree in computer engineering from Nanyang Technological University, Singapore, in 2008. He is currently a professor with the College of Computer Science and Software Engineering, Shenzhen University, China. His current research interests include evolutionary computation, machine learning, and bioinformatics. He is a Vice Chair of IEEE Emergent Technologies Task Force on Memetic Computing.
Ke Tang, University of Science and Technology of China, email@example.com
Ying-ping Chen, National Chiao Tung University, Taiwan, firstname.lastname@example.org
Kay Chen Tan, National University of Singapore, email@example.com
Hussein Abbas, University of New South Wales, Australia, firstname.lastname@example.org
Yaochu Jin, University of Surrey, UK, email@example.com
Hisao Ishibuchi, Osaka Prefecture University, Japan, firstname.lastname@example.org
Chuan-Kang Ting, National Chung Cheng University, Taiwan, email@example.com
Yew-Soon Ong, Nanyang Technological University, Singapore. firstname.lastname@example.org
Maoguo Gong, Xidian University, China. email@example.com
Wenyin Gong, China University of Geosciences, Wuhan, China, firstname.lastname@example.org
Meng-Hiot Lim, Nanyang Technological University, Singapore, EMHLIM@ntu.edu.sg
Chaoli Sun, University of Surrey, UK, email@example.com
Huajin Tang, Sichuan University, China, firstname.lastname@example.org
Bo Liu, Chinese Academy of Sciences, China, email@example.com
Ferrante Neri, De Montfort University, UK, firstname.lastname@example.org
Giovanni Iacca, INCAS3, The Netherlands, giovanniIacca@incas3.eu
Fabio Caraffini, De Montfort University, UK, email@example.com
Anna Kononova, Heriot-Watt University, UK, firstname.lastname@example.org
Mengjie Zhang, Victoria University of Wellington, New Zealand, Mengjie.Zhang@ecs.vuw.ac.nz
Abhishek Gupta, Nanyang Technological University, Singapore, email@example.com
Kamlsh Mistry, Teesside University, UK, K.Mistry@tees.ac.uk
Biju Issac, Teesside University, UK, B.Issac@tees.ac.uk
Jing Tang, Teesside University, UK, J.Tang@tees.ac.uk