Organizers:Hussein A. Abbass and Kay Chen Tan
About:Big Optimization (BigOpt) is the term we coin to differentiate optimization problems that rely on big data from classical large scale optimization. BigOpt problems involve thousands of variables and are normally expected to hide trends.
This special session is organized in conjunction with the BigOpt competition (see HERE). However, authors who do not contribute to the competition but have papers related to the optimization of big data problems are also encouraged to submit to the special session.
ScopeIn this special session, several aspects of Evolutionary Algorithm design can be considered, but not limited to the following:
- Evolutionary and other Nature Inspired Algorithms Design for Big Optimization
- Dimensionality reduction of big search spaces
- Novel operator design for optimization problems with thousands of variables
- Single Objective Big Optimization
- Multi Objective Big Optimization
- Parallel Evolutionary and other Nature Inspired Algorithms for Big Optimizatio
Paper SubmissionSpecial session papers are considered in the same way as regular papers. Please submit via the CEC 2015 submission website. When submitting the paper, please select the "Big Optimization Special Session 2015 (BigOpt2015)" from the "Main Research Topic" list.
Biography of the Main Team MembersProf. Hussein A. Abbass
School of Engineering and Information Technology, University of New South Wales
Hussein Abbass is a full Professor with the University of New South Wales (UNSW-Australia), Canberra Campus, Australia. In 2014, he is spending his sabbatical visiting the Department of Electrical and Computer Engineering, National University of Singapore. Prof. Abbass is a fellow of the UK Operational Research Society and a fellow of the Australian Computer Society. He is an Associate Editor of six international journals, including the IEEE Transactions on Evolutionary Computation, and the IEEE Computational Intelligence Magazine. He has been serving as the Chair of the Emerging Technologies Technical Committee of the IEEE Computational Intelligence Society (IEEE-CIS) for 2 years and has served on many different committees within IEEE-CIS. Prof. Abbass is currently a College Member of the Australian Research Council (ARC) Engineering, Mathematics, and Information Cluster. He was a member of the Research Evaluation Committee of Excellence of Research Australia in 2010. He spent his sabbatical in 2005 at the University of Illinois – Urbana Champaign spending, and was a UNSW John-Yu Fellow at Imperial College London in 2003. He published 200+ refereed papers. His current research interest is in computational red teaming and integrating human brain data with advanced analytics and automation.
Prof. Kay Chen Tan
Department of Electrical and Computer Engineering, National University of Singapore
Kay Chen Tan is currently an Associate Professor in the Department of Electrical and Computer Engineering, National University of Singapore. He has published over 100 journal papers, over 100 papers in conference proceedings, co-authored 5 books. Dr Tan has been an Invited Keynote/Plenary speaker for over 40 international conferences. He is the General Co-Chair for the 2016 IEEE World Congress on Computational Intelligence to be held in Vancouver, Canada. Dr Tan is an elected member of AdCom (2014-2016) and was an IEEE Distinguished Lecturer of IEEE Computational Intelligence Society from 2011-2013. Dr Tan is the Editor-in-Chief of IEEE Transactions on Evolutionary Computation beginning in 2015. He was the Editor-in-Chief of IEEE Computational Intelligence Magazine from 2010-2013. He currently serves as an Associate Editor / Editorial Board member of over 20 international journals, such as IEEE Transactions on Cybernetics, IEEE Transactions on Computational Intelligence and AI in Games, Evolutionary Computation (MIT Press) etc. Dr Tan is a Fellow of IEEE. He is the awardee of the 2012 IEEE Computational Intelligence Society (CIS) Outstanding Early Career Award and the recipient of the Recognition Award (2008) from the International Network for Engineering Education & Research (iNEER).