Please note this website is no longer up to date. It is kept active here only for the purpose of providing better public access to IEEE CIS LSGO Task Force past activities. For the current IEEE CIS LSGO Task Force website (2016 onwards), please visit: http://midas.ctb.upm.es/misc/ieee-lsgo/.
Objectives
In many real-world applications, most existing EAs' performance deteriorates as the size of problem increases
(e.g. a single objective problem with large number of decision variables).
The reasons appear to be two-fold. First, complexity of the problem usually increases with the size of problem.
A previously successful search strategy may no longer be capable of finding the optimal solution.
Second, the solution space of the problem becomes larger and larger when the problem size increases,
which requires a more efficient search strategy to explore all the promising regions in this much larger solution space.
Hence, new evolutionary algorithms for large scale optimization problems are of high importance.
The objectives of this task force are:
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to promote the research and development of evolutionary computation techniques for large scale optimization problems.
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to facilitate the knowledge sharing and collaboration between researchers in the related areas.
There are many people, from Computer Science, Engineering, Math, Operation Research, etc., interested in large scale global optimization.
But they are scattered in different places and in different conferences.
One of the major aims of this TF is to provide a common forum for all these people to come together and exchange ideas.
ECTC is ideally positioned to attract all these people and provide a home to these distributed groupings in
different communities (from CS to Math and from OR to Engineering).
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to exchange experience and promote discussion and contacts between researchers, industrialists and practitioners.
The TF will actively recruit and engage industrialists and practitioners in its activities.
In particular, the TF will solicit "grand challenges" in large scale global optimization, especially from industrialists and practitioners.
Such "grand challenges" will then be put on the web to promote research into novel techniques for tackling such challenges.
The Large-Scale Global Optimization Repository at the University of Birmingham can be used for such purpose:
http://www.cercia.ac.uk/projects/lsgo/
Anticipated interests
Evolutionary computation for large scale optimization is an inter-disciplinary topic that is closely related
to parallelization of EAs, coevolution, EC assisted with meta-models, etc.
Specifically, the anticipated interest of the proposed task force includes:
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EC for large scale single objective numerical optimization, where the problem involves a large number of decision variables.
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EC for large scale combinatorial optimization, such as the Traveling Salesman Problem (TSP),
Vehicle/Arc Routing Problem (VRP/ARP), scheduling problem and etc.
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EC for large scale multi-objective optimization. In the context of MO, the term "large scale" may refer to either large
number of decision variables or objectives, or both.
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Application of large scale EC techniques in challenging real-world problems.
Proposed activities
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Organize workshops (e.g., IEEE Symp.)
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Organize special sessions at international conferences (e.g., CEC)
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Organize journal special issues
News & events
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Special Issue of Information Sciences Journal (ISJ) on "Nature-Inspired Algorithms for Large Scale Global Optimization", September 2015.
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CEC'2015 Tutorial "Decomposition and Cooperative Coevolution Techniques for Large Scale Global Optimization", May 25, 2015.
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CEC'2015 Special Session/Competition on Large Scale Global Optimization, May 25 - 28, 2015.
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MIDAS - a useful tool for comparing LSGO algorithms (in an automated way).
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GECCO'2014 Tutorial "Decomposition and Cooperative Coevolution Techniques for Large Scale Global Optimization".
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CEC'2014 Special Session on Large Scale Global Optimization, July 5 - 11, 2014.
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CEC'2013 Special Session and Competition on Large Scale Global Optimization, June 20 - 23, 2013.
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CEC'2010 Special Session and Competition on Large Scale Global Optimization, July 18-23, 2010.
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Special Issue in Soft Computing Journal on Large Scale Optimization, submission deadline: February 28, 2010.
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CEC'2008 Special Session and Competition on Large Scale Global Optimization, June 1-6, 2008.
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Website for this Task Force was Launched, November 7, 2007.
Chair
Xiaodong Li (Chair from 2012 - 2015)
School of Computer Science and Information Technology
RMIT University, Melbourne, Australia.
Ke Tang (Vice-Chair)
School of Computer Science,
University of Science and Technology of China (Founding chair)
P. N. Suganthan (Vice chair)
School of Electrical and Electronic Engineering
Nanyang Technological University, Singapore
Members
Xin Yao (University of Birmingham, U.K.)
Daniel Molina (University of Cadiz, Spain)
Ferrante Neri (University of Jyväskylä, Finland)
Janez Brest ( University of Maribor, Slovenia)
Swagatam Das (Indian Statistical Institute, India)
Kai Qin (University of Waterloo, Canada)
Manuel Lozano (University of Granada, Spain)
Zhenyu Yang (National University of Defense Technology, China)
Yew-soon Ong (Nanyang Technological University, Singapore)
Antonio LaTorre (Universidad Politécnica de Madrid, Spain)
Yew-soon Ong (Nanyang Technological University, Singapore)
Thomas Stützle (Université Libre de Bruxelles, Belgium)
Bin Li (University of Science and Technology of China, China)
Thomas Bäck (Leiden University, Netherlands)
Anikó Ekárt (Aston University, U.K.)
Maoguo Gong (Xidian University, China)
Yuping Wang (Xidian University, China)
Hui Li (Xi'an Jiaotong University, China)
Yi Mei (Victoria University of Wellington, New Zealand)
Mohammad Nabi Omidvar (RMIT University, Australia)
Contact us
If you have any suggestions for this task force, please contact:
Xiaodong Li:
xiaodong.li@rmit.edu.au
