Purpose of the Task Force
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 purpose of this task force is:
-
To promote the research and development of evolutionary computation techniques for large scale optimization problems.
-
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).
-
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 existing infrastructure at the University of Birmingham can be used for such purpose:
EvoCoBR: http://www.cs.bham.ac.uk/research/projects/ecb/
The Anticipated Interest in the Topic Area
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:
-
EC for large scale single objective numerical optimization, where the problem involves a large number of decision variables.
-
EC for large scale combinatorial optimization, such as the Traveling Salesman Problem (TSP),
Vehicle/Arc Routing Problem (VRP/ARP), scheduling problem and etc.
-
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.
-
Application of large scale EC techniques in challenging real-world problems.
Proposed Activities
-
Organize workshops (e.g., IEEE Symp.)
-
Organize special sessions at international conferences (e.g., CEC)
-
Organize journal special issues
Related News & Events
-
CEC2008's Special Session and Competition on Large Scale Global Optimization.
-
Website for this Task Force has been Launched, Nov 07, 2007.
Chair
Ke Tang:
Nature Inspired Computation and Applications Laboratory (NICAL),
USTC, China.
Membership List
Ke Tang
Nature Inspired Computation and Applications Laboratory (NICAL)
Department of Computer Science and Technology
University of Science and Technology of China, Hefei, Anhui, China
Xin Yao
Nature Inspired Computation and Applications Laboratory (NICAL)
Department of Computer Science and Technology
University of Science and Technology of China
The Centre of Excellence for Research in Computational Intelligence and Applications (CERCIA)
School of Computer Science
University of Birmingham, Edgbaston, Birmingham B15 2TT, U.K.
P. N. Suganthan
School of Electrical and Electronic Engineering
Nanyang Technological University, Singapore
http://www.ntu.edu.sg/home/epnsugan
Cara MacNish
School of Computer Science & Software Engineering
The University of Western Australia
M002, 35 Stirling Highway, Crawley, Western Australia, 6009
Yaochu Jin
Honda Research Institute Europe
Carl-Legien-Str. 3063073 Offenbach, Germany
Jin Li
Safety & Environmental Assurance Centre
Unilever Colworth Science Park
Sharnbrook, Bedford, MK44 1LQ, United Kingdom
Anikó Ekárt
Computer Science
School of Engineering and Applied Science
Aston University, Birmingham, United Kingdom
Partha Dutta
Strategic Research Centre
Rolls-Royce plc.
PO Box 31
Derby DE24 3JS, United Kingdom
Dr. Shahryar Rahnamayan
Product Design and Optimization Lab
Simon Fraser University
Mechatronic Systems Engineering
School of Engineering Science
Simon Fraser University Surrey
250-13450 102 Avenue
Surrey, BC, Canada V3T 0A3
Kay Chen Tan
Department of Electrical and Computer Engineering
National University of Singapore
4 Engineering Drive 3, Singapore 117576
Contact
If you have any suggestions for this task force, please contact:
Ke Tang:
ketang@ustc.edu.cn
