In the past two decades, different kinds of nature-inspired optimization algorithms have been developed and applied to solve optimization problems,
including Simulated Annealing (SA), Evolutionary Algorithms (EAs), Differential Evolution (DE), Particle Swarm Optimization (PSO),
Ant Colony Optimization (ACO), Estimation of Distribution Algorithms (EDA), etc. Although these approaches have shown excellent search abilities when
applying to some small or medium size problems, many of them will encounter severe difficulties when applying to large scale problems, e.g., problems with
up to 1000 variables. The reasons appear to be two-fold. First, the complexity of a problem usually increases with the number of decision variables,
number of constraints, or even number of objectives (for multi-objective optimization). This emergent complexity might prevent a previously successful
search strategy from finding the optimal solution. Second, the solution space of the problem increases exponentially with the number of decision variables,
and a more efficient search strategy is required to explore all the promising regions with limited computational resources.
Historically, scaling up EAs to large scale problems has attracted much interest, including both theoretical and practical studies.
However, existing work in the areas of EAs are still limited given the significance of the scalability issue.
Due to this fact, this special session is devoted to highlight the recent advances in EAs for large scale optimization problems,
involving single objective or multiple objectives, unconstrained or constrained problems, binary or discrete or real or mixed decision variables.
Specifically, we encourage interested researchers to submit their latest work on:
- Both theoretical and experimental analysis of the scalability of EAs.
- Novel approaches and algorithms for scaling up EAs to large scale optimization problems.
- Applications of EAs to real-world large scale optimization problems.
- Papers on novel test suites that help us in understanding problem characteristics are also welcome.
Furthermore, a companion competition on Large Scale Global Optimization will also be organized in company with our special session.
The competition allows participants to run their own algorithms on 20 benchmark functions, each of which is of 1000 dimensions. The purpose of this competition is
to compare different algorithm on the exactly same platform. Researchers are welcome to apply any kind of evolutionary computation approach to the test suite.
The approach and the results can be reported in a paper for the special session (i.e., submitted via the online submission system of WCCI-2012).
Important Dates
| Paper Submission: |
December 19, 2011 |
| Acceptance Notification: |
February 20, 2012 |
| Final Manuscript Due: |
April 2, 2012 |
Paper Submission
Manuscripts should be prepared according to the standard format and page limit specified in CEC 2012.
For more submission instructions, please see the WCCI submission page at:
http://www.ieee-wcci2012.org. Please indicate during submission that your paper is submitted to this special session.
Special Session Organizers
Ke Tang
Nature Inspired Computation and Applications Laboratory (NICAL)
School of Computer Science and Technology
University of Science and Technology of China, Hefei, Anhui, China
Email:
ketang@ustc.edu.cn, Website: http://staff.ustc.edu.cn/~ketang
Zhenyu Yang
Department of Computer Science and Technology
East China Normal University, Shanghai, China
Email: zhyuyang@mail.ustc.edu.cn
Thomas Weise
Nature Inspired Computation and Applications Laboratory (NICAL)
School of Computer Science and Technology
University of Science and Technology of China, Hefei, Anhui, China
Email: tweise@gmx.de, Website: http://www.it-weise.de
Program Committee
- Swagatam Das, Jadavpur University, India
- Yaochu Jin, University of Surrey, UK
- Bin Li, University of Science and Technology of China, China
- Xiaodong Li, RMIT University, Australia
- Manuel Lozano, University of Granada, Spain
- Alberto Moraglio, University of Birmingham, UK
- Mohammad N. Omidvar, RMIT University, Australia
- Yew Soon Ong, Nanyang Technological University, Singapore
- Kai Qin, INRIA Grenoble Rhone-Alpes, France
- Shahryar Rahnamayan, University of Ontario Institute of Technology, Canada
- Ponnuthurai Nagaratnam Suganthan, Nanyang Technological University, Singapore
- Yong Wang, Central South University, China
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