Special Session on

Large Scale Global Optimization

2008 IEEE World Congress on Computational Intelligence (CEC@WCCI-2008)

June 1 - 6, 2008, Hong Kong

New: Comparisons among the accepted entries

Call for papers
The Companion Competition
Test suite for our companion competition is available here

Reference: K. Tang, X. Yao, P. N. Suganthan, C. MacNish, Y. P. Chen, C. M. Chen, and Z. Yang, "Benchmark Functions for the CEC'2008 Special Session and Competition on Large Scale Global Optimization," Technical Report, Nature Inspired Computation and Applications Laboratory, USTC, China, http://nical.ustc.edu.cn/cec08ss.php, 2007.

To those who may participate in the competition: Please could you inform Ke Tang about your participation, so that we can update you about any correction of bugs or extension of the deadline.

Update Notice:

  1. Nov 27, 2007: Paper Submission Deadline Extended to Dec 15, 2007.

  2. Nov 12, 2007: The C/C++ code for function 7 has been included in the package. It is contributed by Ales Zamuda from the University of Maribor, Slovenia. It uses the GJC/CNI interface to run the Java code from C++.

  3. Nov 07, 2007: Another test function (Function 7 - FastFractal "DoubleDip"), which is contributed by Cara MacNish, has been added to the test suite. This function is also available at the Evolutionary Computation Benchmark Repository.


Call for papers
In the past two decades, different kinds of nature-inspired optimization algorithms have been designed and applied to solve optimization problems, e.g., simulated annealing (SA), evolutionary algorithms (EAs), differential evolution (DE), particle swarm optimization (PSO), Ant Colony Optimisation (ACO), Estimation of Distribution Algorithms (EDA), etc. Although these approaches have shown excellent search abilities when applying to some 30-100 dimensional problems, many of them suffer from the "curse of dimensionality", which implies that their performance deteriorates quickly as the dimensionality of search space increases. The reasons appear to be two-fold. First, complexity of the problem usually increases with the size of problem, and a previously successful search strategy may no longer be capable of finding the optimal solution. Second, the solution space of the problem increases exponentially with the problem size, and a more efficient search strategy is required to explore all the promising regions in a given time budget.

Historically, scaling EAs to large size problems have attracted much interest, including both theoretical and practical studies. The earliest practical approach might be the parallelism of an existing EA. Later, cooperative coevolution appears to be another promising method. However, existing work on this topic are often limited to the test problems used in individual studies, and a systematic evaluation platform is not available in the literature for comparing the scalability of different EAs.

This special session is devoted to the novel approaches, algorithms and techniques for tackling large scale global optimization problems, involving single objective or multiple objectives, binary or discrete or real or mixed variables. Papers on novel test suites that help us in understanding problem characteristics are also welcome. We encourage all authors to submit their test functions, algorithms and results to the Birmingham Benchmark site -- Evolutionary Computation Benchmark Repository:
EvoCoBR: http://www.cs.bham.ac.uk/research/projects/ecb/

Further, a set of scalable function optimization problems are available at: LSGO.CEC08.Benchmark.zip. Researchers who make use of this test suite may also participate in our companion competition too.


The Companion Competition
A competition on high-dimensional function optimization will also be organized in company with our special session. In the competition, a set of scalable function optimization problems are provided. The details of the set of scalable functions and requirements on the simulation procedure are available here. Researchers are welcome to apply any kind of computational intelligence approaches (e.g. EAs, Neural Nets, fuzzy-based methods) to the test suite. The results of this competition will be archived on our web pages as done for the CEC 2005, 2006, 2007.

The WCCI2008 committee will kindly provide one free registration for the winner of the competition.


Important Dates
Paper Submission: Dec 1, 2007 -> Dec 15, 2007
Acceptance Notification: Feb 1, 2008
Final Manuscript Due: Mar 1, 2008

For latest news, please refer to www.wcci2008.org.


Paper Submission
Manuscripts should be prepared according to the standard format and page limit specified in CEC 2008: All special session papers will be treated in the same way as regular papers.
The confernce proceedings of CEC have been continuously included in the EI Compendex Database and IEEE Xplore.

Notice:
When submitting, please make sure you have chosen "Large Scale Global Optimization" as the "Main Research Topic".


Contact
Ke Tang: ketang@ustc.edu.cn



Special Session Organizers
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