Special Session & Competition on

Large Scale Global Optimization

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

June 1 - 6, 2008, Hong Kong

Test suite for our companion competition is available from https://github.com/P-N-Suganthan 


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, November 2007.


 Performance Comparisons and analysis in pdf: https://github.com/P-N-Suganthan

Accepted Papers are listed below (Codes Available for DMS-PSO)

(PDFs are available: https://github.com/P-N-Suganthan )

1.     Janez Brest, Aleˇs Zamuda, Borko Boˇskovi´c, Mirjam Sepesy Mauˇcec, and Viljem ˇZumer, "High-Dimensional Real-Parameter Optimization using Self-Adaptive Differential Evolution Algorithm with Population Size Reduction"

2.     Sheng-Ta Hsieh, Tsung-Ying Sun, Chan-Cheng Liu and Shang-Jeng Tsai, "Solving Large Scale Global Optimization Using Improved Particle Swarm Optimizer"

3.     Cara MacNish, Xin Yao, "Direction Matters in High-Dimensional Optimisation"

4.     Lin-Yu Tseng and Chun Chen, "Multiple Trajectory Search for Large Scale Global Optimization"

5.     Yu Wang, Student Member, IEEE, Bin Li, Member, IEEE, "A Restart Univariate Estimation of Distribution Algorithm: Sampling under Mixed Gaussian and L´evy probability Distribution"

6.   Zhenyu Yang, Ke Tang and Xin Yao, "Multilevel Cooperative Coevolution for Large Scale Optimization"

7.     Aleˇs Zamuda, Janez Brest, Borko Boˇskovi´c, Viljem ˇ Zumer, "Large Scale Global Optimization Using Differential Evolution With Self-adaptation and Cooperative Co-evolution"

8.     S. Z. Zhao, J. J. Liang, P. N. Suganthan, and M. F. Tasgetiren, "Dynamic Multi-Swarm Particle Swarm Optimizer with Local Search for Large Scale Global Optimization"


Update Notice:

  1. 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++.
  2. 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.
1.    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.

2.    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

Acceptance Notification:

Feb 1, 2008

Final Manuscript Due:

Mar 1, 2008

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

Cara MacNish
School of Computer Science & Software Engineering
The University of Western Australia
M002, 35 Stirling Highway, Crawley, Western Australia, 6009