2011-10-26: CEC Special Session: Large Scale Global Optimization

Call for Participation

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 competition on Large-Scale Numerical Optimization will also be organized in company with our special session. This competition is built on the successful special session and competition on LSGO in CEC?2010. For the competition in CEC?2012, the previously proposed CEC?2010 benchmark test suite, which consists of 20 benchmark test functions capturing a range of problem characteristics, will be used. Participants of the competition will be required to evaluate their existing or novel algorithms using the test suite, and are welcome to report their approaches and results in a paper submitted to the special session. The competition will provide the participants a great opportunity to compare their LSGO algorithms with others.

For more information about the special session and competition, such as the deadlines and the benchmark problems, please visit the corresponding webpages:

• For Special Session: http://staff.ustc.edu.cn/~ketang/cec2012/cec2012lsgo.htm
• For Competition: http://staff.ustc.edu.cn/~ketang/cec2012/lsgo_competition.htm