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2013 IEEE Congress on Evolutionary Computation Special Session on:

Large Scale Global Optimization

June 20 - 23, 2013, Cancun, Mexico

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

In the past two decades, many nature-inspired optimization algorithms have been developed and applied successfully for solving a wide range of 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 techniques have shown excellent search capabilities when applying to small or medium sized problems, they still encounter serious challenges when applying to large scale problems, i.e., problems with several hundreds to thousands of variables. The reasons appear to be two-fold. Firstly, the complexity of a problem usually increases with the increasing number of decision variables, constraints, or objectives (for multi-objective optimization problems). Problems with this high level of complexity may prevent a previously successful search strategy from locating the optimal solutions. Secondly, the size of the solution space of the problem also increases exponentially with the number of decision variables. As a result, a more efficient search strategy is required to explore all the promising regions with limited computational resources.

In recent years, researches on scaling up EAs to large scale problems have attracted much attention, including both theoretical and practical studies. Existing work on this topic are still rather limited, given the significance of the scalability issue. This special session is devoted to highlight the recent advances in EAs for handling large scale global optimization (LSGO) problems, involving single objective or multiple objectives, unconstrained or constrained, binary/discrete or real, or mixed decision variables. More specifically, we encourage interested researchers to submit their original and unpublished work on:

·         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 understand problem characteristics.

Furthermore, a companion competition on Large Scale Global Optimization (LSGO) will also be organized in conjunction with our special session. The competition allows participants to run their own algorithms on 15 benchmark functions, each of which is of 1000 dimensions. The aim of this competition is to provide a common platform that encourages fair and easy comparisons across different LSGO algorithms. Researchers are welcome to apply any kind of evolutionary computation technique to the test suite. The technique and the results can be reported in a paper for the special session (i.e., submitted via the online submission system of CEC’2013). In case it is too late to submit the results in a paper (i.e., passing the CEC 2013 submission deadline); authors are still allowed to submit their results directly to the special session organizers, in order to be counted in the competition.

Apart from the above, we are also organizing a Special Issue of Information Sciences Journal (ISJ) on "Nature-Inspired Algorithms for Large Scale Global Optimization" (due 30 September 2013). We welcome your original and significant work there.

Important Dates:

·         Paper Submission: 15 March 2013 (extended)

·         Decision Notification: 22 April 2013

·         Final Paper Submission: 6 May 2013

Paper Submission:

Manuscripts should be prepared according to the standard format and page limit specified in CEC 2013. For more submission instructions, please see the CEC’2013 submission page at: http://www.cec2013.org/. Please indicate during submission that your paper is submitted to this special session.

Technical Committee:

·       Ong Yew Soon, Nanyang Technological University, Singapore

·       Bin Li, University of Science and Technology of China, China

·       Kai Qin, RMIT University, Australia

·       Yi Mei, RMIT University, Australia

·       Aimin Zhou, East China Normal University, China

·       Ponnuthurai N. Suganthan, Nanyang Technological University, Singapore

·       Swagatam Das, Indian Statistical Institute, India

·       Thomas Stuetzle, University of Brussels Belgium

·  Maoguo Gong, Xidian University, China

·  Zexuan Zhu, Shenzhen University, China

·  Ferrante Neri, University of Jyväskylä, Finland

·  Janez Brest, University of Maribor, Slovenia

·  Lining Xing, National University of Defense Technology, China

·  Antonio LaTorre, Universidad Politécnica de Madrid, Spain

·  Santiago Muelas, Universidad Politécnica de Madrid, Spain

Special Session Organizers:

Xiaodong Li

School of Computer Science and Information Technology

RMIT University

Melbourne, VIC 3001, Australia

Email: xiaodong.li@rmit.edu.au

 

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

 

Zhenyu Yang

College of Information System and Management

National University of Defense Technology (NUDT), Changsha, China

Email: zhyuyang@mail.ustc.edu.cn

 

 

Last updated: 22 January 2013 - Maintained by Xiaodong Li