2014 IEEE Congress on Evolutionary Computation Special Session on:Large Scale Global OptimizationJuly 6 - 11, 2014, Beijing, China
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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, as the size of the solution space of the problem grows exponentially with the increasing number of decision variables, there is an urgent need to develop more effective and efficient search strategies to better explore this vast solution space with only limited computational budgets. 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 More specifically, we encourage interested researchers to submit their original and unpublished work on: · Theoretical and experimental analysis of the scalability of EAs; · Novel approaches and algorithms for scaling up EAs to large scale optimization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. Note that a previously proposed benchmark suite may help researchers to evaluate and compare LSGO algorithms with the state-of-the-art can be found in IEEE CEC'2013 Competition on Large Scale Global Optimization . This benchmark suite is aimed to provide a common platform that encourages fair and easy comparisons across different LSGO algorithms. The benchmark suite allows researchers to run their own LSGO algorithms on 15 benchmark functions of 1000 dimensions with different characteristics and challenges. Important Dates:· Paper Submission: 20 January 2014 (extended final deadline) · Decision Notification: 15 March 2014 · Final Paper Submission: 15 April 2014 Paper Submission:Manuscripts should be prepared according to the standard format and page limit specified in WCCI'2014. For more submission instructions, please see the WCCI’2014 submission page at: http://www.ieee-wcci2014.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 · Ponnuthurai N. Suganthan, Nanyang Technological University, Singapore · Ferrante Neri, University of Jyväskylä, Finland · Lining Xing, National University of Defense Technology, China · Zexuan Zhu, Shenzhen University, China · Maoguo Gong, Xidian University, China · Antonio LaTorre, Universidad Politécnica de Madrid, Spain · Santiago Muelas, Universidad Politécnica de Madrid, Spain · Thomas Stuetzle, University of Brussels Belgium · Giovanni Iacca, INCAS, The Netherlands · Aimin Zhou, East China Normal University, China · Janez Brest, University of Maribor, Slovenia 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@ieee.org
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Last updated: 18 October 2013 - Maintained by Xiaodong Li
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