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{ \wwwwwwwwwwwwww wwwwwwwww@O: Special Session on Evolutionary Multiobjective Optimization: Methods and Engineering Application
This special session invites papers discussing recent advances in the development and applications of naturalinspired multiobjective optimization algorithms.
Many problems from science and engineering involve several conflicting objectives that have to be optimized simultaneously. A number of evolutionary multiobjective optimization (EMO) algorithms have already been proposed to solve such multiobjective optimization problems. This is motivated mainly because the populationbased nature of EAs enables them to get a set of Paretooptimal solutions in a single run.
Currently, researchers in the EMO community are working towards finding out effective and efficient approaches to handle manyobjective problems with more than two or three conflicting objectives to be optimized simultaneously. Also, there is an increasing interest in using evolutionary algorithms to various engineering problems. These engineering applications, which often have many objectives, provide problems of various types of difficulties for the design and testing of evolutionary algorithms.
The main aim of this special session is to bring together both experts and newcomers working on Evolutionary Multiobjective Optimization (EMO) to discuss new and exciting issues in this area, including both theory and application.
We encourage submission of papers describing new concepts, strategies and tools providing practical implementations. In addition, we are interested in application papers discussing the power and applicability of these novel methods to realworld problems in different areas in science and engineering. You are invited to submit papers that are unpublished original work for this special session.
The main subjects of interests include but are not limited to:
Evolutionary manyobjective optimization
Novel EMO algorithmic techniques including those using heuristics such as artificial immune systems, particle swarm optimization, differential evolution, cultural algorithms, etc.
Test and benchmark problems for EMO algorithms, Performance measures for EMO algorithms
Realworld applications of EMO algorithms in engineering, computer science, scientific computation, EMO control problems, EMO machine learning
Handling practicalities, such as uncertainty, noise, constraints, preference, dynamic problems, computationally expensive problems, etc.
Hybrid approaches combining, for example, EMO algorithms with mathematical programming techniques and exact methods
Theoretical results on multiobjective evolutionary optimization
Important dates:
Paper Submission: 1 August 2014
Decision Notification: 1 September 2014
CameraReady Submission: 1 October 2014
Paper Submission:
You should follow the submission instruction at: http://www.ies2014.org . Special session papers are treated the same as regular conference papers.
CoOrganizers:
Hailin Liu, Ph.D., School of Applied Mathematics, Guangdong University of Technology, Guangzhou, China. Email: hlliu@gdut.edu.cn
Yuping Wang, Ph.D., School of Computer Science and Technology, Xidian University, Xian, China. Email: ywang@xidian.edu.cn.
Zhun Fan, Ph.D., Prof., Department of Electronic Engineering, Shantou University, Shantou, China. Email:HYPERLINK "mailto:zfan@stu.edu.cn"zfan@stu.edu.cn.
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