Introduction to the special session:
An evolutionary optimization algorithm can be viewed as a learning process - it learns properties of the problem in question and locates the optimal solution. Therefore, it is very natural to introduce statistical & machine learning (SML) techniques into evolutionary algorithms (EA). Some examples are the surrogate assist EAs and the EAs by building and sampling probability models, such as estimation of distribution algorithms (EDA), ant colony optimization (ACO), cross-entropy methods, covariance matrix adaptation evolution strategy (CMA-ES), etc. The combination of EAs and SML has been proven to be an efficient strategy for dealing with hard optimization problems. Not only the aforementioned approaches, but also other SML techniques, including regression, density estimation, classification, clustering, and other techniques, can be applied to guide the EA search. This special session aims at bringing researchers who are interested in this area together to review the current state-of-art, exchange the latest ideas and explore future directions.The major topics of interest include, but are not limited to:
- Theoretical work on EAs with SML
- Experimental studies of EAs with SML
- EAs with SML for multiobjective optimization problems
- EAs with SML in dynamic environments
- EAs with SML for expensive black-box optimization
- Real-world/novel applications
Deadline:
The deadline for submissions to this special session is 20 December 2013.Information for Authors:
- All papers should be submitted electronically through: http://ieee-cis.org/conferences/cec2014/upload.php
- To submit your papers to the MC special session, please select the Special Session name in the Main Research topic.
- For more submission information please visit: http://www.ieee-wcci2014.org/Paper%20Submission.htm
- All accepted papers will be published in the WCCI 2014 electronic proceedings, included in the IEEE Xplore digital library, and indexed by EI Compendex.
Organizers:
- Dr. Aimin Zhou, East China Normal University, amzhou@cs.encu.edu.cn
- Prof. John McCall, Robert Gordon University, j.mccall@rgu.ac.uk
- Prof. Qingfu Zhang, University of Essex, qzhang@essex.ac.uk
- Prof. Jose A. Lozano, University of the Basque Country, ja.lozano@ehu.es
- Prof. Pedro LarraƱaga, Polytechnic University of Madrid, pedro.larranaga@fi.upm.es
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