IEEE Transactions on Evolutionary Computation

Evolutionary Algorithms based on Probabilistic Models

AIM & SCOPE
Evolutionary algorithms based on probabilistic models (EAPM) have been recognized as a new computing paradigm in evolutionary computation. There is no traditional crossover or mutation in EAPMs. Instead, they explicitly extract global statistical information from their previous searches and build a probability distribution model of promising solutions, based on the extracted information. New solutions are then sampled from the model thus built. Instances of EAPMs include estimation of distribution algorithms, probabilistic model building genetic algorithms, ant colony optimization, and the cross entropy method, to name just a few. Recent years have seen a growing interest in the research and application of EAPMs. As an interdisciplinary research area, the development of EAPMs needs joint effort from researchers and practitioners in evolutionary computation, machine learning, statistics and simulation. The aim of this special issue is to be a milestone event in the developmen! t of EAPMs, which will highlight the recent development of EAPMs, clarify outstanding issues for future progress, and disseminate EAPMs to a wider audience to attract more researchers to EAPMs.

TOPICS COVERED
Suggested topics include (but are not limited to) the following:
· Theory of EAPMs
· New EAPMs
· Combination of machine learning techniques and EAPMs
· Combination of statistics techniques and EAPMs
· Combination of other heuristics and EAPMs
· EAPMs for multiobjective optimization problems
· EAPMs in dynamic and noisy environments
· Parallel implementation of EAPMs
· Real-world/novel applications

IMPORTANT DATES
· July 31, 2007, Submission deadline
· November 30, 2007, Notification of the first review
· January 31, 2008, Revised versions due
· March 30, 2008, Final notice of acceptance/reject
· April 30, 2008, Final manuscript. The expected publication year of the special issue will be 2008.

SUBMISSIONS
Manuscripts should be prepared according to the instructions of the "Information for Authors" section of the journal founded at ( http://ieee-cis.org/pubs/tec/authors/) and submission should be done through the journal website: http://tevcieee.manuscriptcentral.com/ and clearly mark "Special Issue on EAPM" as comments to the editor-in-chief. Submission of a manuscript implies that it is the authors' original unpublished work and is not being submitted for possible publication elsewhere. The review process will be driven by the Guest Editors of this Special Issue and the Editor-in-Chief, Prof. Xin Yao. For any clarification please contact Jose A. Lozano, Qingfu Zhang or Pedro Larra~naga at the addresses below.

GUEST EDITORS

Prof. Jose A. Lozano
Department of Computer Science and AI
University of the Basque Country, Spain
Tel.:+34 943 018029 e-mail: ja.lozano@ehu.es
url: http://www.sc.ehu.es/isg

Dr. Qingfu Zhang
Department of Computer Science
University of Essex, UK
Tel.: +441206 872336
e-mail: qzhang@essex.ac.uk
url: http://cswww.essex.ac.uk/staff/qzhang

Prof. Pedro Larra~naga
Department of Computer Science and AI
University of the Basque Country, Spain
Tel.:+34 943 018045
e-mail: pedro.larranaga@ehu.es
url: http://www.sc.ehu.es/isg