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IEEE Transactions on Evolutionary Computation:
Special Issue on Theoretical Foundations of Evolutionary Computation
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CALL FOR PAPERS
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I. AIM AND SCOPE
================
Evolutionary computation (EC) methods such as evolutionary algorithms,
ant colony optimization and artificial immune systems have been
successfully applied to a wide range of problems. These include classical
combinatorial optimization problems and a variety of continuous, discrete
and mixed integer real-world optimization problems that are often hard to
optimize by traditional methods (e.g., because they are non-linear, highly
constrained, multi-objective, etc.). In contrast to the successful
applications, there is still a need to understand the behaviour of these
algorithms. The achievement and development of a solid theory of
bio-inspired
computation techniques is important as it provides sound knowledge on their
working principles. In particular, it explains the success or the failure
of
these methods in practical applications. Theoretical analyses lead to the
understanding of which problems are optimized (or approximated) efficiently
by a given algorithm and which ones are not. The benefits of theoretical
understanding for practitioners are threefold.
1) Aiding algorithm design,
2) guiding the choice of the best algorithm for the problem at hand and
3) determining optimal parameter settings.
The aim of this special issue is to advance the theoretical understanding
of
evolutionary computation methods. We solicit novel, high quality scientific
contributions on theoretical or foundational aspects of evolutionary
computation. A successful exchange between theory and practice in
evolutionary
computation is very desirable and papers bridging theory and practice are
of
particular interest. In addition to strict mathematical investigations,
experimental studies strengthening the theoretical foundations of
evolutionary
computation methods are very welcome.
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II. THEMES
=========
This special issue will present novel results from different sub-areas of
the
theory of bio-inspired algorithms. The scope of this special issue includes
(but is not limited to) the following topics:
-Exact and approximation runtime analysis
-Black box complexity
-Self-adaptation
-Population dynamics
-Fitness landscape and problem difficulty analysis
-No free lunch theorems
-Theoretical Foundations of combining traditional optimization techniques
with EC methods
-Statistical approaches for understanding the behaviour of bio-inspired
heuristics
-Computational studies of a foundational nature
All classes of bio-inspired optimization algorithms will be considered
including
(but not limited to) evolutionary algorithms, ant colony optimization,
artificial
immune systems, particle swarm optimization, differential evolution, and
estimation
of distribution algorithms. All problem domains will be considered
including discrete
and continuous optimization, single-objective and multi-objective
optimization,
constraint handling, dynamic and stochastic optimization, co-evolution and
evolutionary learning.
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III. SUBMISSION
=============
Manuscripts should be prepared according to the "Information for Authors"
section of the journal found at http://ieee-cis.org/pubs/tec/authors/ and
submissions should be made through the journal submission website:
http://mc.manuscriptcentral.com/tevc-ieee/, by selecting the Manuscript
Type
of "TFoEC Special Issue Papers" and clearly adding "TFoEC Special Issue
Paper"
to the comments to the Editor-in-Chief.
Submitted papers will be reviewed by at least three different expert
reviewers.
Submission of a manuscript implies that it is the authors' original
unpublished
work and is not being submitted for possible publication elsewhere.
Each submission will contain at least one paragraph explaining why the
paper is
(potentially) relevant to practice.
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IV. IMPORTANT DATES
==================
Submission open: February 1, 2018
Submission deadline: October 1, 2018
Tentative publication date: 2019
Papers will be assigned to reviewers as soon as they are submitted.
Papers will be published online as soon as they are accepted.
For further information, please contact one of the following Guest Editors.
===============
V. GUEST EDITORS
===============
Pietro S. Oliveto
Department of Computer Science
University of Sheffield
United Kingdom
p.oliveto@sheffield.ac.uk
Anne Auger
INRIA
Ecole Polytechnique Paris
France
anne.auger@jnria.fr
Francisco Chicano
Department of Languages and Computing Sciences
University of Malaga
Spain
chicano@lcc.uma.es
Carlos M. Fonseca
Department of Informatics Engineering
University of Coimbra
Portugal
cmfonsec@dei.uc.pt
--
Pietro S. Oliveto
Senior Lecturer,
EPSRC Early Career Fellow,
Department of Computer Science,
The University of Sheffield, Sheffield, UK.
*www.dcs.shef.ac.uk/people/P.Oliveto/rig/
<http://www.dcs.shef.ac.uk/people/P.Oliveto/rig/>*
*Fully funded PhD studentships available now* in time complexity analysis
of bio-inspired computation. Enquiries by excellent candidates can be sent
to me by email. Applications will be accepted until the posts are filled.
Further details are here
<http://staffwww.dcs.shef.ac.uk/people/P.Oliveto/PhDStudentships.html>.
Applicants should apply using the online application form here
<http://www.shef.ac.uk/postgraduate/online>
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