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ALLSTAT  October 2010

ALLSTAT October 2010

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Subject:

CFP - JORS Special Issue on Systems to Build Systems

From:

Ender Ozcan <[log in to unmask]>

Reply-To:

Ender Ozcan <[log in to unmask]>

Date:

Mon, 25 Oct 2010 15:10:03 +0100

Content-Type:

text/plain

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[Please circulate to all those who might be interested, and accept our
apologies if you received multiple copies of this announcement]
****************************************************************
                          CALL FOR PAPERS                        
                                                                  
          Journal of the Operational Research Society             
           Special Issue on Systems to Build Systems              
                                                                  
                    Deadline: 1st of March, 2011                  
                                                                  
    http://www.cs.nott.ac.uk/~exo/specialissue/JORS2011.html      
****************************************************************
Guest editors: 
 Edmund K. Burke, [log in to unmask]
 Ender Ozcan, [log in to unmask]
 Jonathan Thompson, [log in to unmask]

DESCRIPTION:
The current state of the art in the development of decision support systems
and search methodologies is focused around the human design of bespoke
systems, which are specifically tailored to the problem solving environment
in hand. Although such systems are often highly successful and useful, their
development cost is often high due to the human (expert) resources required.
Hence, an ever more important goal is to develop intelligent systems which
are capable of automatically building (and/or selecting) other systems. Over
the past few years, there has been a growing interest in developing such
-systems to build systems- to accomplish this challenging task. The ultimate
aim is to raise the level of generality by providing a more broadly
applicable solution, as opposed to dealing with single problems. These types
of -systems to build systems- have the potential to significantly reduce the
resource cost that is often associated with developing tailored systems,
since the algorithm construction/selection part of the development process
is automated.

The main purpose of this special issue is to reveal the recent advances in
the field, including novel methodologies, their foundations, frameworks and
applications to real-world problems. 

SCOPE:
Topics on the systems to build systems (e.g. hyper-heuristics) include (but
not limited to):
 * new methodologies to build (and/or select) systems
 * automated (computer aided) design of heuristics (e.g., by genetic
programming, grammatical evolution, and others)
 * adaptive/self-tuning methodologies to build systems (e.g. evolutionary
algorithms, multi-meme algorithms, adaptive operator selection, dynamic
algorithm portfolios, reactive search, and others)
 * machine learning techniques to support/build systems (e.g. learning
classifier systems, data mining, reinforcement learning, neural networks,
and others)
 * fuzzy systems to build systems
 * applications and new challenging domains, particularly real-world
problems
 * foundational studies towards the understanding of systems to build
systems
 * classifications of methodologies
 * generality of the methodologies to build systems
 * scalability issues
 * issues in multi-objective, discrete and continuous methodologies to build
systems
 * issues in comparison of systems to build systems over multiple problem
domains 

SUBMISSIONS:
Papers should be submitted electronically via the Journal of the Operational
Research Society's online submission system at http://jors.msubmit.net/,
following the journal's instructions to authors at
http://www.palgrave-journals.com/jors/. Please indicate that your submission
is to the Special Issue on "Systems to Build Systems" (by selecting it as
the article type). All papers submitted to the special issue will go through
the normal strict peer review process of the Journal of the Operational
Research Society to ensure the high quality of this volume.
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