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FIRST ANNUAL WORKSHOP ON METAHEURISTIC DESIGN PATTERNS (MetaDeeP-2014)
to be held as part of the 2014 Genetic and Evolutionary Computation
Conference (GECCO-2014) Vancouver, BC, Canada, July 12-16, 2014
Organized by ACM SIGEVO http://www.sigevo.org/gecco-2014/
PAPER SUBMISSION DEADLINE: March 28th, 2014
Workshop URL:
http://www.cs.stir.ac.uk/~jsw/metaheuristic-design-patterns/MDPWorkshop2014.htm
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You've (presumably) received this email because you're interested in EC
and/or metaheuristics:
* Do you have an idea about how metaheuristics could be better
hybridized or generated?
* Have you observed some commonality (e.g. across frameworks or
methodologies) that is not yet widely recognized?
* Are you frustrated when researchers don't follow best practices that
are well-understood in your field?
If so, then you should attend MetaDeeP 2014 – the first Workshop on
Metaheuristic Design Patterns.
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Why Design Patterns?
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Over the last 20 years, Evolutionary Computation (and meta- and hyper-
heuristics in general) has flourished, spawning an enormous variety of
algorithms, operators and representations.The history of science and
mathematics demonstrates that such proliferation is inevitable in a
growing field, but that in order to progress non-incrementally it is
periodically necessary to obtain a unifying perspective.
Existing EC/metaheuristic frameworks provide a certain level of
abstraction, but these are not generally sufficient to capture
higher-level or cross-cutting concerns such as the automatic design of
metaheuristics "in the large" (c.f. Dijkstra on software componentization).
The "Design Patterns" revolution in 1994 was successful in addressing
analogous issues in the software industry. The default level of
discourse among practitioners was consequently significantly increased,
and today "factory method" or "chain of responsibility" are software
engineers' lingua franca, immensely facilitating communication and
design of software systems.
The workshop organizers strongly believe that the EC/metaheuristics
community needs and deserves a corresponding breakthrough. The domain of
metaheuristics has good mathematical and conceptual foundations, so
nothing precludes the creation of a coherent and useful set of concepts
to help move metaheuristics up an abstraction level. For instance,
hyper-heuristics can be considered as the well-known composite pattern
as applied to metaheuristics. Framing recurring methodological and
algorithmic themes in terms of such Metaheuristic Design Patterns (MDP)
has been advocated in a recent lecture [1] and several papers [2,3];
similar desires have also been expressed elsewhere [4].
This workshop provides a forum for those interested in contributing to
the MDP vision and/or willing to demonstrate its usefulness in practical
and theoretical studies.
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Topics and Themes
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The workshop welcomes original submissions on all applications of design
patterns to metaheuristics, which include (but are not limited to) the
following topics and themes:
- Applications of existing design patterns (e.g. from [5]) to
metaheuristics. Some examples are given in [1,4] and on the Workshop
website.
- New metaheuristic design patterns: algorithms and methodologies that
might be expected to be widely applicable but which have not yet been
documented at the appropriate level of abstraction.
- Automation of metaheuristic design via patterns. There is a wealth of
pattern literature in the (Search-Based) Software Engineering community
related to software automation. Much of this is directly applicable to
metaheuristic design.
- Pattern languages for metaheuristics. See [4] for the definitive example.
Further details (and examples) are available at the Workshop website:
http://www.cs.stir.ac.uk/~jsw/metaheuristic-design-patterns/MDPWorkshop2014.htm
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References
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[1] Jerry Swan. Metaheuristic Design Patterns. Available at
http://www.cs.stir.ac.uk/~jsw/.
[2] Krzysztof Krawiec and Jerry Swan, Pattern-guided Genetic
Programming. GECCO 2013.
[3] John R. Woodward and Jerry Swan, The automatic generation of
mutation operators for Genetic Algorithms, GECCO 2012.
[4] Natalio Krasnogor. Handbook of Natural Computation, chapter "Memetic
Algorithms". Natural Computing. Springer Berlin / Heidelberg, 2009.
[5] Erich Gamma, Richard Helm, Ralph Johnson, and John Vlissides. Design
Patterns: Elements of Reusable Object-Oriented Software. Addison-Wesley
Boston, USA. 1995.
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Paper Submission
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Submitted papers should follow the ACM format, and should be between 2
and 4 pages in length.
Please see "GECCO 2014 information for authors" for further details.
However, note that the review process of the workshop is not
double-blind and hence, authors' information should appear in the paper.
All accepted papers will be presented at the workshop and appear in the
GECCO workshop volume.
Proceedings of the workshop will be published on CD-ROM, and distributed
at the conference.
Papers should be submitted by 28 March, 2014 in PDF format to:
[jerry.swan -at- cs.stir.ac.uk]
containing the subject line "Metaheuristic Design Patterns Workshop".
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Important Dates
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* Paper submission deadline: 28 March, 2014
* Notification of acceptance: April 15, 2014
* Camera-Ready Accepted Papers Due: April 25, 2014
* GECCO-2014: July 12-16, 2014
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Workshop Chairs
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Jerry Swan - University of Stirling, United Kingdom.
jsw –at- cs.stir.ac.uk
John Clark - University of York, United Kingdom.
john.clark -at- cs.york.ac.uk
Krzysztof Krawiec - Poznan University of Technology, Poland.
krawiec –at- cs.put.poznan.pl
Chris Simons - University of the West of England, United Kingdom.
chris.simons -at- uwe.ac.uk
John Woodward - University of Stirling, United Kingdom.
jrw –at- cs.stir.ac.uk
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The traditional apologies are made in the event of cross-posting.
For more details, please visit the workshop website at:
http://www.cs.stir.ac.uk/~jsw/metaheuristic-design-patterns/MDPWorkshop2014.htm
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GECCO is sponsored by the Association for Computing Machinery Special
Interest Group on Genetic and Evolutionary Computation (SIGEVO). SIG
Services: 2 Penn Plaza, Suite 701, New York, NY, 10121, USA,
1-800-342-6626 1-800-342-6626 (USA and Canada) or +212-626-0500 (Global).
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