[Computational-biology] CFP : IDEAL'2007 workshop on Evolutionary Algorithms for Industrial Design Optimisation

A EKART via comp-bio%40net.bio.net (by ekarta from aston.ac.uk)
Tue Sep 18 16:06:03 EST 2007


Apologies for multiple postings

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SUBMISSION DEADLINE EXTENDED TO 30 September, 2007.
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Workshop on Evolutionary Algorithms for Industrial Design Optimisation

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In association with the 8th International Conference on
Intelligent Data Engineering and Automated Learning IDEAL'07,
16-19 December 2007, Birmingham, UK
http://events.cs.bham.ac.uk/ideal07/



******************** CALL FOR PAPERS ***********************************


The efficient running of a large variety of business processes depends
on the optimal realisation of a core capability - design. To highlight a 
few, it could be transportation scheduling for the optimal performance of 
a complex supply chain, layout of a warehouse for the optimal use of
resources, aerodynamics of an aero-engine component to optimise its
efficiency, optimally modelling a physical process with unknown dynamics
from recorded data. So critical are these tasks that a large portion of
industrial research budget is spent on design optimisation. However, the
'hard' problems continue to pose huge challenges. Although the application
domains vary widely, the underlying characteristics of such problems are
fairly generic - a large number of design parameters, many and often
conflicting objectives, noisiness and uncertainty in data, being some of
the most important ones. The complex nature of the objective function
landscape of these problems limits the applicability of traditional
incremental search algorithms (e.g. hill climbing or gradient based
techniques).

Evolutionary Algorithms (EA) are nature-inspired population-based search
algorithms that have received significant attention since their
introduction in the 1970s. The most notable EAs developed initially such
as Genetic Algorithm (GA), Evolutionary Strategy (ES) and Evolutionary
Programming (EP) can be exploited in industrial design optimisation
problems. Genetic Programming (GP) is a relatively recent, and
potentially more powerful, technique to evolve novel, robust solutions
to hard optimisation problems mainly due to its capability to represent
solutions as computer programs. This workshop aims to close the loop
between the state-of-the-art EA research and the real-world challenges
faced by practitioners of design optimisation. The specific goals of
this meeting include, but are not limited to, the following:

* Present the latest applications of EA for industrial design
optimisation.

* Present and discuss the major EA theoretical breakthroughs with
respect to the specific challenges of industrial design optimisation.

* Identify problem categories which are more (or less) amenable for an
EA-based solution.

* Explore their unique advantages and disadvantages for such problems.

* Understand if EA excite industrial design optimisation experts. If
not, why not and can anything be done about it? If so, where and how its
contributions can be extended?


*** Please email original articles in pdf format to BOTH organizing
committee members (details below).

Papers should not exceed 10 pages and should comply with IDEAL 2007
formatting guidelines, available at
http://events.cs.bham.ac.uk/ideal07/submission.php.

All papers will be peer-reviewed.

*** IMPORTANT DATES ***

Paper submission:  	          30 September 2007
(*** DEADLINE EXTENDED ***)
Notification of acceptance:       30 October 2007
Submission of camera-ready paper: 10 November 2007


*** ORGANIZING COMMITTEE ***

Dr. Partha Dutta
Strategic Research Centre
Rolls-Royce plc.
PO Box 31
Derby DE24 3JS
United Kingdom.
Email: partha.dutta from rolls-royce.com


Dr. Aniko Ekart
Knowledge Engineering Research Group
School of Engineering and Applied Science
Aston University
Aston Triangle
Birmingham B47ET.
United Kingdom
Email: ekarta from aston.ac.uk



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