[Opt-net] Extended Deadline: Special Issue on Heuristic Search Methods for Large Scale Optimization Problems in Industry, Evolutionary Computation Journal

[Frank Neumann]

Special Issue on
     Heuristic Search Methods for Large Scale Optimization Problems in 
Industry

          Evolutionary Computation Journal, MIT Press
http://ecj.lri.fr/

              EXTENDED DEADLINE: August 31, 2010.

Guest Editors:
Andreas Ernst, CSIRO Mathematical and Information Science, 
andreas.ernst at csiro.au
Zbigniew Michalewicz, University of Adelaide, 
zbigniew.michalewicz at adelaide.edu.au
Frank Neumann, Max Planck Institute for Informatics, fne at mpi-inf.mpg.de

Description:
This special issue aims to provide a forum for researchers working on 
large applied optimization problems arising in industry. Such problems 
often defy solution by exact approaches such as integer and constraint 
programming. Particular challenges of large applied problems include the 
presence of complex objectives containing a mixture of real costs and 
soft constraints which can be time consuming to evaluate. In addition 
the search space of problems is often so large that traversing it with 
neighbourhood-move, crossover or mutation operators can take too long to 
allow effective exploration. This special issue solicits novel 
high-quality contributions on heuristic methods for large applied 
optimization problems that have been used in practice. While papers on 
any aspect of solving large scale optimization problems in industry are 
welcome, of special interest are submissions on:

-Scheduling/planning problems solved for particular organizations
-Novel methods for exploring very large search spaces
-Decomposition and parallel computing techniques for solving large 
optimization problems
-Hybrid heuristics for real world optimization problems
-Methods for dealing with large data sets in formulating and solving 
large optimization problems, including issues around data consistency 
and completeness.
-Case studies of successful (or unsuccessful) implementations of large 
scale heuristic optimization algorithms in a business and lessons 
learned from these.

Authors are encouraged to make available (de-identified) versions of 
some of their real world data sets to support the development of more 
sophisticated methods to deal with some of these challenging problems.
This special issue will not consider the solution of large abstract 
problems (eg classical VRP or job shop scheduling problems) nor papers 
that only test algorithms on randomly generated data sets. Authors are 
invited to submit original work on topics relevant for this special 
issue. The publication of the special issue is tentatively scheduled for 
Summer 2011.

Submission:
Authors should submit their manuscripts to the Evolutionary Computation
Editorial Manager at http://ecj.lri.fr/.
When submitting a paper, please send at the same time also an
email to Frank Neumann (fne at mpi-inf.mpg.de) and a copy to ecj at lri.fr 
mentioning the special issue, the
paper title, and author list to inform about the submission.