Call for Papers:
Special Issue on
Evolutionary Computation in Combinatorial
Optimization
Evolutionary algorithms are metaheuristics, inspired by natural evolution
in a broader sense, that have often been shown to be effective for difficult
combinatorial optimization problems appearing in various industrial, economical,
and scientific domains. Prominent examples for such problems are network
design, packing, satisfiability, scheduling, timetabling, transportation,
traveling salesperson, and vehicle routing.
This special issue particularly welcomes theoretical and empirical contributions
investigating the key features of successful evolutionary algorithms for
combinatorial optimization problems, like e.g. choice and
properties of representations, variation operators, and constraint handling
techniques. Studies of hybrid approaches that combine ideas of evolutionary
algorithms with any other method, such as problem specific heuristics, enumeration
techniques, or linear programming, are also welcome. Furthermore, investigations
may include search space analyses and comparisons with other (possibly non-evolutionary)
optimization methods.
The Journal of Mathematical Modelling and Algorithms is a relatively new
journal published by Kluwer Academic Publishing since 2002. More information
about the journal can be found at
http://www.kluweronline.com/issn/1570-1166.
Editors of the special issue:
Jens Gottlieb, SAP AG, Germany
Emma Hart, Napier University, Edinburgh, UK
Martin Middendorf, University of Leipzig, Germany
Guenther Raidl, Vienna University of Technology, Austria
Colin Reeves, Coventry University, UK
Submission:
Your manuscript should be formatted according to the instructions listed
on the journal's web-page (http://www.kluweronline.com/issn/1570-1166).
Send a postscript or PDF file to ecco_jmma @ads.tuwien.ac.at
before May 1, 2003.