Jounal of Heuristics special Issue
Forum 'Annonces' - Sujet créé le 2005-07-11
JOURNAL OF HEURISTICS
Special Issue on Advances in Metaheuristics for Multiobjective
Optimization
Guest Editors :
- Enrique Alba, University of Málaga - Spain
- El-Ghazali Talbi, University of Lille - France
- Antonio J. Nebro, University of Málaga - Spain
Real-world optimization problems have become increasingly complex,
forcing the development of solution procedures whose efficiency is
measured by their ability to find acceptable solutions within a
reasonable amount of computer time. To complicate matters, many
real-world situations lead to problems that have several conflicting
objectives, which typically cannot be optimized with a unique solution.
Hence, in multiobjective optimization, solution procedures are designed
to search for a good approximation of the Pareto optimal set. Measuring
the merit of a given approximation is itself a difficult problem and a
number of metrics continue to be developed and tested.
Metaheuristic optimization stands out as a promising approach to deal
with this difficult class of problems. Evolutionary algorithms have
become one of the most prominent class of metaheuristics for tackling
multiobjective optimization problems. However, other methodologies, such
as scatter search, tabu search, ant colonies, simulated annealing and
GRASP are gaining momentum.
Concerning the development of metaheuristics for multiobjective
optimization, there are two areas of special interest: (1) parallel
procedures and (2) hybrid implementations. We believe that focusing on
these developments may result in significant advances toward the
solution of complex multiobjective optimization problems found in
practice. The main goal of this special issue is to report on research
that produces state-of-the-art metaheuristic tools to solve non-trivial
multiobjective problems in a wide spectrum of applications. Of
particular interest are papers in the following topics:
- Numerical efficient metaheuristics for multiobjective optimization
(either population-based or trajectory based procedures)
- Real-world, complex or novel applications of multiobjective
optimization (e.g., telecommunications, bio-informatics, or large
NP-hard problem instances.)
- New search operators to deal with hard multiobjective optimization problems
- Improved or new representations for hard multiobjective optimization problems
- Comparative studies on different metaheuristics for complex
multiobjective problems
- Computational studies that demonstrate the efficiency of a
metaheuristic over a wide set of multiobjective problems
- Computational studies that report on best known results for
hard/interesting problems
- Parallel and distributed metaheuristics for multiobjective optimization
- Hybrid models of metaheuristic, constraint programming or mathematical
programming techniques
- Theory, metrics and advances to create an efficient multiobjective
algorithm
The proposed timeline for the special issue is as follows:
- Submission of papers: December 1st, 2005
- Notification of first review: April 15th, 2006
- Final manuscripts sent: July 1st, 2006
Authors should submit their manuscripts to the /Journal of Heuristics
Editorial Manager/ http://heur.edmgr.com Please, select "Special Issue -
Multiobjective" as the article type.
Prof. El-Ghazali TALBI
LIFL (USTL, CNRS, INRIA)
talbi@lifl.fr
http://www.lifl.fr/~talbi
Special Issue on Advances in Metaheuristics for Multiobjective
Optimization
Guest Editors :
- Enrique Alba, University of Málaga - Spain
- El-Ghazali Talbi, University of Lille - France
- Antonio J. Nebro, University of Málaga - Spain
Real-world optimization problems have become increasingly complex,
forcing the development of solution procedures whose efficiency is
measured by their ability to find acceptable solutions within a
reasonable amount of computer time. To complicate matters, many
real-world situations lead to problems that have several conflicting
objectives, which typically cannot be optimized with a unique solution.
Hence, in multiobjective optimization, solution procedures are designed
to search for a good approximation of the Pareto optimal set. Measuring
the merit of a given approximation is itself a difficult problem and a
number of metrics continue to be developed and tested.
Metaheuristic optimization stands out as a promising approach to deal
with this difficult class of problems. Evolutionary algorithms have
become one of the most prominent class of metaheuristics for tackling
multiobjective optimization problems. However, other methodologies, such
as scatter search, tabu search, ant colonies, simulated annealing and
GRASP are gaining momentum.
Concerning the development of metaheuristics for multiobjective
optimization, there are two areas of special interest: (1) parallel
procedures and (2) hybrid implementations. We believe that focusing on
these developments may result in significant advances toward the
solution of complex multiobjective optimization problems found in
practice. The main goal of this special issue is to report on research
that produces state-of-the-art metaheuristic tools to solve non-trivial
multiobjective problems in a wide spectrum of applications. Of
particular interest are papers in the following topics:
- Numerical efficient metaheuristics for multiobjective optimization
(either population-based or trajectory based procedures)
- Real-world, complex or novel applications of multiobjective
optimization (e.g., telecommunications, bio-informatics, or large
NP-hard problem instances.)
- New search operators to deal with hard multiobjective optimization problems
- Improved or new representations for hard multiobjective optimization problems
- Comparative studies on different metaheuristics for complex
multiobjective problems
- Computational studies that demonstrate the efficiency of a
metaheuristic over a wide set of multiobjective problems
- Computational studies that report on best known results for
hard/interesting problems
- Parallel and distributed metaheuristics for multiobjective optimization
- Hybrid models of metaheuristic, constraint programming or mathematical
programming techniques
- Theory, metrics and advances to create an efficient multiobjective
algorithm
The proposed timeline for the special issue is as follows:
- Submission of papers: December 1st, 2005
- Notification of first review: April 15th, 2006
- Final manuscripts sent: July 1st, 2006
Authors should submit their manuscripts to the /Journal of Heuristics
Editorial Manager/ http://heur.edmgr.com Please, select "Special Issue -
Multiobjective" as the article type.
Prof. El-Ghazali TALBI
LIFL (USTL, CNRS, INRIA)
talbi@lifl.fr
http://www.lifl.fr/~talbi