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Meta-heuristics for multi-objective optimisation (2004) 249
Meta-heuristics for multi-objective optimisation
Xavier Gandibleux 1, Marc Sevaux 2, Kenneth Sörensen 3, Vincent T'Kindt 4
For the MOMH collaboration(s)
(2004)

The success of metaheuristics on hard single-objective optimization problems is well recognized today. However, many real-life problems require taking into account several conflicting points of view corresponding to multiple objectives. The use of metaheuristic optimization techniques for multi-objective problems is the subject of this volume. The book includes selected surveys, tutorials and state-of-the-art research papers in this field, which were first presented at a free workshop jointly organized by the French working group on Multi-objective Mathematical Programming (PM2O) and the EURO working group on Metaheuristics in December 2002. It is the first book which considers both various metaheuristics and various kind of problems (e.g. combinatorial problems, real situations, non-linear problems) applied to multiple objective optimization. Metaheuristics used include: genetic algorithms, ant colony optimization, simulated annealing, scatter search, etc. Problems concern timetabling, vehicle routing, and more. Methodological aspects, such as quality evaluation, are also covered
1:  Laboratoire d'Informatique de Nantes Atlantique (LINA)
CNRS : FRE2729 – Université de Nantes – École Nationale Supérieure des Mines - Nantes
2:  Laboratoire d'Electronique des Systèmes TEmps Réel (LESTER)
CNRS : FRE2734 – Université de Bretagne Sud
3:  Faculteit Toegepaste Economische Wetenschappen (TEW)
University of Antwerp
4:  Laboratoire d'Informatique de l'Université de Tours (LI)
Ministère de l'Enseignement Supérieur et de la Recherche Scientifique – Université François Rabelais - Tours : EA2101
Lab-STICC_UBS_CACS_MOCS
Mathematics/Optimization and Control
Metaheuristics – Multicriteria Optimization – Multiobjective – Operations Research – Optimization