Metaheuristics for Multiobjective Optimisation
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Springer Berlin Heidelberg New York Hong Kong London Milan Paris Tokyo
Xavier Gandibleux Marc Sevaux Kenneth Sorensen Vincent T'kindt (Eds.)
Metaheuristics for Multiobjective Optimisation
Springer
Editors Prof. Kenneth Sörensen Sorensen University of Antwerp Faculty of Applied Economics Prinsstraat 13 2000 Antwerp Belgium
Prof. Xavier Gandibleux of Valenciennes University ofValenciennes LAMIH- ROI UMR CNRS 8530 Campus Le Mont Rouy Houy 59313 Valenciennes Cedex 9 France Prof. Marc Sevaux University ofValenciennes of Valenciennes LAMIH- SP UMR CNRS 8530 Campus Le Mont Rouy Houy 59313 Valenciennes Cedex 9 France
Prof. Vincent T'kindt University of Tours Department of Computer Science Poly tech' Tours Polytech' 64 avenue Jean Portalis 37200 Tours France
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ISSN 0075-8442 ISBN 978-3-540-20637-8 ISBN 978-3-642-17144-4 (eBook) DOI 10.1007/978-3-642-17144-4
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Preface
A large number of real-life optimisation problems can only be realistically modelled with several~often conflicting~objectives. This fact requires us to abandon the concept of "optimal solution" in favour of vector optimization notions dealing with "efficient solution" and "efficient set". To solve these challenging multiobjective problems, the metaheuristics community has put forward a number of techniques commonly referred to as multiobjective metaheuristics (MOMH). By its very nature, the field of MOMH covers a large research area both in terms of the types of problems solved and the techniques used to solve these problems. Its theoretical interest and practical applicability have attracted a large number of researchers and generated nu
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