Metaheuristics for Multiobjective Optimisation

Metaheuristics for Multiobjective Optimisation

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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 qoptimal solutionq in favour of vector optimization notions dealing with qefficient solutionq and qefficient setq. To solve these challenging multiobjective problems, the metaheuristics community has put forward a number of techniques commonly referred to as multiobjective metaAs heuristics (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 numerous papers, books and speAs cial issues. Moreover, several conferences and workshops have been organised, often specialising in specific sub-areas such as multiobjective evolutionary opAs timisation. The main purpose of this volume is to provide an overview of the current state-of-the-art in the research field of MOMH. This overview is necessarAs ily non-exhaustive, and contains both methodological and problem-oriented contributions, and applications of both population-based and neighbourhoodAs based heuristics. This volume originated from the workshop on multiobjective metaheuristics that was organised at the Carre des Sciences in Paris on November 4-5, 2002. This meeting was a joint effort of two working groups: ED jME and PM20.Burke E.K., Smith A., Hybrid Evolutionary Techniques for the Maintenance Scheduling Problem, IEEE Transactions on Power Systems, Vol. ... Timetabling, European Journal 124 J. Dario Landa Silva, Edmund K. Burke, and Sanja Petrovic.

Title:Metaheuristics for Multiobjective Optimisation
Author: Xavier Gandibleux
Publisher:Springer Science & Business Media - 2004-01-14

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