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An approach for the local exploration of ...
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Document type :
Autre communication scientifique (congrès sans actes - poster - séminaire...): Communication dans un congrès avec actes
DOI :
10.1109/TSMCB.2008.926329
Title :
An approach for the local exploration of discrete many objective optimization problems
Author(s) :
Cuate, Oliver [Auteur]
Centro de Investigacion y de Estudios Avanzados del Instituto Politécnico Nacional [CINVESTAV]
Derbel, Bilel [Auteur] refId
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Liefooghe, Arnaud [Auteur] refId
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Talbi, El-Ghazali [Auteur] refId
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Schütze, Oliver [Auteur]
Centro de Investigacion y de Estudios Avanzados del Instituto Politécnico Nacional [CINVESTAV]
Conference title :
9th International Conference on Evolutionary Multi-Criterion Optimization (EMO 2017)
City :
Münster
Country :
Allemagne
Start date of the conference :
2017-03-19
Publication date :
2017
English keyword(s) :
Many objective optimization
Multi-Criteria Decision Making
Discrete Optimization
Knapsack
Evolutionary Computation
HAL domain(s) :
Informatique [cs]/Recherche opérationnelle [cs.RO]
Mathématiques [math]/Optimisation et contrôle [math.OC]
English abstract : [en]
Multi-objective optimization problems with more than three objectives, which are also termed as many objective optimization problems , play an important role in the decision making process. For such problems, it is ...
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Multi-objective optimization problems with more than three objectives, which are also termed as many objective optimization problems , play an important role in the decision making process. For such problems, it is computationally expensive or even intractable to approximate the entire set of optimal solutions. An alternative is to compute a subset of optimal solutions based on the preferences of the decision maker. Commonly, interactive methods from the literature consider the user preferences at every iteration by means of weight vectors or reference points. Besides the fact that mathematical programming techniques only produce one solution at each iteration, they generally require first or second derivative information, that limits its applicability to certain problems. The approach proposed in this paper allows to steer the search into any direction in the objective space for optimization problems of discrete nature. This provides a more intuitive way to set the preferences, which represents a useful tool to explore the regions of interest of the decision maker. Numerical results on multi-objective multi-dimensional knapsack problem instances show the interest of the proposed approach.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Collections :
  • Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
Source :
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