A parallel multiple reference point approach ...
Type de document :
Article dans une revue scientifique
Titre :
A parallel multiple reference point approach for multi-objective optimization
Auteur(s) :
Figueira, José [Auteur]
Center for Management Studies, Instituto Superior Técnico [Porto Salvo] [CEG - IST]
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Liefooghe, Arnaud [Auteur correspondant]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Talbi, El-Ghazali [Auteur]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Wierzbicki, Andrzej [Auteur]
National Institute of Telecommunications [NIT]
Center for Management Studies, Instituto Superior Técnico [Porto Salvo] [CEG - IST]
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Liefooghe, Arnaud [Auteur correspondant]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Talbi, El-Ghazali [Auteur]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Wierzbicki, Andrzej [Auteur]
National Institute of Telecommunications [NIT]
Titre de la revue :
European Journal of Operational Research
Pagination :
390 - 400
Éditeur :
Elsevier
Date de publication :
2010
ISSN :
0377-2217
Mot(s)-clé(s) en anglais :
Multiple objective programming
Parallel computing
Multiple reference point approach
Evolutionary computations
Bi-objective flow-shop scheduling
Parallel computing
Multiple reference point approach
Evolutionary computations
Bi-objective flow-shop scheduling
Discipline(s) HAL :
Informatique [cs]/Recherche opérationnelle [cs.RO]
Informatique [cs]/Algorithme et structure de données [cs.DS]
Informatique [cs]/Algorithme et structure de données [cs.DS]
Résumé en anglais : [en]
This paper presents a multiple reference point approach for multi-objective optimization problems of discrete and combinatorial nature. When approximating the Pareto Frontier, multiple reference points can be used instead ...
Lire la suite >This paper presents a multiple reference point approach for multi-objective optimization problems of discrete and combinatorial nature. When approximating the Pareto Frontier, multiple reference points can be used instead of traditional techniques. These multiple reference points can easily be implemented in a parallel algorithmic framework. The reference points can be uniformly distributed within a region that covers the Pareto Frontier. An evolutionary algorithm is based on an achievement scalarizing function that does not impose any restrictions with respect to the location of the reference points in the objective space. Computational experiments are performed on a bi-objective flow-shop scheduling problem. Results, quality measures as well as a statistical analysis are reported in the paper.Lire moins >
Lire la suite >This paper presents a multiple reference point approach for multi-objective optimization problems of discrete and combinatorial nature. When approximating the Pareto Frontier, multiple reference points can be used instead of traditional techniques. These multiple reference points can easily be implemented in a parallel algorithmic framework. The reference points can be uniformly distributed within a region that covers the Pareto Frontier. An evolutionary algorithm is based on an achievement scalarizing function that does not impose any restrictions with respect to the location of the reference points in the objective space. Computational experiments are performed on a bi-objective flow-shop scheduling problem. Results, quality measures as well as a statistical analysis are reported in the paper.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Collections :
Source :
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