A parallel multiple reference point approach ...
Document type :
Compte-rendu et recension critique d'ouvrage
Title :
A parallel multiple reference point approach for multi-objective optimization
Author(s) :
Figueira, José [Auteur]
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Center for Management Studies, Instituto Superior Técnico [Porto Salvo] [CEG - IST]
Liefooghe, Arnaud [Auteur correspondant]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Talbi, El-Ghazali [Auteur]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Wierzbicki, Andrzej [Auteur]
National Institute of Telecommunications [NIT]
Laboratoire d'analyse et modélisation de systèmes pour l'aide à la décision [LAMSADE]
Center for Management Studies, Instituto Superior Técnico [Porto Salvo] [CEG - IST]
Liefooghe, Arnaud [Auteur correspondant]

Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Talbi, El-Ghazali [Auteur]

Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Wierzbicki, Andrzej [Auteur]
National Institute of Telecommunications [NIT]
Journal title :
European Journal of Operational Research
Pages :
390 - 400
Publisher :
Elsevier
Publication date :
2010
ISSN :
0377-2217
English keyword(s) :
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
HAL domain(s) :
Computer Science [cs]/Operations Research [math.OC]
Informatique [cs]/Algorithme et structure de données [cs.DS]
Informatique [cs]/Algorithme et structure de données [cs.DS]
English abstract : [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 ...
Show more >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.Show less >
Show more >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.Show less >
Language :
Anglais
Popular science :
Non
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