β-Robustness approach for fuzzy multi-objective ...
Type de document :
Communication dans un congrès avec actes
Titre :
β-Robustness approach for fuzzy multi-objective problems
Auteur(s) :
Bahri, Oumayma [Auteur]
Laboratoire de Recherche Opérationnelle de Décision et de Contrôle de Processus [LARODEC]
Talbi, El-Ghazali [Auteur]
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Benamor, Nahla [Auteur]
Laboratoire de Recherche Opérationnelle de Décision et de Contrôle de Processus [LARODEC]
Laboratoire de Recherche Opérationnelle de Décision et de Contrôle de Processus [LARODEC]
Talbi, El-Ghazali [Auteur]

Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Benamor, Nahla [Auteur]
Laboratoire de Recherche Opérationnelle de Décision et de Contrôle de Processus [LARODEC]
Titre de la manifestation scientifique :
IPMU‘2016 - 16th Int. Conference On Information Processing and Management on Uncertainty in Knowledge-based Systems
Ville :
Eindhoeven
Pays :
Pays-Bas
Date de début de la manifestation scientifique :
2016
Discipline(s) HAL :
Informatique [cs]/Intelligence artificielle [cs.AI]
Résumé en anglais : [en]
The paper addresses the robustness of multi-objective optimization problems with fuzzy data, expressed via triangular fuzzy numbers. To this end, we introduced a new robustness approach able to deal with fuzziness in the ...
Lire la suite >The paper addresses the robustness of multi-objective optimization problems with fuzzy data, expressed via triangular fuzzy numbers. To this end, we introduced a new robustness approach able to deal with fuzziness in the multi-objective context. The proposed approach is composed of two main contributions: First, new concepts of β-robustness are proposed to analyze fuzziness propagation to the multiple objectives. Second, an extension of our previously proposed evolutionary algorithms is suggested for integrating robustness. These proposals are illustrated on a multi-objective vehicle routing problem with fuzzy customer demands. The experimental results on different instances show the efficiency of the proposed approach.Lire moins >
Lire la suite >The paper addresses the robustness of multi-objective optimization problems with fuzzy data, expressed via triangular fuzzy numbers. To this end, we introduced a new robustness approach able to deal with fuzziness in the multi-objective context. The proposed approach is composed of two main contributions: First, new concepts of β-robustness are proposed to analyze fuzziness propagation to the multiple objectives. Second, an extension of our previously proposed evolutionary algorithms is suggested for integrating robustness. These proposals are illustrated on a multi-objective vehicle routing problem with fuzzy customer demands. The experimental results on different instances show the efficiency of the proposed approach.Lire moins >
Langue :
Anglais
Comité de lecture :
Oui
Audience :
Internationale
Vulgarisation :
Non
Collections :
Source :