A software framework based on a conceptual ...
Document type :
Article dans une revue scientifique: Article original
Title :
A software framework based on a conceptual unified model for evolutionary multiobjective optimization: ParadisEO-MOEO
Author(s) :
Liefooghe, Arnaud [Auteur]
Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Jourdan, Laetitia [Auteur]
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]

Laboratoire d'Informatique Fondamentale de Lille [LIFL]
Parallel Cooperative Multi-criteria Optimization [DOLPHIN]
Jourdan, Laetitia [Auteur]

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]
Journal title :
European Journal of Operational Research
Pages :
104-112
Publisher :
Elsevier
Publication date :
2011
ISSN :
0377-2217
English keyword(s) :
Multiple objective programming
Evolutionary algorithms
Conceptual unified model
Algorithm design and implementation
Software framework
Evolutionary algorithms
Conceptual unified model
Algorithm design and implementation
Software framework
HAL domain(s) :
Computer Science [cs]/Operations Research [math.OC]
English abstract : [en]
This paper presents a general-purpose software framework dedicated to the design and the implementation of evolutionary multiobjective optimization techniques: ParadisEO-MOEO. A concise overview of evolutionary algorithms ...
Show more >This paper presents a general-purpose software framework dedicated to the design and the implementation of evolutionary multiobjective optimization techniques: ParadisEO-MOEO. A concise overview of evolutionary algorithms for multiobjective optimization is given. A substantial number of methods has been proposed so far, and an attempt of conceptually unifying existing approaches is presented here. Based on a fine-grained decomposition and following the main issues of fitness assignment, diversity preservation and elitism, a conceptual model is proposed and is validated by regarding a number of state-of-the-art algorithms as simple variants of the same structure. This model is then incorporated into the ParadisEO-MOEO software framework. This framework has proven its validity and high flexibility by enabling the resolution of many academic, real-world and hard multiobjective optimization problems.Show less >
Show more >This paper presents a general-purpose software framework dedicated to the design and the implementation of evolutionary multiobjective optimization techniques: ParadisEO-MOEO. A concise overview of evolutionary algorithms for multiobjective optimization is given. A substantial number of methods has been proposed so far, and an attempt of conceptually unifying existing approaches is presented here. Based on a fine-grained decomposition and following the main issues of fitness assignment, diversity preservation and elitism, a conceptual model is proposed and is validated by regarding a number of state-of-the-art algorithms as simple variants of the same structure. This model is then incorporated into the ParadisEO-MOEO software framework. This framework has proven its validity and high flexibility by enabling the resolution of many academic, real-world and hard multiobjective optimization problems.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
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