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On the Combined Impact of Population Size ...
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Document type :
Communication dans un congrès avec actes
DOI :
10.1007/978-3-030-43680-3_9
Title :
On the Combined Impact of Population Size and Sub-problem Selection in MOEA/D
Author(s) :
Pruvost, Geoffrey [Auteur]
Optimisation de grande taille et calcul large échelle [BONUS]
Derbel, Bilel [Auteur] refId
Optimisation de grande taille et calcul large échelle [BONUS]
Liefooghe, Arnaud [Auteur] refId
Optimisation de grande taille et calcul large échelle [BONUS]
Li, Ke [Auteur]
University of Exeter
Zhang, Qingfu [Auteur]
City University of Hong Kong [Hong Kong] [CUHK]
Conference title :
EvoCOP 2021 - 21st European Conference on Evolutionary Computation in Combinatorial Optimization
City :
Seville
Country :
Espagne
Start date of the conference :
2020-04-15
HAL domain(s) :
Informatique [cs]/Intelligence artificielle [cs.AI]
English abstract : [en]
This paper intends to understand and to improve the working principle of decomposition-based multi-objective evolutionary algorithms. We review the design of the well-established Moea/d framework to support the smooth ...
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This paper intends to understand and to improve the working principle of decomposition-based multi-objective evolutionary algorithms. We review the design of the well-established Moea/d framework to support the smooth integration of different strategies for sub-problem selection, while emphasizing the role of the population size and of the number of offspring created at each generation. By conducting a comprehensive empirical analysis on a wide range of multi-and many-objective combinatorial NK landscapes, we provide new insights into the combined effect of those parameters on the anytime performance of the underlying search process. In particular, we show that even a simple random strategy selecting sub-problems at random outperforms existing sophisticated strategies. We also study the sensitivity of such strategies with respect to the ruggedness and the objective space dimension of the target problem.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
ANR Project :
Optimisation Multiobjectif Big
Collections :
  • Centre de Recherche en Informatique, Signal et Automatique de Lille (CRIStAL) - UMR 9189
Source :
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