Two-Level Algorithm Combining Bayesian ...
Document type :
Communication dans un congrès avec actes
DOI :
Title :
Two-Level Algorithm Combining Bayesian Optimization and Swarm Intelligence for Variable-Size Optimal Layout Problems
Author(s) :
Gamot, Juliette [Auteur]
DTIS, ONERA, Université Paris Saclay [Palaiseau]
Inria Lille - Nord Europe
Balesdent, Mathieu [Auteur]
DTIS, ONERA, Université Paris Saclay [Palaiseau]
Tremolet, Arnault [Auteur]
DTIS, ONERA, Université Paris Saclay [Palaiseau]
Wuilbercq, Romain [Auteur]
DTIS, ONERA, Université Paris Saclay [Palaiseau]
Melab, Nouredine [Auteur]
Optimisation de grande taille et calcul large échelle [BONUS]
Talbi, El-Ghazali [Auteur]
Optimisation de grande taille et calcul large échelle [BONUS]
Université de Lille
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Inria Lille - Nord Europe
DTIS, ONERA, Université Paris Saclay [Palaiseau]
Inria Lille - Nord Europe
Balesdent, Mathieu [Auteur]
DTIS, ONERA, Université Paris Saclay [Palaiseau]
Tremolet, Arnault [Auteur]
DTIS, ONERA, Université Paris Saclay [Palaiseau]
Wuilbercq, Romain [Auteur]
DTIS, ONERA, Université Paris Saclay [Palaiseau]
Melab, Nouredine [Auteur]
Optimisation de grande taille et calcul large échelle [BONUS]
Talbi, El-Ghazali [Auteur]
Optimisation de grande taille et calcul large échelle [BONUS]
Université de Lille
Centre de Recherche en Informatique, Signal et Automatique de Lille - UMR 9189 [CRIStAL]
Inria Lille - Nord Europe
Conference title :
GECCO '23 Companion: Companion Conference on Genetic and Evolutionary Computation
City :
Lisbonne
Country :
Portugal
Start date of the conference :
2023-07-15
Publisher :
ACM
Publication date :
2023-07-24
Keyword(s) :
optimisation bayésienne
intelligence en essaim
optimisation multi-échelle
intelligence en essaim
optimisation multi-échelle
English keyword(s) :
bayesian optimization
swarm intelligence
multilevel optimization
swarm intelligence
multilevel optimization
HAL domain(s) :
Informatique [cs]
Sciences de l'ingénieur [physics]
Sciences de l'ingénieur [physics]
English abstract : [en]
The design process of complex engineering systems may involve problems in which the number and type of design variables and constraints vary throughout the optimization process based on the values of dimensional variables. ...
Show more >The design process of complex engineering systems may involve problems in which the number and type of design variables and constraints vary throughout the optimization process based on the values of dimensional variables. This category of problems is called Variable-Size Design Space optimization. A well-known application is the optimal layout problem which requires to place a variable number of components into a container. The dual objective is here to optimize the list of components in addition to their placements within the container. In this paper, a two-level algorithm is described to solve the aforementioned optimal layout problems. This algorithm combines the strength of a Swarm Intelligence algorithm based on a virtual-force system and a discrete Bayesian Optimization algorithm purposely adapted to tackle the dimensional aspect of this problem. The implementation of the two-level algorithm is discussed and the proposed approach is applied to the layout optimization of a satellite module. The performance of the algorithm is then analyzed with respect to several occupation rates of the system. This approach is also compared with a Hidden-Genes Genetic Algorithm.Show less >
Show more >The design process of complex engineering systems may involve problems in which the number and type of design variables and constraints vary throughout the optimization process based on the values of dimensional variables. This category of problems is called Variable-Size Design Space optimization. A well-known application is the optimal layout problem which requires to place a variable number of components into a container. The dual objective is here to optimize the list of components in addition to their placements within the container. In this paper, a two-level algorithm is described to solve the aforementioned optimal layout problems. This algorithm combines the strength of a Swarm Intelligence algorithm based on a virtual-force system and a discrete Bayesian Optimization algorithm purposely adapted to tackle the dimensional aspect of this problem. The implementation of the two-level algorithm is discussed and the proposed approach is applied to the layout optimization of a satellite module. The performance of the algorithm is then analyzed with respect to several occupation rates of the system. This approach is also compared with a Hidden-Genes Genetic Algorithm.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
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