Two-Level Algorithm Combining Bayesian Optimization and Swarm Intelligence for Variable-Size Optimal Layout Problems - ONERA - Office national d'études et de recherches aérospatiales Accéder directement au contenu
Communication Dans Un Congrès Année : 2023

Two-Level Algorithm Combining Bayesian Optimization and Swarm Intelligence for Variable-Size Optimal Layout Problems

Résumé

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.
Fichier principal
Vignette du fichier
3583133.3596997-1.pdf (1.1 Mo) Télécharger le fichier
Origine Fichiers produits par l'(les) auteur(s)

Dates et versions

hal-04381343 , version 1 (27-06-2024)

Licence

Identifiants

Citer

Juliette Gamot, Mathieu Balesdent, Arnault Tremolet, Romain Wuilbercq, Nouredine Melab, et al.. Two-Level Algorithm Combining Bayesian Optimization and Swarm Intelligence for Variable-Size Optimal Layout Problems. GECCO '23 Companion: Companion Conference on Genetic and Evolutionary Computation, Jul 2023, Lisbonne, Portugal. pp.139-142, ⟨10.1145/3583133.3596997⟩. ⟨hal-04381343⟩
10 Consultations
0 Téléchargements

Altmetric

Partager

Gmail Mastodon Facebook X LinkedIn More