Multiobjective Design Optimization using Nash Games - Inria - Institut national de recherche en sciences et technologies du numérique Accéder directement au contenu
Chapitre D'ouvrage Année : 2014

Multiobjective Design Optimization using Nash Games

Résumé

In the area of pure numerical simulation of multidisciplinary coupled systems, the computational cost to evaluate a configuration may be very high. A fortiori, in multi- disciplinary optimization, one is led to evaluate a number of different configurations to iterate on the design parameters. This observation motivates the search for the most in- novative and computationally efficient approaches in all the sectors of the computational chain : at the level of the solvers (using a hierarchy of physical models), the meshes and geometrical parameterizations for shape, or shape deformation, the implementation (on a sequential or parallel architecture; grid computing), and the optimizers (deterministic or semi-stochastic, or hybrid; synchronous, or asynchronous). In the present approach, we concentrate on situations typically involving a small number of disciplines assumed to be strongly antagonistic, and a relatively moderate number of related objective functions. However, our objective functions are functionals, that is, PDE-constrained, and thus costly to evaluate. The aerodynamic and structural optimization of an aircraft configuration is a prototype of such a context, when these disciplines have been reduced to a few major objectives. This is the case when, implicitly, many subsystems are taken into account by local optimizations. Our developments are focused on the question of approximating the Pareto set in cases of strongly-conflicting disciplines. For this purpose, a general computational technique is proposed, guided by a form of sensitivity analysis, with the additional objective to be more economical than standard evolutionary approaches.
Fichier principal
Vignette du fichier
ddh-chapter-3.pdf (1.9 Mo) Télécharger le fichier
Origine : Fichiers éditeurs autorisés sur une archive ouverte
Loading...

Dates et versions

hal-00923584 , version 1 (03-01-2014)

Identifiants

  • HAL Id : hal-00923584 , version 1

Citer

Jean-Antoine Desideri, Régis Duvigneau, Abderrahmane Habbal. Multiobjective Design Optimization using Nash Games. Massimiliano Vasile and Victor M. Becerra. Computational Intelligence in the Aerospace Sciences, American Institute of Aeronautics and Astronautics (AIAA), 2014, Progress in Astronautics and Aeronautics, 978-1-62410-260-8. ⟨hal-00923584⟩
611 Consultations
1078 Téléchargements

Partager

Gmail Facebook X LinkedIn More