Multidisciplinary and multiobjective optimization: Comparison of several methods

Philippe Dépincé (1) , Benoît Guédas (1) , Jérôme Picard (1)

1 IRCCyN - Institut de Recherche en Communications et en Cybernétique de Nantes

Engineering design of complex systems is a decision making process that aims at choosing from among a set of options that implies an irrevocable allocation of resources. It is inherently a multidisciplinary and multi-objective process. The paper describes some classical multidisciplinary optimization (MDO) methods with their advantages and drawbacks. Some new approaches combining genetic algorithms (MOGA) and collaborative optimization (CO) are presented. They allow to: 1) increase the convergence rate when a design problem can be broken up regarding design variables, and 2) provide an optimal set of design variables in case of multi-level multi-objective design problem.

Mots clés: Multidisciplinary Design Optimization; Bi-Level Collaborative Optimization; Genetic Algorithm; Pareto Frontier

Domaines: Autre

Philippe Dépincé, Benoît Guédas, Jérôme Picard. Multidisciplinary and multiobjective optimization: Comparison of several methods. 7th World Congress on Structural and Multidisciplinary Optimization, May 2007, Seoul, South Korea. ⟨hal-00449605⟩