International audienceMany real-life applications lead to the definition of robust optimization problems where the objective function is a black box. This may be due, for example, to the fact that the objective function is evaluated through computer simulations, and that some parameters are uncertain. When this is the case, existing algorithms for optimization are not able to provide good-quality solutions in general. We propose a heuristic algorithm for solving black box robust optimization problems based on the minimax formulation of the problem.We also apply this algorithm for the solution of a wing shape optimization where the objective function is a computationally expensive black box. Preliminary computational experiments are reported
AbstractAdvanced engineering systems, like aircraft, are defined by tens or even hundreds of design ...
Design of complex physical systems most often relies on numerical simulations that may be extremely ...
In the robust optimization field, the robustness of the objective function emphasizes an insensitive...
International audienceMany real-life applications lead to the definition of robust optimization prob...
Optimization is becoming an important field of research. The availability of more powerful computati...
Robust optimization is a valuable alternative to stochastic programming, where all underlying probab...
International audienceThis paper focuses on a robust optimization of an aircraft preliminary design ...
We propose a novel robust optimization technique, which is applicable to nonconvex and simulation-ba...
A robust optimization method is developed to overcome point-optimization at the sampled design point...
In this paper, the aerodynamic shape optimization problems with uncertain operating conditions have ...
In this paper, the aerodynamic shape optimization problems with uncertain operating conditions has b...
The paper presents a simple memetic algorithm for the solution of min-max problems. It will be shown...
In real-world applications of optimization, optimal solutions are often of limited value, because di...
We propose a new robust optimization method for problems with objective functions that may be comput...
In the world of vehicle structure optimization the goal is to find car components that are, for exam...
AbstractAdvanced engineering systems, like aircraft, are defined by tens or even hundreds of design ...
Design of complex physical systems most often relies on numerical simulations that may be extremely ...
In the robust optimization field, the robustness of the objective function emphasizes an insensitive...
International audienceMany real-life applications lead to the definition of robust optimization prob...
Optimization is becoming an important field of research. The availability of more powerful computati...
Robust optimization is a valuable alternative to stochastic programming, where all underlying probab...
International audienceThis paper focuses on a robust optimization of an aircraft preliminary design ...
We propose a novel robust optimization technique, which is applicable to nonconvex and simulation-ba...
A robust optimization method is developed to overcome point-optimization at the sampled design point...
In this paper, the aerodynamic shape optimization problems with uncertain operating conditions have ...
In this paper, the aerodynamic shape optimization problems with uncertain operating conditions has b...
The paper presents a simple memetic algorithm for the solution of min-max problems. It will be shown...
In real-world applications of optimization, optimal solutions are often of limited value, because di...
We propose a new robust optimization method for problems with objective functions that may be comput...
In the world of vehicle structure optimization the goal is to find car components that are, for exam...
AbstractAdvanced engineering systems, like aircraft, are defined by tens or even hundreds of design ...
Design of complex physical systems most often relies on numerical simulations that may be extremely ...
In the robust optimization field, the robustness of the objective function emphasizes an insensitive...