6 papers
Efficient multidisciplinary design via Bayesian optimization
Nathalie Bartoli, Thierry Lefebvre, Rémi Lafage +3
This study introduces SEGOMOE, a Bayesian optimization tool for optimizing complex, computationally expensive systems, especially in aeronautics. It efficiently handles mixed desig…
Transfer Learning in Bayesian Optimization for Aircraft Design
Ali Tfaily, Youssef Diouane, Nathalie Bartoli +1
The use of transfer learning within Bayesian optimization addresses the disadvantages of the so-called \textit{cold start} problem by using source data to aid in the optimization o…
Multi-fidelity approaches for general constrained Bayesian optimization with application to aircraft design
Oihan Cordelier, Youssef Diouane, Nathalie Bartoli +1
Aircraft design relies heavily on solving challenging and computationally expensive Multidisciplinary Design Optimization problems. In this context, there has been growing interest…
Modeling Hierarchical Spaces: A Review and Unified Framework for Surrogate-Based Architecture Design
Paul Saves, Edward Hallé-Hannan, Jasper Bussemaker +2
Simulation-based problems involving mixed-variable inputs frequently feature domains that are hierarchical, conditional, heterogeneous, or tree-structured. These characteristics po…
System-of-systems Modeling and Optimization: An Integrated Framework for Intermodal Mobility
Paul Saves, Jasper Bussemaker, Rémi Lafage +4
For developing innovative systems architectures, modeling and optimization techniques have been central to frame the architecting process and define the optimization and modeling p…
Surrogate-based optimization of system architectures subject to hidden constraints
Jasper Bussemaker, Paul Saves, Nathalie Bartoli +2
The exploration of novel architectures requires physics-based simulation due to a lack of prior experience to start from, which introduces two specific challenges for optimization…