125 citations · 263 across the 17 of their papers we have counts for
8 papers · 1 filter
Adaptive direct search algorithms for constrained optimization
Charles Audet, Théo Denorme, Youssef Diouane +2
Two families of directional direct search methods have emerged in derivative-free and blackbox optimization (DFO and BBO), each based on distinct principles: Mesh Adaptive Direct S…
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…
CatMADS: Mesh Adaptive Direct Search for constrained blackbox optimization with categorical variables
Charles Audet, Youssef Diouane, Edward Hallé-Hannan +2
Solving optimization problems in which functions are blackboxes and variables involve different types poses significant theoretical and algorithmic challenges. Nevertheless, such s…
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…
Multi-objective Bayesian Optimization With Mixed-categorical Design Variables for Expensive-to-evaluate Aeronautical Applications
Nathalie Bartoli, Thierry Lefebvre, Rémi Lafage +8
This work aims at developing new methodologies to optimize computational costly complex systems (e.g., aeronautical engineering systems). The proposed surrogate-based method (often…
Bayesian optimization for mixed variables using an adaptive dimension reduction process: applications to aircraft design
Paul Saves, Nathalie Bartoli, Youssef Diouane +5
Multidisciplinary design optimization methods aim at adapting numerical optimization techniques to the design of engineering systems involving multiple disciplines. In this context…
Regularized infill criteria for multi-objective Bayesian optimization with application to aircraft design
Robin Grapin, Youssef Diouane, Joseph Morlier +4
Bayesian optimization is an advanced tool to perform ecient global optimization It consists on enriching iteratively surrogate Kriging models of the objective and the constraints b…
High-Dimensional Bayesian Optimization Using Both Random and Supervised Embeddings
Rémy Priem, Youssef Diouane, Nathalie Bartoli +2
Bayesian optimization (BO) is one of the most powerful strategies to solve computationally expensive-to-evaluate blackbox optimization problems. However, BO methods are conventiona…