most citedRegularized infill criteria for multi-objective Bayesian optimization with application to aircraft design

11 citations · 30 across the 6 of their papers we have counts for

collaborators

6 papers

cs.LG2025

Modèles de Substitution pour les Modèles à base d'Agents : Enjeux, Méthodes et Applications

Paul Saves, Nicolas Verstaevel, Benoît Gaudou

Multi-agent simulations enables the modeling and analyses of the dynamic behaviors and interactions of autonomous entities evolving in complex environments. Agent-based models (ABM…

cs.LG20253 cited

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…

cs.LG20257 cited

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…

stat.ME20259 cited

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…

cs.LG202511 cited

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…

cs.LG2025

SMT-EX: An Explainable Surrogate Modeling Toolbox for Mixed-Variables Design Exploration

Mohammad Daffa Robani, Paul Saves, Pramudita Satria Palar +2

Surrogate models are of high interest for many engineering applications, serving as cheap-to-evaluate time-efficient approximations of black-box functions to help engineers and pra…