5 papers
Bayesian Algorithm for Collaborative Optimization with Application to Aircraft Design
Mohamed Ali Belhafnaoui, Youssef Diouane
Collaborative Optimization (CO) is a multidisciplinary design optimization (MDO) framework that decomposes large-scale engineering problems into parallel, independently solvable su…
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…
A Spectral Preconditioner for the Conjugate Gradient Method with Iteration Budget
Youssef Diouane, Selime Gürol, Oussama Mouhtal +1
We study the solution of large symmetric positive-definite linear systems in a matrix-free setting with a limited iteration budget. We focus on the preconditioned conjugate gradien…
Surrogate-based categorical neighborhoods for mixed-variable blackbox optimization
Charles Audet, Youssef Diouane, Edward Hallé-Hannan +2
In simulation-based engineering, design choices are often obtained following the optimization of complex blackbox models. These models frequently involve mixed-variable domains wit…