1 citations · 1 across the 6 of their papers we have counts for
7 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…
A Line-Search Algorithm Inspired by the Adaptive Cubic Regularization Framework and Complexity Analysis
El houcine Bergou, Youssef Diouane, Serge Gratton
Adaptive regularized framework using cubics has emerged as an alternative to line-search and trust-region algorithms for smooth nonconvex optimization, with an optimal complexity a…
A Merit Function Approach for Evolution Strategies
Youssef Diouane
In this paper, we extend a class of globally convergent evolution strategies to handle general constrained optimization problems. The proposed framework handles relaxable constrain…