collaborators
Showing math.OCShow all

6 papers · 1 filter

math.OC2026

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…

math.OC2026

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…

math.OC2026

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…

math.OC2026

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…

math.OC2018

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…

math.OC2018

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…