From the 1 of 10 linked papers with an AI index.
1 citations · 1 across the 3 of their papers we have counts for
10 papers
An Inexact Modified Quasi-Newton Method for Nonsmooth Regularized Optimization
Nathan Allaire, Sébastien Le Digabel, Dominique Orban
The paper proposes iR2N, a modified proximal quasi‑Newton algorithm that handles nonsmooth regularized problems with inexact evaluations of the smooth part and proximal operators,…
Parallel versions of the mesh adaptive direct search algorithm
Sébastien Le Digabel, Antoine Lesage-Landry, Samuel Mendoza +1
This work surveys the different parallel variants of the mesh adaptive direct search (MADS) algorithm for constrained blackbox optimization. These problems can inherently imply hig…
Adaptive direct search algorithms with relaxable and quantifiable constraints
Charles Audet, Théo Denorme, Youssef Diouane +2
This work introduces ADS-PB, an extension of the Adaptive Direct Search (ADS) framework for solving constrained blackbox optimization problems. With ADS, iterates progress without…
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 penalty-interior point method combined with MADS for equality and inequality constrained optimization
Charles Audet, Andrea Brilli, Youssef Diouane +3
This work introduces MADS-PIP, an efficient framework that integrates a penalty-interior point strategy into the mesh adaptive direct search (MADS) algorithm for solving nonsmooth…
Multi-fidelity constraints in blackbox optimization
Stéphane Alarie, Charles Audet, Miguel Diago +2
This work studies constrained blackbox optimization problems that cannot be solved in reasonable time due to prohibitive computational costs. This challenge is especially prevalent…