Nous proposons une méthode de régularisation pour les problèmes aux moindres carrés non linéaires avec contraintes d'égalité. Notre appliquons les approches...

The present work is in a context of derivative-free optimization involving direct search algorithms guided by surrogate models of the original problem. The...

In the interest of full disclosure, the reader is advised that I am biased positively towards the book considered here as I have collaborated with its first ...

Nous proposons un algorithm pour les problèmes d’optimisation non linéaire avec contraintes d’égalité basé sur une fonction de pénalité lisse proposée par ...

Algorithms for finding sparse solutions of underdetermined systems of linear equations have been the subject of intense interest in recent years, sparked b...

We describe LNLQ for solving the least-norm problem \(\min\ \|x\|\) subject to \(Ax=b\). Craig's method is known to be equivalent to applying the conjug...

Derivative-free optimization (DFO) is the mathematical study of the optimization algorithms that do not use derivatives. One branch of DFO focuses on model-...

The mesh adaptive direct search (MADS) algorithm is designed for blackbox optimization problems for which the functions defining the objective and the constr...

We propose an infeasible interior-point algorithm for constrained linear least-squares problems based on the primal-dual regularization of convex program...

We investigate surrogate-assisted strategies for global derivative-free optimization using the mesh adaptive direct search MADS blackbox optimization algorit...

Dans cet article, nous proposons une méthode d'optimisation sans factorisation pour les problèmes avec contraintes d'égalité pour lequel toutes les contrai...

For optimization problems involving many nonlinear inequality constraints, we extend the bound-constrained (BCL) and linearly-constrained (LCL) augmented-La...

Despite the lack of theoretical and practical convergence support, the Nelder-Mead (NM) algorithm is widely used to solve unconstrained optimization proble...

Nous considérons les problèmes d'optimisation sans dérivées avec variables continues, entières, discrètes et de catégorie dans le contexte d'applications i...

Global optimization problems are very hard to solve, especially when the nonlinear constraints are highly nonconvex, which can result in a large number of di...

We study X-ray tomograqphic reconstruction using statistical methods. The problem is expressed in cylindrical coordinates, which yield significant computatio...

The particularities of the aircraft parts riveting process simulation necessitate the solution of a large amount of contact problems. We propose a primal-dua...

Nanoparticle-based drug delivery is a promising method to increase the therapeutic index of anti-cancer agents with low median toxic dose. The delivery effic...

The problem of output stabilization is studied for a class of linear hybrid systems subject to signal uncertainties: linear impulsive systems under dwell-t...