Motivated by our collaboration with one of the largest fast-fashion retailers in Europe, we study a two-echelon inventory control problem called the One-Ware...

This paper presents PDENLPModels.jl a new Julia package for modeling and discretizing optimization problems with mixed algebraic and partial differential equ...

Providing the right data to a machine learning model is an important step to insure the performance of the model. Non-compliant training data instances may l...

Nous considérons la méthode de surrelaxation successive généralisée (GSOR) pour la résolution d’une classe de systèmes de points de selle à trois par trois...

Position estimation in Multi-Robot Systems (MRS) relies on relative angle or distance measurements between the robots, which generally deteriorate as dista...

We consider the problem of training a deep neural network with nonsmooth regularization to retrieve a sparse and efficient sub-structure. Our regularizer is ...

The conjugate gradient (CG) method is a classic Krylov subspace method for solving symmetric positive definite linear systems. We introduce an analogous sem...

Nous proposons une procédure pour calculer une projection de \(w \in ℝ^n\) dans l'intersection de la soi-disant boule en norme zéro \(k B_0\) de rayon ...

This paper presents DCISolver.jl a new Julia package implementating the Dynamic Control of Infeasibility method (DCI), introduced by Bielschowsky & Gomes (20...

Cette étude exploratoire est originale dans le champ de l'accompagnement. A partir de la base de données horodatées fournie par Google, notre étude retrace l...

In blackbox optimization, evaluation of the objective and constraint functions is time consuming. In some situations, constraint values may be evaluated in...

Une fonction de coût de Mayer constante par morceaux est requise pour correctement modéliser des problèmes de contrôle optimal dans lesquels l'espace des éta...

We introduce an iterative method named GPMR for solving 2X2 block unsymmetric linear systems. GPMR is based on a new process that reduces simultaneously...

This paper presents an efficient method for extracting the second-order sensitivities from a system of implicit nonlinear equations. We design a custom aut...

Pour un graphe simple et connexe \(G\), soient \(D(G), ~Tr(G)\), \(D^{L}(G)=Tr(G)-D(G)\), et \(D^{Q}(G)=Tr(G)+D(G)\) la matrice des distances, la mat...

In this paper, we consider both first- and second-order techniques to address continuous optimization problems arising in machine learning. In the first-orde...

This work is in the context of blackbox optimization where the functions defining the problem are expensive to evaluate and where no derivatives are availabl...

The goal of the Encyclopedia of Optimization is to introduce the reader to a complete set of topics that sh...

The Quadratic Knapsack Problem (QKP) is a well-known combinatorial optimization problem which amounts to maximizing a quadratic function of binary variables,...

NOMAD is software for optimizing blackbox problems. In continuous development since 2001, it constantly evolved with the integration of new algorithmic...