Mathematical programming problems involving continuum of inequality constraints
Maximal monotone relations and the second derivatives of nonsmooth functions
Method for solving a convex integer programming problem.
Méthodes du second ordre dans les problèmes d'optimisation avec contraintes
Metric subregularity for nonclosed convex multifunctions in normed spaces
In terms of the normal cone and the coderivative, we provide some necessary and/or sufficient conditions of metric subregularity for (not necessarily closed) convex multifunctions in normed spaces. As applications, we present some error bound results for (not necessarily lower semicontinuous) convex functions on normed spaces. These results improve and extend some existing error bound results.
Minimal-Energy Clusters of Hard Spheres.
Minimisation d'une fonction convexe séparable avec contraintes de rapport entre les variables
Minimization of nonsmooth convex functionals in Banach spaces.
Minimizing convex functions by continuous descent methods.
Modélisation et optimisation numérique pour la reconstruction d'un polyèdre à partir de son image gaussienne généralisée
Modified golden ratio algorithms for pseudomonotone equilibrium problems and variational inequalities
We propose a modification of the golden ratio algorithm for solving pseudomonotone equilibrium problems with a Lipschitz-type condition in Hilbert spaces. A new non-monotone stepsize rule is used in the method. Without such an additional condition, the theorem of weak convergence is proved. Furthermore, with strongly pseudomonotone condition, the $R$-linear convergence rate of the method is established. The results obtained are applied to a variational inequality problem, and the convergence rate...
Monotone point-to-set vector fields.
Monotonicity of the Lagrangian function in the parametric interior point methods of convex programming.
Multifonctions s.c.i. et régularisée s.c.i. essentielle
Multi-objective Optimization Problem with Bounded Parameters
In this paper, we propose a nonlinear multi-objective optimization problem whose parameters in the objective functions and constraints vary in between some lower and upper bounds. Existence of the efficient solution of this model is studied and gradient based as well as gradient free optimality conditions are derived. The theoretical developments are illustrated through numerical examples.