International audienceWe present a new proximity control bundle algorithm to minimize nonsmooth and nonconvex locally Lipschitz functions. In contrast with the traditional oracle-based methods in nonsmooth program- ming, our method is model-based and can accommodate cases where several Clarke subgradients can be computed at reasonable cost. We propose a new way to manage the proximity control parameter, which allows us to handle nonconvex objectives. We prove global convergence of our method in the sense that every accumulation point of the sequence of serious steps is critical. Our method is tested on a variety of examples in H∞-controller synthesis
In this paper, we consider a class of mathematical programs with switching constraints (MPSCs) where...
In this paper, we present a study of the proximal point algorithm using very general regularizations...
This chapter is devoted to algorithms for solving nonsmooth unconstrained difference of convex optim...
International audienceWe present a new proximity control bundle algorithm to minimize nonsmooth and ...
Cette thèse développe une méthode de faisceau non convexe pour la minimisation de fonctions localeme...
An algorithm based on a combination of the polyhedral and quadratic approximation is given for findi...
We present an algorithm to locally minimize nonsmooth, nonconvex functions. In order to find descent...
Nowadays, solving nonsmooth (not necessarily differentiable) optimization prob-lems plays a very imp...
We present a bundle type method for minimizing nonconvex nondifferentiable functions of several vari...
We present a numerical bundle-type method for local minimization of a real function of several varia...
In this paper, a new algorithm to locally minimize nonsmooth functions represented as a difference o...
Abstract. The problem of maximizing a nonsmooth convex function over an arbitrary set is considered....
We consider the problem of minimizing the composition of a nonsmooth function with a smooth mapping ...
Abstract—Nonsmooth variational analysis and related compu-tational methods are powerful tools that c...
© 2016 Society for Industrial and Applied Mathematics. The numerical realization of the dynamic prog...
In this paper, we consider a class of mathematical programs with switching constraints (MPSCs) where...
In this paper, we present a study of the proximal point algorithm using very general regularizations...
This chapter is devoted to algorithms for solving nonsmooth unconstrained difference of convex optim...
International audienceWe present a new proximity control bundle algorithm to minimize nonsmooth and ...
Cette thèse développe une méthode de faisceau non convexe pour la minimisation de fonctions localeme...
An algorithm based on a combination of the polyhedral and quadratic approximation is given for findi...
We present an algorithm to locally minimize nonsmooth, nonconvex functions. In order to find descent...
Nowadays, solving nonsmooth (not necessarily differentiable) optimization prob-lems plays a very imp...
We present a bundle type method for minimizing nonconvex nondifferentiable functions of several vari...
We present a numerical bundle-type method for local minimization of a real function of several varia...
In this paper, a new algorithm to locally minimize nonsmooth functions represented as a difference o...
Abstract. The problem of maximizing a nonsmooth convex function over an arbitrary set is considered....
We consider the problem of minimizing the composition of a nonsmooth function with a smooth mapping ...
Abstract—Nonsmooth variational analysis and related compu-tational methods are powerful tools that c...
© 2016 Society for Industrial and Applied Mathematics. The numerical realization of the dynamic prog...
In this paper, we consider a class of mathematical programs with switching constraints (MPSCs) where...
In this paper, we present a study of the proximal point algorithm using very general regularizations...
This chapter is devoted to algorithms for solving nonsmooth unconstrained difference of convex optim...