Carathéodory's lemma states that if we have a linear combination of vectors in n, we can rewrite this combination using a linearly independent subset. This lemma has been successfully applied in nonlinear optimization in many contexts. In this work we present a new version of this celebrated result, in which we obtained new bounds for the size of the coefficients in the linear combination and we provide examples where these bounds are useful. We show how these new bounds can be used to prove that the internal penalty method converges to KKT points, and we prove that the hypothesis to obtain this result cannot be weakened.The new bounds also provides us some new results of convergence for the quasi feasible interior point ℓ2-penalty method o...
We analyze the global convergence properties of a class of penalty methods for nonlinear programming...
An algorithm for linear programming (LP) and convex quadratic programming (CQP) is proposed, based o...
Recently, in [10], the authors presented a new large-update primal-dual method for Linear Optimizati...
Abstract. In [3], two interior-point ℓ2-penalty methods with strong global convergence properties we...
We study the local convergence of a primal-dual interior point method for nonlinear programming. A l...
International audienceIn this paper, we propose a modified primal-dual interior-point method for non...
The aim of this paper is to show that the theorem on the global convergence of the Newton interior-...
robust primal-dual interior point algorithm for nonlinear programs ∗ Xinwei Liu†and Jie Sun‡ Abstrac...
This paper presents the convergence proof and complexity analysis of an interior-point framework tha...
Abstract An exact-penalty-function-based scheme--inspired from an old idea due to Mayne and Polak (M...
International audienceWe present a uniform boundedness property of a sequence of in- verses of Jacob...
In this research, we discuss linear and nonlinear programming problems and methods. We have implemen...
In this work we consider a linesearch globalization of the local primal-dual interior-point Newton m...
Abstract. In this work, we first study in detail the formulation of the primal-dual interior-point m...
In this paper, we describe a variant of the Newton Interior{Point method in [8] for nonlinear progra...
We analyze the global convergence properties of a class of penalty methods for nonlinear programming...
An algorithm for linear programming (LP) and convex quadratic programming (CQP) is proposed, based o...
Recently, in [10], the authors presented a new large-update primal-dual method for Linear Optimizati...
Abstract. In [3], two interior-point ℓ2-penalty methods with strong global convergence properties we...
We study the local convergence of a primal-dual interior point method for nonlinear programming. A l...
International audienceIn this paper, we propose a modified primal-dual interior-point method for non...
The aim of this paper is to show that the theorem on the global convergence of the Newton interior-...
robust primal-dual interior point algorithm for nonlinear programs ∗ Xinwei Liu†and Jie Sun‡ Abstrac...
This paper presents the convergence proof and complexity analysis of an interior-point framework tha...
Abstract An exact-penalty-function-based scheme--inspired from an old idea due to Mayne and Polak (M...
International audienceWe present a uniform boundedness property of a sequence of in- verses of Jacob...
In this research, we discuss linear and nonlinear programming problems and methods. We have implemen...
In this work we consider a linesearch globalization of the local primal-dual interior-point Newton m...
Abstract. In this work, we first study in detail the formulation of the primal-dual interior-point m...
In this paper, we describe a variant of the Newton Interior{Point method in [8] for nonlinear progra...
We analyze the global convergence properties of a class of penalty methods for nonlinear programming...
An algorithm for linear programming (LP) and convex quadratic programming (CQP) is proposed, based o...
Recently, in [10], the authors presented a new large-update primal-dual method for Linear Optimizati...