By means of a conjugation scheme based on generalized convex conjugation theory instead of Fenchel conjugation, we build an alternative dual problem, using the perturbational approach, for a general optimization one defined on a separated locally convex topological space. Conditions guaranteeing strong duality for primal problems which are perturbed by continuous linear functionals and their respective dual problems, which is named stable strong duality, are established. In these conditions, the fact that the perturbation function is evenly convex will play a fundamental role. Stable strong duality will also be studied in particular for Fenchel and Lagrange primal–dual problems, obtaining a characterization for Fenchel case.This research wa...
AbstractBifunctional Duality, Lagrange Duality, and Fenchel Duality in convex programming are presen...
AbstractIn this article we provide weak sufficient strong duality conditions for a convex optimizati...
This paper deals with the robust strong duality for nonconvex optimization problem with the data unc...
By means of a conjugation scheme based on generalized convex conjugation theory instead of Fenchel c...
Via perturbational approach, we give an alternative dual problem for a general infinite dimensional ...
With this thesis we bring some new results and improve some existing ones in conjugate duality and s...
Abstract. We consider the optimization problem (PA) inf x∈X {f(x) + g(Ax)} where f and g are proper ...
In this work, we obtain a Fenchel–Lagrange dual problem for an infinite dimensional optimization pri...
An evenly convex function on a locally convex space is an extended real-valued function, whose epigr...
We consider the optimization problem (PA) infx∈X{f(x) + g(Ax)} where f and g are proper convex funct...
We consider the optimization problem (PA) infx∈X{f(x) + g(Ax)} where f and g are proper convex funct...
AbstractWe give some necessary and sufficient conditions which completely characterize the strong an...
The paper deals with optimization problems with uncertain constraints and linear perturbations of th...
preprint version The conjugate duality, which states that infx∈X φ(x, 0) = maxv∈Y ′ −φ∗(0, v), when...
Author name used in this publication: X. Q. Yang.2011-2012 > Academic research: refereed > Publicati...
AbstractBifunctional Duality, Lagrange Duality, and Fenchel Duality in convex programming are presen...
AbstractIn this article we provide weak sufficient strong duality conditions for a convex optimizati...
This paper deals with the robust strong duality for nonconvex optimization problem with the data unc...
By means of a conjugation scheme based on generalized convex conjugation theory instead of Fenchel c...
Via perturbational approach, we give an alternative dual problem for a general infinite dimensional ...
With this thesis we bring some new results and improve some existing ones in conjugate duality and s...
Abstract. We consider the optimization problem (PA) inf x∈X {f(x) + g(Ax)} where f and g are proper ...
In this work, we obtain a Fenchel–Lagrange dual problem for an infinite dimensional optimization pri...
An evenly convex function on a locally convex space is an extended real-valued function, whose epigr...
We consider the optimization problem (PA) infx∈X{f(x) + g(Ax)} where f and g are proper convex funct...
We consider the optimization problem (PA) infx∈X{f(x) + g(Ax)} where f and g are proper convex funct...
AbstractWe give some necessary and sufficient conditions which completely characterize the strong an...
The paper deals with optimization problems with uncertain constraints and linear perturbations of th...
preprint version The conjugate duality, which states that infx∈X φ(x, 0) = maxv∈Y ′ −φ∗(0, v), when...
Author name used in this publication: X. Q. Yang.2011-2012 > Academic research: refereed > Publicati...
AbstractBifunctional Duality, Lagrange Duality, and Fenchel Duality in convex programming are presen...
AbstractIn this article we provide weak sufficient strong duality conditions for a convex optimizati...
This paper deals with the robust strong duality for nonconvex optimization problem with the data unc...