We associate a dual problem to a constrained optimization problem in which the ob-jective is quasiconvex and either attains at 0 its global minimum or its global maximum. The attractive features of such a duality are that it does not require an additional pa-rameter to set the dual and that the dual problem has a form which is similar to the one of the primal problem. We present conditions ensuring strong duality using separation properties. We relate our approach to the Lagrangian theory. Key words Coradiant set. Coradiant function, dual problem. Even convexity. Lagrangian. Quasiconvexity. Radiant set. Radiant function.
The paper studies radiant and coradiant sets of some normed space X from the point of view of separa...
In this paper, we study a nonconvex quadratic minimization problem with two quadratic constraints, o...
This thesis is centred around the topic of duality. It presents the classical duality theories in op...
Superlinear functionals are used to separate points from a radiant set according to both a strict an...
Superlinear functionals are used to separate points from a radiant set according to both a strict an...
Superlinear functionals are used to separate points from a radiant set according to both a strict an...
Primal or dual strong-duality (or min-sup, inf-max duality) in nonconvex optimization is revisited i...
AbstractIn this article we provide weak sufficient strong duality conditions for a convex optimizati...
An open question in the study of quasiconvex function is the characterization of the class of functi...
textabstractIn the first chapter of this book the basic results within convex and quasiconvex analys...
In this paper we consider the problem of minimizing a nonconvex quadratic function, subject to two q...
The paper studies radiant and coradiant sets of some normed space X from the point of view of separa...
Nondifferentiable quasiconvex programming problems are studied using Clarke's subgradients. Several ...
AbstractIn this paper we introduce a concept of quasiconjugate for functions defined on Rn whose val...
The well-known perturbational duality theory for convex optimization is refined to handle directly, ...
The paper studies radiant and coradiant sets of some normed space X from the point of view of separa...
In this paper, we study a nonconvex quadratic minimization problem with two quadratic constraints, o...
This thesis is centred around the topic of duality. It presents the classical duality theories in op...
Superlinear functionals are used to separate points from a radiant set according to both a strict an...
Superlinear functionals are used to separate points from a radiant set according to both a strict an...
Superlinear functionals are used to separate points from a radiant set according to both a strict an...
Primal or dual strong-duality (or min-sup, inf-max duality) in nonconvex optimization is revisited i...
AbstractIn this article we provide weak sufficient strong duality conditions for a convex optimizati...
An open question in the study of quasiconvex function is the characterization of the class of functi...
textabstractIn the first chapter of this book the basic results within convex and quasiconvex analys...
In this paper we consider the problem of minimizing a nonconvex quadratic function, subject to two q...
The paper studies radiant and coradiant sets of some normed space X from the point of view of separa...
Nondifferentiable quasiconvex programming problems are studied using Clarke's subgradients. Several ...
AbstractIn this paper we introduce a concept of quasiconjugate for functions defined on Rn whose val...
The well-known perturbational duality theory for convex optimization is refined to handle directly, ...
The paper studies radiant and coradiant sets of some normed space X from the point of view of separa...
In this paper, we study a nonconvex quadratic minimization problem with two quadratic constraints, o...
This thesis is centred around the topic of duality. It presents the classical duality theories in op...