This paper deals with robust quasi approximate optimal solutions for a nonsmooth semi-infinite optimization problems with uncertainty data. By virtue of the epigraphs of the conjugates of the constraint functions, we first introduce a robust type closed convex constraint qualification. Then, by using the robust type closed convex constraint qualification and robust optimization technique, we obtain some necessary and sufficient optimality conditions for robust quasi approximate optimal solution and exact optimal solution of this nonsmooth uncertain semi-infinite optimization problem. Moreover, the obtained results in this paper are applied to a nonsmooth uncertain optimization problem with cone constraints
Abstract This paper deals with convex optimization problems in the face of data uncertainty within t...
We investigate a constrained optimization problem for which there is uncertainty about a constraint ...
© 2017 Springer-Verlag GmbH Germany In this paper, we study convex programming problems with data un...
This note is devoted to the investigation of optimality conditions for robust approximate quasi weak...
We review our results for approximate solutions for a robust convex optimization problem with a geom...
In this paper, Karush-Kuhn-Tucker type robust necessary optimality conditions for a robust nonsmooth...
Abstract This paper provides some new results on robust approximate optimal solutions of a fractiona...
Robust optimization has come out to be a potent approach to study mathematical problems with data un...
This paper deals with the robust strong duality for nonconvex optimization problem with the data unc...
Abstract In this paper, we consider adjustable robust versions of convex optimiza-tion problems with...
This thesis discusses different methods for robust optimization problems that are convex in the unce...
Adjustable robust optimization (ARO) generally produces better worst-case solutions than static robu...
We investigate a constrained optimization problem for which there is uncertainty about a constraint ...
Abstract. We consider a rather general class of mathematical programming problems with data uncertai...
This paper considers an uncertain convex optimization problem, posed in a locally convex decision sp...
Abstract This paper deals with convex optimization problems in the face of data uncertainty within t...
We investigate a constrained optimization problem for which there is uncertainty about a constraint ...
© 2017 Springer-Verlag GmbH Germany In this paper, we study convex programming problems with data un...
This note is devoted to the investigation of optimality conditions for robust approximate quasi weak...
We review our results for approximate solutions for a robust convex optimization problem with a geom...
In this paper, Karush-Kuhn-Tucker type robust necessary optimality conditions for a robust nonsmooth...
Abstract This paper provides some new results on robust approximate optimal solutions of a fractiona...
Robust optimization has come out to be a potent approach to study mathematical problems with data un...
This paper deals with the robust strong duality for nonconvex optimization problem with the data unc...
Abstract In this paper, we consider adjustable robust versions of convex optimiza-tion problems with...
This thesis discusses different methods for robust optimization problems that are convex in the unce...
Adjustable robust optimization (ARO) generally produces better worst-case solutions than static robu...
We investigate a constrained optimization problem for which there is uncertainty about a constraint ...
Abstract. We consider a rather general class of mathematical programming problems with data uncertai...
This paper considers an uncertain convex optimization problem, posed in a locally convex decision sp...
Abstract This paper deals with convex optimization problems in the face of data uncertainty within t...
We investigate a constrained optimization problem for which there is uncertainty about a constraint ...
© 2017 Springer-Verlag GmbH Germany In this paper, we study convex programming problems with data un...