This paper deals with convex optimization problems in the face of data uncertainty within the
framework of robust optimization. It provides various properties and characterizations of the …

In this paper, we deal with robust optimal solution sets for a class of optimization problems
with data uncertainty in both the objective and constraints. We first introduce a mixed-type …

This paper devotes to the quasi ϵ ϵ-solution (one sort of approximate solutions) for a robust
convex optimization problem in the face of data uncertainty. Using robust optimization …

This paper studies the vector optimization problem of finding weakly efficient points for maps
from Rn to Rm, with respect to the partial order induced by a closed, convex, and pointed …

A new approach to characterize the solution set of a nonconvex optimization problem via its
dual problem is proposed. Some properties of the Lagrange function associated to the …

In this paper, we study convex programming problems with data uncertainty in both the
objective function and the constraints. Under the framework of robust optimization, we …

We consider ϵ-solutions (approximate solutions) for a robust convex optimization problem in
the face of data uncertainty. Using robust optimization approach (worst-case approach), we …

In this paper, we obtain characterizations of solution sets of the interval-valued mathematical
programming problems with switching constraints. Stationary conditions which are weaker …

We establish necessary and sufficient conditions for a stable Farkas' lemma. We then derive
necessary and sufficient conditions for a stable duality of a cone-convex optimization …

In this paper, we consider an uncertain convex optimization problem with a robust convex
feasible set described by locally Lipschitz constraints. Using robust optimization approach …