Qualitative analysis of basic notions in parametric rough convex programming (parameters in the objective function and feasible region is a rough set)

Parametric studying of an optimization problem often yields a new insight into the optimization problem at hand. The behavior of optimal solution set is studied to detect the change of this behavior if the input data are changed. In this paper questions concerning how the optimal solution set changes with respect to perturbations in the rough data are investigated. It presents qualitative analysis of basic notions in parametric rough convex programming when parameters in the objective function and roughness exist in the constraints. Numerical examples are given to clarify the theory under development.