An Iterative Regularized Incremental Projected Subgradient Method for a Class of Bilevel Optimization Problems

Understand

We study a class of bilevel convex optimization problems where the goal is to find the minimizer of an objective function in the upper level, among the set of all optimal solutions of an optimization problem in the lower level.

• A wide range of problems in convex optimization can be formulated using this class.
• An important example is the case where an optimization problem is ill-posed.
• In this paper, our interest lies in addressing the bilevel problems, where the lower level objective is given as a finite sum of separate nondifferentiable convex component functions.