Exact Penalties for Decomposable Optimization Problems

Abstract

We consider a general decomposable convex optimization problem. By using right-hand side allocation technique, it can be transformed into a collection of small dimensional optimization problems. The master problem is a convex non-smooth optimization problem. We propose to apply the exact non-smooth penalty method, which gives a solution of the initial problem under some fixed penalty parameter and provides the consistency of lower level problems. The master problem is suggested to be solved by a two-speed subgradient projection method, which enhances the step-size selection. Preliminary results of computational experiments confirm its efficiency.