DYNAMIC DUALIZATION IN A GENERAL SETTING

Abstract

Recently, Iwamoto, Kimura, and Ueno proposed dynamic dualization to present dual problems for unconstrained optimization problems whose objective function is a sum of squares. The aim of this paper is to show that dynamic dualization works well for unconstrained problems whose objective function is a sum of convex functions. Further we give another way to get dual problems, which is based on the infimal convolution. In both approaches we make clear the assumption for duality to hold.