On an Extension of Condition Number Theory to Nonconic Convex Optimization

The purpose of this paper is to extend, as much as possible, the modern theory of condition numbers for conic convex optimization: z∗ := minx ctx s.t. Ax− b ∈ CY x ∈ CX , to the more general non-conic format: (GPd) z∗ := minx ctx s.t. Ax− b ∈ CY x ∈ P , where P is any closed convex set, not necessarily a cone, which we call the groundset. Although any convex problem can be transformed to conic form, such transformations are neither unique nor natural given the natural description of many problems, thereby diminishing the relevance of data-based condition number theory. Herein we extend the modern theory of condition numbers to the problem format (GPd). As a byproduct, we are able to state and prove natural extensions of many theorems from the conic-based theory of condition numbers to this broader problem format.