A hierarchy of polyhedral approximations of robust semidefinite programs

Abstract

Robust semidefinite programs are NP-hard in general. In contrast, robust linear programs admit equivalent reformulations as finite-dimensional convex programs provided that the problem data are parameterized affinely in the uncertain parameters; and that the underlying uncertainty set is described by an affine slice of a proper cone. In this paper, we… (More)
DOI: 10.1109/CDC.2016.7799356

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