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2008

A geometric framework for nonconvex optimization duality using augmented lagrangian functions

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A geometric framework for nonconvex optimization duality using augmented lagrangian functions
We provide a unifying geometric framework for the analysis of general classes of duality schemes and penalty methods for nonconvex constrained optimization problems. We present a separation result for nonconvex sets via general concave surfaces. We use this separation result to provide necessary and sufficient conditions for establishing strong duality between geometric primal and dual problems. Using the primal function of a constrained optimization problem, we apply our results both in the analysis of duality schemes constructed using augmented Lagrangian functions, and in establishing necessary and sufficient conditions for the convergence of penalty methods.
Angelia Nedic, Asuman E. Ozdaglar
Added 13 Dec 2010
Updated 13 Dec 2010
Type Journal
Year 2008
Where JGO
Authors Angelia Nedic, Asuman E. Ozdaglar
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