Proving strong duality for geometric optimization using a conic formulation

François Glineur (Francois.Glineurfpms.ac.be)

Abstract: Geometric optimization is an important class of problems that has many applications, especially in engineering design. In this article, we provide new simplified proofs for the well-known associated duality theory, using conic optimization. After introducing suitable convex cones and studying their properties, we model geometric optimization problems with a conic formulation, which allows us to apply the powerful duality theory of conic optimization and derive the duality results known for geometric optimization.

Keywords: convex optimization, conic optimization, geometric optimization

Category 1: Convex and Nonsmooth Optimization (Convex Optimization )

Category 2: Linear, Cone and Semidefinite Programming (Other )

Citation: IMAGE9903, Service MATHRO, Faculté Polytechnique de Mons, Mons, Belgium, Oct/99

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Entry Submitted: 02/21/2001
Entry Accepted: 02/21/2001
Entry Last Modified: 02/21/2001

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