Optimization Online


On the Central Paths and Cauchy Trajectories in Semidefinite Programming

Julio Lopez(jclopez***at***dim.uchile.cl)
Hector Ramirez C.(hramirez***at***dim.uchile.cl)

Abstract: In this work, we study the properties of central paths, defined with respect to a large class of penalty and barrier functions, for convex semidefinite programs. The type of programs studied here is characterized by the minimization of a smooth and convex objective function subject to a linear matrix inequality constraint. So, it is a particular case of convex programming with conic constraints. The studied class of functions consists of spectrally defined functions induced by penalty or barrier maps defined over the real nonnegative numbers. We prove the convergence of the (primal, dual and primal-dual) central path toward a (primal, dual, primal-dual, respectively) solution of our problem. Finally, we prove the global existence of Cauchy trajectories in our context and we recall its relation with primal central path when linear semidefinite programs are considered. Some illustrative examples are shown at the end of this paper.

Keywords: Semidefinite programming, central paths, penalty/barrier functions, Riemannian geometry, Cauchy trajectories.

Category 1: Linear, Cone and Semidefinite Programming (Semi-definite Programming )

Citation: DIM-CMM N: CMM-B-09/08-227, Universidad de Chile, Aug/2009.

Download: [Postscript][PDF]

Entry Submitted: 09/01/2009
Entry Accepted: 09/01/2009
Entry Last Modified: 09/01/2009

Modify/Update this entry

  Visitors Authors More about us Links
  Subscribe, Unsubscribe
Digest Archive
Search, Browse the Repository


Coordinator's Board
Classification Scheme
Give us feedback
Optimization Journals, Sites, Societies
Mathematical Programming Society