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An interior point method with a primal-dual quadratic barrier penalty function for nonlinear semidefinite programming

Atsushi Kato(j1410702***at***ed.kagu.tus.ac.jp)
Hiroshi Yabe(yabe***at***rs.kagu.tus.ac.jp)
Hiroshi Yamashita(hy***at***msi.co.jp)

Abstract: In this paper, we consider an interior point method for nonlinear semidefinite programming. Yamashita, Yabe and Harada presented a primal-dual interior point method in which a nondifferentiable merit function was used. By using shifted barrier KKT conditions, we propose a differentiable primal-dual merit function within the framework of the line search strategy, and prove the global convergence property of our method.

Keywords: Nonlinear semidefinite programming, Primal-dual interior point method, Primal-dual quadratic barrier penalty function, Global convergence

Category 1: Nonlinear Optimization (Constrained Nonlinear Optimization )

Citation:

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Entry Submitted: 02/11/2013
Entry Accepted: 02/11/2013
Entry Last Modified: 02/11/2013

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