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

Atsushi Kato, Hiroshi Yabe, Hiroshi Yamashita

  • 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 its global convergence property under weaker assumptions than the method of Yamashita, Yabe and Harada.


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