A globally convergent QP-free algorithm for nonlinear semidefinite programming

In this paper, we present a QP-free algorithm for nonlinear semidefinite programming. At each iteration, the search direction is yielded by solving two systems of linear equations with the same coefficient matrix; [Formula: see text] penalty function is used as merit function for line search, the st...

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Detalles Bibliográficos
Autores principales: Li, Jian-Ling, Yang, Zhen-Ping, Jian, Jin-Bao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2017
Materias:
Research
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5488296/
https://www.ncbi.nlm.nih.gov/pubmed/28680248
http://dx.doi.org/10.1186/s13660-017-1415-y
Descripción
Sumario:In this paper, we present a QP-free algorithm for nonlinear semidefinite programming. At each iteration, the search direction is yielded by solving two systems of linear equations with the same coefficient matrix; [Formula: see text] penalty function is used as merit function for line search, the step size is determined by Armijo type inexact line search. The global convergence of the proposed algorithm is shown under suitable conditions. Preliminary numerical results are reported.

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