Semidefinite Programming: Optimality Conditions and Stability

2012 ◽  
Keyword(s):  
Semidefinite Programming ◽  
Optimality Conditions

Optimality Conditions in Semidefinite Programming

2014 ◽  
Vol 35 (7-9) ◽  
pp. 1174-1196 ◽  
Author(s):  
Jean-Paul Penot
Keyword(s):  
Semidefinite Programming ◽  
Optimality Conditions

scholarly journals Optimality conditions for nonlinear semidefinite programming via squared slack variables

2016 ◽  
Vol 168 (1-2) ◽  
pp. 177-200 ◽  
Author(s):  
Bruno F. Lourenço ◽  
Ellen H. Fukuda ◽  
Masao Fukushima
Keyword(s):  
Semidefinite Programming ◽  
Optimality Conditions ◽  
Nonlinear Semidefinite Programming ◽  
Slack Variables

Optimality conditions for nonsmooth semidefinite programming via convexificators

Positivity ◽  
2014 ◽  
Vol 19 (2) ◽  
pp. 221-236 ◽  
Author(s):  
M. Golestani ◽  
S. Nobakhtian
Keyword(s):  
Semidefinite Programming ◽  
Optimality Conditions

Optimality conditions and global convergence for nonlinear semidefinite programming

2018 ◽  
Vol 180 (1-2) ◽  
pp. 203-235 ◽  
Author(s):  
Roberto Andreani ◽  
Gabriel Haeser ◽  
Daiana S. Viana
Keyword(s):  
Global Convergence ◽  
Semidefinite Programming ◽  
Optimality Conditions ◽  
Nonlinear Semidefinite Programming

Semidefinite Programming: Optimality Conditions and Stability

2008 ◽  
pp. 3380-3384
Author(s):  
Alexander Shapiro
Keyword(s):  
Semidefinite Programming ◽  
Optimality Conditions

scholarly journals PREDICTOR–CORRECTOR SMOOTHING NEWTON METHOD FOR SOLVING SEMIDEFINITE PROGRAMMING

2009 ◽  
Vol 79 (3) ◽  
pp. 367-376
Author(s):  
CAIYING WU ◽  
GUOQING CHEN
Keyword(s):  
Global Convergence ◽  
Semidefinite Programming ◽  
Optimality Conditions ◽  
Newton Method ◽  
Superlinear Convergence ◽  
Smoothing Newton Method ◽  
Equivalent Transformation ◽  
Newton Algorithm ◽  
Smoothing Methods ◽  
Predictor Corrector

AbstractThere has been much interest recently in smoothing methods for solving semidefinite programming (SDP). In this paper, based on the equivalent transformation for the optimality conditions of SDP, we present a predictor–corrector smoothing Newton algorithm for SDP. Issues such as the existence of Newton directions, boundedness of iterates, global convergence, and local superlinear convergence of our algorithm are studied under suitable assumptions.

Semidefinite Programming: Optimality Conditions and Stability

2006 ◽  
pp. 2312-2317
Author(s):  
Alexander Shapiro
Keyword(s):  
Semidefinite Programming ◽  
Optimality Conditions

Optimality conditions for nonconvex semidefinite programming

2000 ◽  
Vol 88 (1) ◽  
pp. 105-128 ◽  
Author(s):  
Anders Forsgren
Keyword(s):  
Semidefinite Programming ◽  
Optimality Conditions ◽  
Nonconvex Semidefinite Programming
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