A superlinearly convergent SSDP algorithm for nonlinear semidefinite programming

A superlinearly convergent SSDP algorithm for nonlinear semidefinite programming

Abstract In this paper, we present a sequential semidefinite programming (SSDP) algorithm for nonlinear semidefinite programming. At each iteration, a linear semidefinite programming subproblem and a modified quadratic semidefinite programming subproblem are solved to generate a master search direct...

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Bibliographic Details
Main Authors: Jian Ling Li, Hui Zhang
Format: Article
Language:English
Published: SpringerOpen 2019-08-01
Series:Journal of Inequalities and Applications
Subjects:
Nonlinear semidefinite programming
Penalty function
Sequential semidefinite programming
Global convergence
Superlinear convergence
Online Access:http://link.springer.com/article/10.1186/s13660-019-2171-y

Internet

http://link.springer.com/article/10.1186/s13660-019-2171-y

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