Release Time:2019-03-09  Hits:

Indexed by: Journal Article

Date of Publication: 2009-08-01

Journal: JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION

Included Journals: Scopus、SCIE

Volume: 5

Issue: 3

Page Number: 651-669

ISSN: 1547-5816

Key Words: nonconvex semidefinite programming; nonlinear Lagrangian; Lowner operator

Abstract: We present a nonlinear Lagrangian method for nonconvex semi-definite programming. This nonlinear Lagrangian is generated by a Lowner operator associated with Log-Sigmoid function. Under a set of assumptions, we prove a convergence theorem, which shows that the nonlinear Lagrangian algorithm is locally convergent when the penalty parameter is less than a threshold and the error bound of the solution is proportional to the penalty parameter.