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Indexed by:期刊论文

Date of Publication:2009-08-01

Journal:JOURNAL OF INDUSTRIAL AND MANAGEMENT OPTIMIZATION

Included Journals:SCIE、Scopus

Volume:5

Issue:3

Page Number:651-669

ISSN No.: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.