Open Access
2013 A Newton-Like Trust Region Method for Large-Scale Unconstrained Nonconvex Minimization
Yang Weiwei, Yang Yueting, Zhang Chenhui, Cao Mingyuan
Abstr. Appl. Anal. 2013: 1-6 (2013). DOI: 10.1155/2013/478407

Abstract

We present a new Newton-like method for large-scale unconstrained nonconvex minimization. And a new straightforward limited memory quasi-Newton updating based on the modified quasi-Newton equation is deduced to construct the trust region subproblem, in which the information of both the function value and gradient is used to construct approximate Hessian. The global convergence of the algorithm is proved. Numerical results indicate that the proposed method is competitive and efficient on some classical large-scale nonconvex test problems.

Citation

Download Citation

Yang Weiwei. Yang Yueting. Zhang Chenhui. Cao Mingyuan. "A Newton-Like Trust Region Method for Large-Scale Unconstrained Nonconvex Minimization." Abstr. Appl. Anal. 2013 1 - 6, 2013. https://doi.org/10.1155/2013/478407

Information

Published: 2013
First available in Project Euclid: 27 February 2014

zbMATH: 1291.90192
MathSciNet: MR3121405
Digital Object Identifier: 10.1155/2013/478407

Rights: Copyright © 2013 Hindawi

Vol.2013 • 2013
Back to Top