Table of Contents Author Guidelines Submit a Manuscript
Abstract and Applied Analysis
Volume 2013 (2013), Article ID 814912, 8 pages
Research Article

A Self-Adjusting Spectral Conjugate Gradient Method for Large-Scale Unconstrained Optimization

1School of Foreign Languages, Gannan Normal University, Ganzhou 341000, China
2School of Mathematics and Computer Sciences, Gannan Normal University, Ganzhou 341000, China

Received 21 February 2013; Accepted 17 March 2013

Academic Editor: Guoyin Li

Copyright © 2013 Yuanying Qiu et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


This paper presents a hybrid spectral conjugate gradient method for large-scale unconstrained optimization, which possesses a self-adjusting property. Under the standard Wolfe conditions, its global convergence result is established. Preliminary numerical results are reported on a set of large-scale problems in CUTEr to show the convergence and efficiency of the proposed method.