Global convergence of a two-parameter family of conjugate gradient methods without line search

Authors:
Xiongda Chen;Jie Sun
Affiliations:
High Performance Computing for Engineered Systems, Singapore-MIT Alliance, National University of Singapore, Singapore;Department of Decision Sciences, Faculty of Business Administration, National University of Singapore, Singapore
Venue:
Journal of Computational and Applied Mathematics - Special issue: Papers presented at the 1st Sino--Japan optimization meeting, 26-28 October 2000, Hong Kong, China
Year:
2002

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Abstract

We study the global convergence of a two-parameter family of conjugate gradient methods in which the line search procedure is replaced by a fixed formula of stepsize. This character is of significance if the line search is expensive in a particular application. In addition to the convergence results, we present computational results for various conjugate gradient methods without line search including those discussed by Sun and Zhang. (Ann. Oper. Res. 103 (2001) 161-173).