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- Title
NONLINEAR CONJUGATE GRADIENT METHODS WITH SUFFICIENT DESCENT PROPERTIES FOR UNCONSTRAINED OPTIMIZATION.
- Authors
WATARU NAKAMURA; YASUSHI NARUSHIMA; HIROSHI YABE
- Abstract
It is very important to generate a descent search direction independent of line searches in showing the global convergence of conjugate gradient methods. The method of Hager and Zhang (2005) satisfies the sufficient descent condition. In this paper, we treat two subjects. We first consider a unified formula of parameters which establishes the sufficient descent condition and follows the modification technique of Hager and Zhang. In order to show the global convergence of the conjugate gradient method with the unified formula of parameters, we define some property (say Property A). We prove the global convergence of the method with Property A. Next, we apply the unified formula to a scaled conjugate gradient method and show its global convergence property. Finally numerical results are given.
- Subjects
CONJUGATE gradient methods; THEORY of descent (Mathematics); MATHEMATICAL optimization; STOCHASTIC convergence; PARAMETERS (Statistics); MATHEMATICAL formulas
- Publication
Journal of Industrial & Management Optimization, 2013, Vol 9, Issue 3, p595
- ISSN
1547-5816
- Publication type
Article
- DOI
10.3934/jimo.2013.9.595